QoI-aware incentive for multimedia crowdsensing enabled learning system

While much research has been devoted to algorithm improvement of the machine learning model for multimedia applications, relatively little research has focused on the acquisition of massive multimedia datasets with strict data demands for model training. In this paper, we propose a Quality-of-Information (QoI) aware incentive mechanism in multimedia crowdsensing, with the objective of promoting the growth of an initial training model. We begin with a reverse auction incentive model to maximize social welfare while meeting the requirements in quality, timeliness, correlation, and coverage. Then, we discuss how to achieve the optimal social welfare in the presence of an NP-hard winner determination problem. Lastly, we design an effective incentive mechanism to solve the auction problem, which is shown to be truthful, individually rational and computationally efficient. Our evaluation study is carried out using a real multimedia dataset. Extensive simulation results demonstrate that the proposed incentive mechanism produces close-to-optimal social welfare noticeably, while accompanied by accelerating the growth of the machine learning model with a high-QoI dataset.     

Iron-Based Nanozymes in Disease Diagnosis and Treatment

Iron-based nanozymes are currently one of the few clinical inorganic nanoparticles for disease diagnosis and treatment. Overcoming the shortcomings of natural enzymes, such as easy inactivation and low yield, combined with their special nanometer properties and magnetic functions, iron-based nanozymes have broad prospects in biomedicine. This minireview summarizes their preparation, biological activity, catalytic mechanism, and applications in diagnosis and treatment of diseases. Finally, challenges to their future development and the trends of iron-based nanozymes are discussed. The purpose of this minireview is to better understand and reasonably speculate on the rational design of iron-based nanozymes as an increasingly important new paradigm for diagnostics.     

摩擦变形量对异种金属摩擦焊组织和性能影响研究

针对摩擦变形量对异种金属的焊接质量影响情况认识不充分这一问题,开展了摩擦变形量对焊缝组织及力学性能影响规律的研究。基于微观组织、显微硬度和力学性能的对比分析,对调质态42CrMo与正火态36Mn2V管材不同摩擦变形量的连续驱动摩擦焊进行了研究,为其在工程应用提供理论依据。     

Experimental studies and thermodynamic assessment of the Ba-Mo-O system by the CALPHAD method

Thermodynamic measurements on BaMoO₄, BaMoO₃ and BaMo₃O₁₀ are reported, that served as input for the development of a thermodynamic model of the Ba-Mo-O system using the CALPHAD methodology. The valence states of molybdenum in BaMoO₄ and BaMoO₃ were confirmed to be VI and IV, respectively, from X-ray Absorption Near Edge Structure Spectroscopy measurements at the Mo K-edge. The heat capacity at low temperatures of these compounds was obtained from thermal-relaxation calorimetry. Phase equilibrium data in the BaMoO₄-MoO₃ section were also measured, and the transition enthalpy associated with the peritectic decomposition of BaMo₃O₁₀ was determined using Differential Scanning Calorimetry. The developed thermodynamic model used the compound energy formalism for intermediate compounds, and an ionic two-sublattice model for the liquid phase. The optimized Gibbs energies were assessed with respect to the known thermodynamic and phase equilibrium data. A good agreement is generally obtained, but a number of ill-defined data were also identified.     

Exploration on efficient similar sentences extraction

Measuring the semantic similarity between sentences is an essential issue for many applications, such as text summarization, Web page retrieval, question-answer model, image extraction, and so forth. A few studies have explored on this issue by several techniques, e.g., knowledge-based strategies, corpus-based strategies, hybrid strategies, etc. Most of these studies focus on how to improve the effectiveness of the problem. In this paper, we address the efficiency issue, i.e., for a given sentence collection, how to efficiently discover the top-k semantic similar sentences to a query. The previous methods cannot handle the big data efficiently, i.e., applying such strategies directly is time consuming because every candidate sentence needs to be tested. In this paper, we propose efficient strategies to tackle such problem based on a general framework. The basic idea is that for each similarity, we build a corresponding index in the preprocessing. Traversing these indices in the querying process can avoid to test many candidates, so as to improve the efficiency. Moreover, an optimal aggregation algorithm is introduced to assemble these similarities. Our framework is general enough that many similarity metrics can be incorporated, as will be discussed in the paper. We conduct extensive experimental evaluation on three real datasets to evaluate the efficiency of our proposal. In addition, we illustrate the trade-off between the effectiveness and efficiency. The experimental results demonstrate that the performance of our proposal outperforms the state-of-the-art techniques on efficiency while keeping the same high precision as them.     

Optimal Representation of Large-Scale Graph Data Based on K2-Tree

Wireless Personal Communications - Graph is widely used to model data in various applications. With the rapid growth of many emerging applications such as Internet of Things, it is urgent to...     

Fault Prediction Based on the Kernel Function for Ribbon Wireless Sensor Networks

There exist several applications of wireless sensor networks in which the reliable operation can be crucial. Fault prediction is a critical problem in reliability theory for ribbon wireless sensor networks (RWSNs). Accurate fault prediction can effectively improve the availability of the WSNs system. In this paper, we evaluated the network performance for RWSNs, studied the basic theory of kernel functions, proposed a new failure prediction method based on kernel function, and selected the radial basis function as kernel function failure prediction models from two aspects of node hardware failures and network failures for fault prediction. Theoretical evidence and experimental results have shown that the proposed algorithmic prediction method has higher accuracy of 12 and 15% than that of GRNN and PNN respectively. Finally, we provided extensive numerical results to demonstrate the usage and efficiency of the proposed algorithms and complement our theoretical analysis.     

9号高炉热风炉1200℃风温攻关

新钢9号炉通过稳定高风温操作,为节焦降耗起到了良好的促进作用。