Secure three-party computational protocols for triangle area

In this work, we have put forth two different protocols to address a concrete secure multi-party computational (MPC) problem related to a triangle, of which the coordinates of the three vertices are confidentially kept by the three participants, respectively. The three parties wish to collaboratively compute the area of this triangle while preserving their own coordinate privacy. As one of the merits, our protocols employ weaker assumptions of the existence of pseudorandom generators. In particular, unlike massive secure MPC protocols that rely a lot on oblivious transfer, ours utilize a new computing idea called “pseudorandom-then-rounding” method to avoid this burdensome obstacle. The two protocols are based on different theorems, while they both make use of the same underlying idea. At last, we provide a detailed proof for the first protocol by a series of security reductions of our newly defined games, which seems somewhat stronger than the previous simulation-based proofs and a proof sketch for the second one. Analysis and discussion about the reasons are provided as well to round off our work.     

在ASP.NET 2.0中自动化构建数据访问层

使用ASP.NET2.0所提供的BuildProvider类,将自动化构建的数据访问层源代码编译到程序集中,使得开发者利用Ob-jectDataSource控件,可以简单、快速地实现三层架构的Web应用。     

基于AR技术的光交箱资源校准技术

光交箱端口状态对通信网络的正常运行具有重要作用,由于光交箱内部布线杂乱,容易对端口产生排线遮挡问题,导致传统的光交箱端口图像识别操作不便。文中提出了一种基于AR技术的光交箱资源校准技术,该技术可以对实时视频自适应选取关键帧,然后对关键帧进行光交箱端口状态和文字识别,最后返回加权融合后的识别结果,并利用实时AR交互指引巡检人员处理被遮挡端口,这不仅能提升巡检人员的工作效率,还能提高实时识别准确率。将该校准技术应用到光交箱端口的智能检测中,能对光交箱的端口识别提供极大便利。     

Tuning the band gap of the CIGS solar buffer layer Cd1-xZnxS (x=0—1) to achieve high efficiency

To evaluate the impact of zinc sulfate (ZnSO4) concentration on the structural properties of the films, Cd1-xZnxS thin films were formed on glass substrates using chemical bath deposition (CBD) in this study. The effect of ZnSO4 precursor concentration on the surface morphology, optical properties, and morphological structure of the Cd1-xZnxS films was investigated. To study the impact of zinc doping content on the performance metrics of Cu(In1-xGax)Se2 (CIGS) cells in the experimental group and to improve the buffer layer thickness, simulations were run using one-dimensional solar cell capacitance simulator (SCAPS-1D) software.     

Adaptive Clustered Federated Learning for Heterogeneous Data in Edge Computing

Mobile Networks and Applications - Although federated learning has been widely used in collaborative training of machine learning models, its practical uses are still challenged by heterogeneous...     

Low-rank tensor completion via combined Tucker and Tensor Train for color image recovery

Applied Intelligence - In recent years, low-rank tensor completion has been widely used in color image recovery. Tensor Train (TT), as a balanced tensor rank minimization method, has achieved good...     

Super connectivity of Kronecker products of graphs

Let G₁ and G₂ be two connected graphs. The Kronecker product G₁×G₂ has vertex set V(G₁×G₂)=V(G₁)×V(G₂) and the edge set . In this paper, we show that if G is a bipartite graph with κ(G)=δ(G), then G×Kn(n?3) is super-κ.     

ADAPTIVE RANKS CLONE AND k‐NEAREST NEIGHBOR LIST–BASED IMMUNE MULTI‐OBJECTIVE OPTIMIZATION

Artificial immune systems (AIS) are computational systems inspired by the principles and processes of the vertebrate immune system. The AIS‐based algorithms typically exploit the immune system's characteristics of learning and adaptability to solve some complicated problems. Although, several AIS‐based algorithms have proposed to solve multi‐objective optimization problems (MOPs), little focus have been placed on the issues that adaptively use the online discovered solutions. Here, we proposed an adaptive selection scheme and an adaptive ranks clone scheme by the online discovered solutions in different ranks. Accordingly, the dynamic information of the online antibody population is efficiently exploited, which is beneficial to the search process. Furthermore, it has been widely approved that one‐off deletion could not obtain excellent diversity in the final population; therefore, a k‐nearest neighbor list (where k is the number of objectives) is established and maintained to eliminate the solutions in the archive population. The k‐nearest neighbors of each antibody are founded and stored in a list memory. Once an antibody with minimal product of k‐nearest neighbors is deleted, the neighborhood relations of the remaining antibodies in the list memory are updated. Finally, the proposed algorithm is tested on 10 well‐known and frequently used multi‐objective problems and two many‐objective problems with 4, 6, and 8 objectives. Compared with five other state‐of‐the‐art multi‐objective algorithms, namely NSGA‐II, SPEA2, IBEA, HYPE, and NNIA, our method achieves comparable results in terms of convergence, diversity metrics, and computational time.