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This research proposes a set of novel algorithms for structural reliability estimation based on muti-dimensional binary search tree and breadth-first search, namely the reliability accuracy supervised searching algorithm, the limit-state surface resolution supervised searching algorithm and the reliability index precision supervised fast searching algorithm. The proposed algorithms have the following strengths: 1, all the proposed algorithms have satisfactory computational efficiency by reducing redundant samplings; 2, their computational costs are stable and computable; 3, performance functions of high non-linearity can be will handled; 4, the reliability accuracy supervised searching algorithm can adapt its computational cost according to a prescribed accuracy; 5, the limit-state surface resolution supervised searching algorithm is able to probe sharp changes on limit-state surfaces; 6, the reliability index precision supervised fast searching algorithm computes the reliability index with sufficient precision in a fast way.

People who use social networks often fall prey to clickbait, which is commonly exploited by scammers. The scammer attempts to create a striking headline that attracts the majority of users to click an attached link. Users who follow the link can be redirected to a fraudulent resource, where their personal data are easily extracted. To solve this problem, a novel browser extension named ClickBaitSecurity is proposed, which helps to evaluate the security of a link. The novel extension is based on the legitimate and illegitimate list search (LILS) algorithm and the domain rating check (DRC) algorithm. Both of these algorithms incorporate binary search features to detect malicious content more quickly and more efficiently. Furthermore, ClickBaitSecurity leverages the features of a deep recurrent neural network (RNN). The proposed ClickBaitSecurity solution has greater accuracy in detecting malicious and safe links compared to existing solutions.

This paper presents a low jitter All-Digital Delay-Locked Loop (ADDLL) with fast lock time and process immunity. A coarse locking algorithm is proposed to prevent harmonic locking with just a small increase in hardware resources. In order to effectively solve the dithering phenomenon after locking, a replica delay line and a modified binary search algorithm with two modes were introduced in our ADDLL, which can significantly reduce the peak-to-peak jitter of the replica delay line. In addition, digital codes for a replica delay line can be conveniently applied to the delay line of multi-channel Vernier TDC while maintaining consistency between channels. The proposed ADDLL has been designed in 55 nm CMOS technology. In addition, the post-layout simulation results show that when operated at 1.2 V, the proposed ADDLL locks within 37 cycles and has a closed-loop characteristic, the peak-to-peak and root-mean-square jitter at 800 MHz are 6.5 ps and 1.18 ps, respectively. The active area is 0.024 mm2 and the power consumption at 800 MHz is 6.92 mW. In order to verify the performance of the proposed ADDLL, an architecture of dual ADDLL is applied to Vernier TDC to stabilize the Vernier delay lines against the process, voltage, and temperature (PVT) variations. With a 600 MHz operating frequency, the TDC achieves a 10.7 ps resolution, and the proposed ADDLL can keep the resolution stable even if PVT varies.

Abstract Today, Red-Black trees are becoming a popular data structure typically used to implement dictionaries, associative arrays, symbol tables within some compilers (C++, Java …) and many other systems. In this paper, we present an improvement of the delete algorithm of this kind of binary search tree. The proposed algorithm is very promising since it colors differently the tree while reducing color changes by a factor of about 29%. Moreover, the maintenance operations re-establishing Red-Black tree balance properties are reduced by a factor of about 11%. As a consequence, the proposed algorithm saves about 4% on running time when insert and delete operations are used together while conserving search performance of the standard algorithm.

Consider optimizing a periodic schedule for an automated production plant as a last step of a more comprehensive design process. In our scenario, each robot’s cyclic sequence of operations and trajectories between potential waiting points have already been fully specified. Further given are those precedences that fix sequence requirements on operations between different robots. It remains to determine the starting time for each operation or movement of each robot within a common cyclic time period so as to avoid collisions of robots that operate in the same space simultaneously. So the task is to find a conflict-resolving schedule that minimizes this common periodic cycle time while observing all precedence relations and collision avoidance constraints. The proposed cycle time minimization problem for robot coordination has, to the best of our knowledge, not been studied before. We develop an approach for solving it by employing binary search for determining the smallest feasible period time of an iso-periodic event scheduling problem (IPESP). This is a variant of the periodic event scheduling problem in which the objects that have to be scheduled need to obey exactly the same period time. The possibility to wait arbitrarily long at waiting points turns out to be essential to justify the use of binary search for identifying the minimum cycle time, thereby avoiding bilinear mixed integer formulations. Special properties of the given scenario admit bounds on the periodic tension variables of an integer programming formulation. Although the IPESP subproblems remain NP-complete in general, these bounds allow solving real-world instances sufficiently fast for the approach to be applicable in practice. Numerical experiments on real-world and randomly generated data are supplied to illustrate the potential and limitations of this approach. Summary of Contribution: When designing automated production plants, a crucial step is to identify the smallest possible per unit period time for the production processes. Based on periodic event scheduling ideas, we develop and analyze mathematical methods for this purpose. We show that the algorithmic implementation of our approach provides an answer to current real-world designs in reasonable time.

AbstractLow-rank inducing unitarily invariant norms have been introduced to convexify problems with a low-rank/sparsity constraint. The most well-known member of this family is the so-called nuclear norm. To solve optimization problems involving such norms with proximal splitting methods, efficient ways of evaluating the proximal mapping of the low-rank inducing norms are needed. This is known for the nuclear norm, but not for most other members of the low-rank inducing family. This work supplies a framework that reduces the proximal mapping evaluation into a nested binary search, in which each iteration requires the solution of a much simpler problem. The simpler problem can often be solved analytically as demonstrated for the so-called low-rank inducing Frobenius and spectral norms. The framework also allows to compute the proximal mapping of increasing convex functions composed with these norms as well as projections onto their epigraphs.