Domains via approximation operators

In this paper, we tailor-make new approximation operators inspired by rough set theory and specially suited for domain theory. Our approximation operators offer a fresh perspective to existing concepts and results in domain theory, but also reveal ways to establishing novel domain-theoretic results. For instance, (1) the well-known interpolation property of the way-below relation on a continuous poset is equivalent to the idempotence of a certain set-operator; (2) the continuity of a poset can be characterized by the coincidence of the Scott closure operator and the upper approximation operator induced by the way below relation; (3) meet-continuity can be established from a certain property of the topological closure operator. Additionally, we show how, to each approximating relation, an associated order-compatible topology can be defined in such a way that for the case of a continuous poset the topology associated to the way-below relation is exactly the Scott topology. A preliminary investigation is carried out on this new topology.Comment: 17 pages; 1figure, Domains XII Worksho

Sense: Model Hardware Co-design for Accelerating Sparse CNN on Systolic Array

Sparsity is an intrinsic property of convolutional neural network(CNN) and worth exploiting for CNN accelerators, but extra processing comes with hardware overhead, causing many architectures suffering from only minor profit. Meanwhile, systolic array has been increasingly competitive on CNNs acceleration for its high spatiotemporal locality and low hardware overhead. However, the irregularity of sparsity induces imbalanced workload under the rigid systolic dataflow, causing performance degradation. Thus, this paper proposed a systolicarray-based architecture, called Sense, for sparse CNN acceleration by model-hardware co-design, achieving large performance improvement. To balance input feature map(IFM) and weight loads across Processing Element(PE) array, we applied channel clustering to gather IFMs with approximate sparsity for array computation, and co-designed a load-balancing weight pruning method to keep the sparsity ratio of each kernel at a certain value with little accuracy loss, improving PE utilization and overall performance. Additionally, Adaptive Dataflow Configuration is applied to determine the computing strategy based on the storage ratio of IFMs and weights, lowering 1.17x-1.8x DRAM access compared with Swallow and further reducing system energy consumption. The whole design is implemented on ZynqZCU102 with 200MHz and performs at 471-, 34-, 53- and 191-image/s for AlexNet, VGG-16, ResNet-50 and GoogleNet respectively. Compared against sparse systolic-array-based accelerators, Swallow, FESA and SPOTS, Sense achieves 1x-2.25x, 1.95x-2.5x and 1.17x-2.37x performance improvement on these CNNs respectively with reasonable overhead.Comment: 14 pages, 29 figures, 6 tables, IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEM

Firm Dynamics in News Driven Business Cycle: The Role of Endogenous Survival Rate

Evidences from structural VAR show that new business formation positively co-moves with output under news shocks. The Jaimovich-Rebelo model augmented with firm dynamics can explain the empirical findings. The key assumption is endogenous survival rates for new entrants

Firm Dynamics in News Driven Business Cycle: The Role of Endogenous Survival Rate

Evidences from structural VAR show that new business formation positively co-moves with output under news shocks. The Jaimovich-Rebelo model augmented with firm dynamics can explain the empirical findings. The key assumption is endogenous survival rates for new entrants

Firm Dynamics in News Driven Business Cycle: The Role of Endogenous Survival Rate

Evidences from structural VAR show that new business formation positively co-moves with output under news shocks. The Jaimovich-Rebelo model augmented with firm dynamics can explain the empirical findings. The key assumption is endogenous survival rates for new entrants

Seasonal variation in systemic lupus erythematosus and rheumatoid arthritis: an ecological study In based on internet searches

Systemic lupus erythematosus (SLE) is a prototypical autoimmune disease in which immune regulation is disrupted and characterized by intense inflammation and damage to multiple organs or systems. Rheumatoid arthritis (RA) is another systemic autoimmune disease characterized by chronic synovial joint inflammation that leads to disability and poor quality of life. Although the etiologies and pathogenesis of SLE and RA are not fully understood, it is generally accepted that they are both caused by interactions between genetic and environmental factors. In recent years, emerging studies have demonstrated the potential role of seasonality in the development and disease activity of variety of autoimmune diseases [[1], [2], [3]]

The c−c-differential uniformity and boomerang uniformity of three classes of permutation polynomials over F2n\mathbb{F}_{2^n}

Permutation polynomials with low $c$-differential uniformity and boomerang uniformity have wide applications in cryptography. In this paper, by utilizing the Weil sums technique and solving some certain equations over $\mathbb{F}_{2^n}$, we determine the $c$-differential uniformity and boomerang uniformity of these permutation polynomials: (1) $f_1(x)=x+\mathrm{Tr}_1^n(x^{2^{k+1}+1}+x^3+x+ux)$, where $n=2k+1$, $u\in\mathbb{F}_{2^n}$ with $\mathrm{Tr}_1^n(u)=1$; (2) $f_2(x)=x+\mathrm{Tr}_1^n(x^{{2^k}+3}+(x+1)^{2^k+3})$, where $n=2k+1$; (3) $f_3(x)=x^{-1}+\mathrm{Tr}_1^n((x^{-1}+1)^d+x^{-d})$, where $n$ is even and $d$ is a positive integer. The results show that the involutions $f_1(x)$ and $f_2(x)$ are APcN functions for $c\in\mathbb{F}_{2^n}\backslash \{0,1\}$. Moreover, the boomerang uniformity of $f_1(x)$ and $f_2(x)$ can attain $2^n$. Furthermore, we generalize some previous works and derive the upper bounds on the $c$-differential uniformity and boomerang uniformity of $f_3(x)$

Robust time synchronisation for industrial internet of things by H∞ output feedback control

Precise timing over timestamped packet exchange communication is an enabling technology in the mission-critical industrial Internet of Things, particularly when satellite-based timing is unavailable. The main challenge is to ensure timing accuracy when the clock synchronisation system is subject to disturbances caused by the drifting frequency, time-varying delay, jitter, and timestamping uncertainty. In this work, a Robust Packet-Coupled Oscillators (R-PkCOs) protocol is proposed to reduce the effects of perturbations manifested in the drifting clock, timestamping uncertainty and delays. First, in the spanning tree clock topology, time synchronisation between an arbitrary pair of clocks is modelled as a state-space model, where clock states are coupled with each other by one-way timestamped packet exchange (referred to as packet coupling), and the impacts of both drifting frequency and delays are modelled as disturbances. A static output controller is adopted to adjust the drifting clock. The H∞ robust control design solution is proposed to guarantee that the ratio between the modulus of synchronisation precision and the magnitude of the disturbances is always less than a given value. Therefore, the proposed time synchronisation protocol is robust against the disturbances, which means that the impacts of drifting frequency and delays on the synchronisation accuracy are limited. The one-hour experimental results demonstrate that the proposed R-PkCOs protocol can realise time synchronisation with the precision of six microseconds in a 21-node IEEE 802.15.4 network. This work has widespread impacts in the process automation of automotive, mining, oil and gas industries