Approximate finite-dimensional ODE temperature model for microwave heating

In this paper, a finite-dimensional ordinary differential equation (ODE) model is proposed for predicting the temperature profile with microwave heating to accomplish lower computing complexity. The traditional parabolic partial different equation (PDE) model with integrating Maxwell's equation and heat transport equation is not suitable for designing the on-line controller. Based on the obstruction, using an auxiliary function derives an intermediate model, which is analyzed and discussed for model reduction by employing the parameter separation method and Galerkin's method. The simulation experiments on one-dimensional waveguide and cavity demonstrate that the proposed approximate model is effective

Monitoring Influenza Epidemics in China with Search Query from Baidu

Several approaches have been proposed for near real-time detection and prediction of the spread of influenza. These include search query data for influenza-related terms, which has been explored as a tool for augmenting traditional surveillance methods. In this paper, we present a method that uses Internet search query data from Baidu to model and monitor influenza activity in China. The objectives of the study are to present a comprehensive technique for: (i) keyword selection, (ii) keyword filtering, (iii) index composition and (iv) modeling and detection of influenza activity in China. Sequential time-series for the selected composite keyword index is significantly correlated with Chinese influenza case data. In addition, one-month ahead prediction of influenza cases for the first eight months of 2012 has a mean absolute percent error less than 11%. To our knowledge, this is the first study on the use of search query data from Baidu in conjunction with this approach for estimation of influenza activity in China

A Robust Collaborative Filtering Approach Based on User Relationships for Recommendation Systems

Personalized recommendation systems have been widely used as an effective way to deal with information overload. The common approach in the systems, item-based collaborative filtering (CF), has been identified to be vulnerable to “Shilling” attack. To improve the robustness of item-based CF, the authors propose a novel CF approach based on the mostly used relationships between users. In the paper, three most commonly used relationships between users are analyzed and applied to construct several user models at first. The DBSCAN clustering is then utilized to select the valid user model in accordance with how the models benefit detecting spam users. The selected model is used to detect spam user group. Finally, a detection-based CF method is proposed for the calculation of item-item similarities and rating prediction, by setting different weights for suspicious spam users and normal users. The experimental results demonstrate that the proposed approach provides a better robustness than the typical item-based kNN (k Nearest Neighbor) CF approach

Research progress on the role and mechanism of ADAMTS9 in atherosclerosis

Atherosclerosis is an inflammatory disease of arterial stenosis caused by the imbalance of lipid metabolism and atherosclerotic plaques clustered on the arterial wall. It is the main pathological process of vascular diseases， such as stroke and coronary heart disease， etc. Atherosclerotic diseases yield high disability and death rates. Recent relevant studies have reported that ADAMTS9 is closely correlated with vascular pathophysiological processes. ADAMTS9 can degrade and assemble extracellular matrix， enhance vascular smooth muscle cell proliferation and migration， provoke pro-inflammatory response， promote intimal thickening， accelerate plaque rupture， and exert anti-angiogenesis effect. In this article， the role and mechanism of ADAMTS9 in the incidence and development of atherosclerosis were mainly summarized

Defending against the Advanced Persistent Threat: An Optimal Control Approach

The new cyberattack pattern of advanced persistent threat (APT) has posed a serious threat to modern society. This paper addresses the APT defense problem, that is, the problem of how to effectively defend against an APT campaign. Based on a novel APT attack-defense model, the effectiveness of an APT defense strategy is quantified. Thereby, the APT defense problem is modeled as an optimal control problem, in which an optimal control stands for a most effective APT defense strategy. The existence of an optimal control is proved, and an optimality system is derived. Consequently, an optimal control can be figured out by solving the optimality system. Some examples of the optimal control are given. Finally, the influence of some factors on the effectiveness of an optimal control is examined through computer experiments. These findings help organizations to work out policies of defending against APTs

A Hierarchical Dataflow-Driven Heterogeneous Architecture for Wireless Baseband Processing

Wireless baseband processing (WBP) is a key element of wireless communications, with a series of signal processing modules to improve data throughput and counter channel fading. Conventional hardware solutions, such as digital signal processors (DSPs) and more recently, graphic processing units (GPUs), provide various degrees of parallelism, yet they both fail to take into account the cyclical and consecutive character of WBP. Furthermore, the large amount of data in WBPs cannot be processed quickly in symmetric multiprocessors (SMPs) due to the unpredictability of memory latency. To address this issue, we propose a hierarchical dataflow-driven architecture to accelerate WBP. A pack-and-ship approach is presented under a non-uniform memory access (NUMA) architecture to allow the subordinate tiles to operate in a bundled access and execute manner. We also propose a multi-level dataflow model and the related scheduling scheme to manage and allocate the heterogeneous hardware resources. Experiment results demonstrate that our prototype achieves $2\times$ and $2.3\times$ speedup in terms of normalized throughput and single-tile clock cycles compared with GPU and DSP counterparts in several critical WBP benchmarks. Additionally, a link-level throughput of $288$ Mbps can be achieved with a $45$-core configuration.Comment: 7 pages, 7 figures, conferenc

RAP-SAM: Towards Real-Time All-Purpose Segment Anything

Advanced by transformer architecture, vision foundation models (VFMs) achieve remarkable progress in performance and generalization ability. Segment Anything Model (SAM) is one remarkable model that can achieve generalized segmentation. However, most VFMs cannot run in realtime, which makes it difficult to transfer them into several products. On the other hand, current real-time segmentation mainly has one purpose, such as semantic segmentation on the driving scene. We argue that diverse outputs are needed for real applications. Thus, this work explores a new real-time segmentation setting, named all-purpose segmentation in real-time, to transfer VFMs in real-time deployment. It contains three different tasks, including interactive segmentation, panoptic segmentation, and video segmentation. We aim to use one model to achieve the above tasks in real-time. We first benchmark several strong baselines. Then, we present Real-Time All Purpose SAM (RAP-SAM). It contains an efficient encoder and an efficient decoupled decoder to perform prompt-driven decoding. Moreover, we further explore different training strategies and tuning methods to boost co-training performance further. Our code and model are available at https://github.com/xushilin1/RAP-SAM/.Comment: Project Page: https://xushilin1.github.io/rap_sam

Ultrafast Hole Trapping and Relaxation Dynamics in p-Type CuS Nanodisks

CuS nanocrystals are potential materials for developing low-cost solar energy conversion devices. Understanding the underlying dynamics of photoinduced carriers in CuS nanocrystals is essential to improve their performance in these devices. In this work, we investigated the photoinduced hole dynamics in CuS nanodisks (NDs) using the combination of transient optical (OTA) and X-ray (XTA) absorption spectroscopy. OTA results show that the broad transient absorption in the visible region is attributed to the photoinduced hot and trapped holes. The hole trapping process occurs on a subpicosecond time scale, followed by carrier recombination (~100 ps). The nature of the hole trapping sites, revealed by XTA, is characteristic of S or organic ligands on the surface of CuS NDs. These results not only suggest the possibility to control the hole dynamics by tuning the surface chemistry of CuS but also represent the first time observation of hole dynamics in semiconductor nanocrystals using XTA