Channel Estimation and Information Symbol Detection for DS-UWB Communication Systems

The UWB channel estimation and multiuser detection problem are investigated. The information symbol and channel parameter are considered as unknown variables. The multiuser detector and UWB channel estimator are designed jointly. For symbol detection, the one-step predictor of channel parameter is used and the estimation error is treated as a multiplicative noise; then a Riccati equation and a Lyapunov equation will be needed. If the transmitted symbols are uncorrelated and identically distributed random variables with zero mean and unit variance, only a Riccati equation needs to be solved. For UWB channel estimation, the one-step predictor of information symbol is used and the estimation error is also considered as a multiplicative noise. The solutions to the above two problems are obtained by solving a couple of Riccati equations together with two Lyapunov equations

Deep Learning with S-shaped Rectified Linear Activation Units

Rectified linear activation units are important components for state-of-the-art deep convolutional networks. In this paper, we propose a novel S-shaped rectified linear activation unit (SReLU) to learn both convex and non-convex functions, imitating the multiple function forms given by the two fundamental laws, namely the Webner-Fechner law and the Stevens law, in psychophysics and neural sciences. Specifically, SReLU consists of three piecewise linear functions, which are formulated by four learnable parameters. The SReLU is learned jointly with the training of the whole deep network through back propagation. During the training phase, to initialize SReLU in different layers, we propose a "freezing" method to degenerate SReLU into a predefined leaky rectified linear unit in the initial several training epochs and then adaptively learn the good initial values. SReLU can be universally used in the existing deep networks with negligible additional parameters and computation cost. Experiments with two popular CNN architectures, Network in Network and GoogLeNet on scale-various benchmarks including CIFAR10, CIFAR100, MNIST and ImageNet demonstrate that SReLU achieves remarkable improvement compared to other activation functions.Comment: Accepted by AAAI-1

Concordane of OSTA and lumbar spine BMD by DXA in identifying risk of osteoporosis

OBJECTIVE: To investigate the accuracy of Osteoporosis Self-assessment Tool for Asians (OSTA) in identifying the risk of osteoporosis in postmenopausal women. To validate use of OSTA risk index by comparing it with the bone mineral density (BMD) of lumbar spine measured by dual energy X-ray absorptiometry (DXA). METHODS: The data of lumbar spine BMD (LS BMD) measurements by DXA of 218 postmenopausal women of Han nationality in Sichuan province were compared with OSTA risk index. The concordance of OSTA and LS BMD were calculated and analyzed by fourfold table and receiver operating characteristic (ROC) curve. RESULTS: The prevalence of osteoporosis in these women was 40.4% and 61.5%, with the LS BMD T score cutoffs -2.5 and -2.0, respectively. The sensitivity, specificity, and accuracy of OSTA risk index compared with T score cutoff -2.5 of LS BMD were 59.1%, 56.9% and 57.8%, respectively, while they were 57.5%, 63.1%, 59.6% by T score cutoff -2.0. CONCLUSION: For identifying risk of osteoporosis, the concurrence was lower than those reported studies when comparing LS BMD measurements to OSTA risk index in Chinese Han nationality postmenopausal women of Sichuan province. Physicians should identify women who need BMD measurement according to more factors rather than age and body weight

A New Real-Time Ocean Observing Station on Ship Shoal on Louisiana Shelf

One of the major challenges that we are facing in the northern Gulf of Mexico coastal area is the need of a better and reliable offshore met-ocean real time data collection system that supports the mission of Bureau of Ocean Energy Management (BOEM) and other federal and local agencies for coastal management, protection, and restoration, especially along the Louisiana coast. This area has a suite of environmental problems that require the acquisition of real time data for immediate assessment or model-based assessment and predictions that rely on this kind of data. One such system providing this kind of data is managed by the Wave-Current-Surge Information System at LSU

A New Real-Time Ocean Observing Station on Ship Shoal on Louisiana Shelf

One of the major challenges that we are facing in the northern Gulf of Mexico coastal area is the need of a better and reliable offshore met-ocean real time data collection system that supports the mission of Bureau of Ocean Energy Management (BOEM) and other federal and local agencies for coastal management, protection, and restoration, especially along the Louisiana coast. This area has a suite of environmental problems that require the acquisition of real time data for immediate assessment or model-based assessment and predictions that rely on this kind of data. One such system providing this kind of data is managed by the Wave-Current-Surge Information System at LSU

Planar Graphs with Homomorphisms to the 9-cycle

We study the problem of finding homomorphisms into odd cycles from planar graphs with high odd-girth. The Jaeger-Zhang conjecture states that every planar graph of odd-girth at least $4k+1$ admits a homomorphism to the odd cycle $C_{2k+1}$. The $k=1$ case is the well-known Gr\"otzsch's $3$-coloring theorem. For general $k$, in 2013 Lov\'asz, Thomassen, Wu, and Zhang showed that it suffices to have odd-girth at least $6k+1$. Improvements are known for $C_5$ and $C_7$ in [Combinatorica 2017, SIDMA 2020, Combinatorica 2022]. For $C_9$ we improve this hypothesis by showing that it suffices to have odd-girth 23. Our main tool is a variation on the potential method applied to modular orientations. This allows more flexibility when seeking reducible configurations. The same techniques also prove some results on circular coloring of signed planar graphs.Comment: 24 pages, 4 figure

Studies on the expression and biological functions of ZIC5 in hepatocellular carcinoma

Purpose: To study the expression of zinc finger protein of the cerebellum 5 (ZIC5) and its biological functions in hepatocellular carcinoma (HCC). Methods: Sixty-five patients undergoing HCC surgery were selected. Expression of ZIC5 in HCC and para-carcinoma tissue was examined by quantitative real time-polymerase chain reaction (qRT-PCR) and western blotting. The relationship between ZIC5 expression and clinicopathological features, postoperative survival rate, and prognosis of liver cancer patients was analyzed by t-test, Kaplan-Meier method, and Cox regression analysis, respectively. The effects of ZIC5 silencing on Huh-7 cell proliferation, migration, invasion, and apoptosis were assessed using Cell Counting Kit-8 (CCK-8), wound healing assay, Transwell assay, and flow cytometry, respectively. Results: ZIC5 expression in liver cancer tissue was significantly higher than in the para-carcinoma tissue and was significantly correlated with TNM stage and differentiation degree (p < 0.001). The overall survival rate of patients with high ZIC5 expression level was significantly lower than that of patients with low ZIC5 expression (p < 0.01). ZIC5 expression, TNM stage, and differentiation degree were independent prognostic factors. ZIC5 silencing significantly inhibited the proliferative, migratory, invasive, and anti-apoptotic capacity of Huh-7 cells (p < 0.01). Conclusion: ZIC5 is highly expressed in HCC, and this can promote liver cancer cell proliferation, migration, and invasion

Flexible and Robust Counterfactual Explanations with Minimal Satisfiable Perturbations

Counterfactual explanations (CFEs) exemplify how to minimally modify a feature vector to achieve a different prediction for an instance. CFEs can enhance informational fairness and trustworthiness, and provide suggestions for users who receive adverse predictions. However, recent research has shown that multiple CFEs can be offered for the same instance or instances with slight differences. Multiple CFEs provide flexible choices and cover diverse desiderata for user selection. However, individual fairness and model reliability will be damaged if unstable CFEs with different costs are returned. Existing methods fail to exploit flexibility and address the concerns of non-robustness simultaneously. To address these issues, we propose a conceptually simple yet effective solution named Counterfactual Explanations with Minimal Satisfiable Perturbations (CEMSP). Specifically, CEMSP constrains changing values of abnormal features with the help of their semantically meaningful normal ranges. For efficiency, we model the problem as a Boolean satisfiability problem to modify as few features as possible. Additionally, CEMSP is a general framework and can easily accommodate more practical requirements, e.g., casualty and actionability. Compared to existing methods, we conduct comprehensive experiments on both synthetic and real-world datasets to demonstrate that our method provides more robust explanations while preserving flexibility.Comment: Accepted by CIKM 202