Brief Analysis on the Construction Site Safety Management Situation and Countermeasure

The construction industry is a high-risk, the industry frequent accidents, and in the production process, there are many uncontrollable influence factors. In recent years， the safety management in the construction industry is gradually maturing and perfect， but the construction field casualties multiple situations has not fundamentally reversed, this article focuses on the causes and countermeasures of construction casualties explore

“Does the tail wag the dog? The effect of credit default swaps on credit risk”

Credit default swaps (CDS) are derivative contracts that are widely used as tools for credit risk management. However, in recent years, concerns have been raised about whether CDS trading itself affects the credit risk of the reference entities. We use a unique, comprehensive sample covering CDS trading of 901 North American corporate issuers, between June 1997 and April 2009, to address this question. We find that the probability of both a credit rating downgrade and bankruptcy increase, with large economic magnitudes, after the inception of CDS trading. This finding is robust to controlling for the endogeneity of CDS trading. Beyond the CDS introduction effect, we show that firms with relatively larger amounts of CDS contracts outstanding, and those with relatively more “no restructuring” contracts than other types of CDS contracts covering restructuring, are more adversely affected by CDS trading. Moreover, the number of creditors increases after CDS trading begins, exacerbating creditor coordination failure for the resolution of financial distress

Linearly Supporting Feature Extraction For Automated Estimation Of Stellar Atmospheric Parameters

We describe a scheme to extract linearly supporting (LSU) features from stellar spectra to automatically estimate the atmospheric parameters $T_{eff}$, log$~g$, and [Fe/H]. "Linearly supporting" means that the atmospheric parameters can be accurately estimated from the extracted features through a linear model. The successive steps of the process are as follow: first, decompose the spectrum using a wavelet packet (WP) and represent it by the derived decomposition coefficients; second, detect representative spectral features from the decomposition coefficients using the proposed method Least Absolute Shrinkage and Selection Operator (LARS)$_{bs}$; third, estimate the atmospheric parameters $T_{eff}$, log$~g$, and [Fe/H] from the detected features using a linear regression method. One prominent characteristic of this scheme is its ability to evaluate quantitatively the contribution of each detected feature to the atmospheric parameter estimate and also to trace back the physical significance of that feature. This work also shows that the usefulness of a component depends on both wavelength and frequency. The proposed scheme has been evaluated on both real spectra from the Sloan Digital Sky Survey (SDSS)/SEGUE and synthetic spectra calculated from Kurucz's NEWODF models. On real spectra, we extracted 23 features to estimate $T_{eff}$, 62 features for log$~g$, and 68 features for [Fe/H]. Test consistencies between our estimates and those provided by the Spectroscopic Sarameter Pipeline of SDSS show that the mean absolute errors (MAEs) are 0.0062 dex for log$~T_{eff}$ (83 K for $T_{eff}$), 0.2345 dex for log$~g$, and 0.1564 dex for [Fe/H]. For the synthetic spectra, the MAE test accuracies are 0.0022 dex for log$~T_{eff}$ (32 K for $T_{eff}$), 0.0337 dex for log$~g$, and 0.0268 dex for [Fe/H].Comment: 21 pages, 7 figures, 8 tables, The Astrophysical Journal Supplement Series (accepted for publication

A Synergetic Pattern Matching Method Based-on DHT Structure for Intrusion Detection in Large-scale Network

AbstractResearch in network security, with the attacks becoming more frequent, increasing complexity means, for the large-scale network intrusion detection, this paper presents a warning by analyzing the behavior of the log, the contents of the relevant association, through the DHT(Distributed Hash Table) distributed architecture, the Collabarative matching, fusion, and ultimately determine the method of attack paths. First, by improving the classical Apriori algorithm, greatly improving the efficiency of the association. At the same time, through the behavior pattern matching algorithms to extract information about the behavior of the alert and the behavior sequence elements to match the template, and through the right path to finally determine the value of the threat of the network path. After the design of a DHT network, the distributed collaborative match the path used to find complex network attacks. Finally, the overall algorithm flow, proposed a complete threat detection system architecture

Polymer based tunneling sensor

A process for fabricating a polymer based circuit by the following steps. A mold of a design is formed through a lithography process. The design is transferred to a polymer substrate through a hot embossing process. A metal layer is then deposited over at least part of said design and at least one electrical lead is connected to said metal layer

Automatic emotion perception using eye movement information for E-Healthcare systems.

Facing the adolescents and detecting their emotional state is vital for promoting rehabilitation therapy within an E-Healthcare system. Focusing on a novel approach for a sensor-based E-Healthcare system, we propose an eye movement information-based emotion perception algorithm by collecting and analyzing electrooculography (EOG) signals and eye movement video synchronously. Specifically, we extract the time-frequency eye movement features by firstly applying the short-time Fourier transform (STFT) to raw multi-channel EOG signals. Subsequently, in order to integrate time domain eye movement features (i.e., saccade duration, fixation duration, and pupil diameter), we investigate two feature fusion strategies: feature level fusion (FLF) and decision level fusion (DLF). Recognition experiments have been also performed according to three emotional states: positive, neutral, and negative. The average accuracies are 88.64% (the FLF method) and 88.35% (the DLF with maximal rule method), respectively. Experimental results reveal that eye movement information can effectively reflect the emotional state of the adolescences, which provides a promising tool to improve the performance of the E-Healthcare system.Anhui Provincial Natural Science Research Project of Colleges and Universities Fund under Grant KJ2018A0008, Open Fund for Discipline Construction under Grant Institute of Physical Science and Information Technology in Anhui University, and National Natural Science Fund of China under Grant 61401002