An unsupervised acoustic fall detection system using source separation for sound interference suppression

We present a novel unsupervised fall detection system that employs the collected acoustic signals (footstep sound signals) from an elderly person׳s normal activities to construct a data description model to distinguish falls from non-falls. The measured acoustic signals are initially processed with a source separation (SS) technique to remove the possible interferences from other background sound sources. Mel-frequency cepstral coefficient (MFCC) features are next extracted from the processed signals and used to construct a data description model based on a one class support vector machine (OCSVM) method, which is finally applied to distinguish fall from non-fall sounds. Experiments on a recorded dataset confirm that our proposed fall detection system can achieve better performance, especially with high level of interference from other sound sources, as compared with existing single microphone based methods

Word Searching in Scene Image and Video Frame in Multi-Script Scenario using Dynamic Shape Coding

Retrieval of text information from natural scene images and video frames is a challenging task due to its inherent problems like complex character shapes, low resolution, background noise, etc. Available OCR systems often fail to retrieve such information in scene/video frames. Keyword spotting, an alternative way to retrieve information, performs efficient text searching in such scenarios. However, current word spotting techniques in scene/video images are script-specific and they are mainly developed for Latin script. This paper presents a novel word spotting framework using dynamic shape coding for text retrieval in natural scene image and video frames. The framework is designed to search query keyword from multiple scripts with the help of on-the-fly script-wise keyword generation for the corresponding script. We have used a two-stage word spotting approach using Hidden Markov Model (HMM) to detect the translated keyword in a given text line by identifying the script of the line. A novel unsupervised dynamic shape coding based scheme has been used to group similar shape characters to avoid confusion and to improve text alignment. Next, the hypotheses locations are verified to improve retrieval performance. To evaluate the proposed system for searching keyword from natural scene image and video frames, we have considered two popular Indic scripts such as Bangla (Bengali) and Devanagari along with English. Inspired by the zone-wise recognition approach in Indic scripts[1], zone-wise text information has been used to improve the traditional word spotting performance in Indic scripts. For our experiment, a dataset consisting of images of different scenes and video frames of English, Bangla and Devanagari scripts were considered. The results obtained showed the effectiveness of our proposed word spotting approach.Comment: Multimedia Tools and Applications, Springe

MODELING EXCHANGE RATE VOLATILITIES IN CROATIA

Modeling and forecasting exchange rate volatility has important implications in a range of areas in macroeconomics and finance. A number of models have been developed in empirical finance literature to investigate this volatility across different regions and countries. Well known and frequently applied models to estimate exchange rate volatility are the autoregressive conditional heteroscedastic (ARCH) model advanced by Engle (1982) and the generalized (GARCH) model developed independently by Bollerslev (1986) and Taylor (1986). This paper examines the performance of several ARCH models for the EUR and USD against the HRK on daily data sets within the time period from 1997 to 2015. Evaluating the models through standard information criteria showed that the GARCH (2,1) is the best fitted model  for the EUR/HRK and the GARCH (1,1) for the USD/HRK daily return volatility. In accordance to the estimated models there is no empirical evidence that negative and positive shocks imply a different next period volatility of the daily EUR/HRK as well as the USD/HRK exchange rate return.</p

Metallic Nanocages: Synthesis of Bimetallic Pt–Pd Hollow Nanoparticles with Dendritic Shells by Selective Chemical Etching

We report a facile synthesis of Pt–Pd bimetallic nanoparticles, named “metallic nanocages”, with a hollow interior and porous dendritic shell. This synthesis is easily achieved by selective chemical etching of Pd cores from dendritic Pt-on-Pd nanoparticles. The obtained Pt–Pd nanocages show superior catalytic activity for methanol oxidation reaction compared to other Pt-based materials reported previously

MOESM1 of 3C-digital PCR for quantification of chromatin interactions

Additional file 1: Table S1. Table of sequences of the primers and TaqMan probes used for dPCR

<b>The Ultimate Controlling Shareholder’s Motivation for Equity Pledge in China</b>

This paper empirically investigates the motivations of ultimate controlling shareholders’ equity pledges in the Chinese A-share market from two perspectives, financing constraints and interest encroachment, with a panel data regression model.</p

Uniformly Semiparametric Efficient Estimation of Treatment Effects With a Continuous Treatment

<p>This article studies identification, estimation, and inference of general unconditional treatment effects models with continuous treatment under the ignorability assumption. We show identification of the parameters of interest, the dose–response functions, under the assumption that selection to treatment is based on observables. We propose a semiparametric two-step estimator, and consider estimation of the dose–response functions through moment restriction models with generalized residual functions that are possibly nonsmooth. This general formulation includes average and quantile treatment effects as special cases. The asymptotic properties of the estimator are derived, namely, uniform consistency, weak convergence, and semiparametric efficiency. We also develop statistical inference procedures and establish the validity of a bootstrap approach to implement these methods in practice. Monte Carlo simulations show that the proposed methods have good finite sample properties. Finally, we apply the proposed methods to estimate the unconditional average and quantile effects of mothers’ weight gain and age on birthweight. Supplementary materials for this article are available online.</p

Photocatalyzed Facile Synthesis of α‑Chloro Aryl Ketones with Polyaniline–g‑C₃N₄–TiO₂ Composite under Visible Light

PANI (polyaniline)–g-C₃N₄–TiO₂ composite was prepared and utilized in the photocatalyzed synthesis of α-chloro aryl ketones via a radical-triggered domino process under oxygen atmosphere. This semiconductor photocatalyst showed good photocatalytic performance and chemoselectivity under visible light irradiation. A variety of aryl diazonium salts and aryl alkynes survived the reaction conditions well to afford the corresponding products in moderate to good yields. Scale-up (10 mmol) synthesis was also achieved. The recycle studies showed that the semiconductor composite could be readily recovered and reused for eight consecutive runs with a slight decrease in the catalytic activity. Control experiments were also performed, and a plausible catalytic mode was proposed

Additional file 3 of Targeting Bruton’s tyrosine kinase in vitreoretinal lymphoma: an open-label, prospective, single-center, phase 2 study

Additional file 3. Additional methods

Additional file 1 of Targeting Bruton’s tyrosine kinase in vitreoretinal lymphoma: an open-label, prospective, single-center, phase 2 study

Additional file 1: Table S1. Characteristics of patients with PVRL and PCNSL with vitreoretinal involvement