助视器对年龄相关性黄斑变性患者视功能恢复和阅读速度的影响

目的:评估助视器对年龄相关性黄斑变性(AMD)患者视功能恢复和阅读速度的影响。方法:对低视力门诊44名AMD患者进行评估。收集并分析使用助视器前和使用助视器时裸眼视力、最佳矫正视力、屈光状态、助视器类型(LVAs)以及阅读速度的相关数据。结果:共44例AMD患者,平均年龄为73±10.8岁,男性36例(82%)。其中,29例(67%)受试者视力较好的眼远视力(DVA)为1.0~1.6 LogMAR,而36例(82%)受试者近视力(NVA)小于3.2 m。使用助视器时平均DVA提高0.67±0.27 LogMAR(P=0.000)。使用LVAs时,42例患者NVA达到1 m甚至更佳,仅有2例(4.5%)没有使用LVAs的患者NVA为1 m。在使用一定时间的助视器后,有阅读能力的患者平均阅读速度从每分钟2.9±4.78字提高到每分钟71.31±29.96字(P<0.001)。15名受试者远距离视觉使用单目望远镜,而戴高倍单目镜片眼镜作为最常用的阅读辅助工具。结论:LVAs对AMD患者的视功能恢复和阅读能力的提高有一定的作用。对于AMD患者而言,接受低视力护理服务是有必要的。     

A novel audio forensic data-set for digital multimedia forensics

Today, digital multimedia (audio, video, images) is a common evidential source in litigation and criminal justice proceedings, and, not surprisingly, multimedia forensics is an active research area. One particular challenge faced by multimedia forensic researchers is the lack of a comprehensive and publicly available data-set for evaluating existing and new algorithms. This paper presents a digital audio forensic data-set, designed to facilitate evaluation of audio forensic algorithms (e.g. microphone identification, acoustic environment identification and splice detection). This paper also briefly describes the data-collection settings, microphones, speakers, languages and notations used. Existing tamper-detection techniques rely on artefacts due to recording devices, codec and/or the acoustic environment in the audio in question. Experimental results show that the selected approaches achieved promising results.     

Type A Behavior and Job Performance: Some Suggestive Findings

Abstract

This study examined Type A and Type B differences in job performance, psychosomatic complaints, and career progression among white-collar employees (N = 218) in a field setting. Significant differences were found between Type A's and Type B's in quality of performance, effort exerted at the job, and psychosomatic complaints. Employees' cultural background and sex moderated some of the relationships observed in the study. Implications of the findings for future research on the topic are discussed.     

Performance Evaluation of Time-Frequency Distributions for ECG Signal Analysis

The non-stationary and multi-frequency nature of biomedical signal activities makes the use of time-frequency distributions (TFDs) for analysis inevitable. Time-frequency analysis provides simultaneous interpretations in both time and frequency domain enabling comprehensive explanation, presentation and interpretation of electrocardiogram (ECG) signals. The diversity of TFDs and specific properties for each type show the need to determine the best TFD for ECG analysis. In this study, a performance evaluation of five TFDs in term of ECG abnormality detection is presented. The detection criteria based on extracted features from most important ECG signal components (QRS) to detect normal and abnormal cases. This is achieved by estimating its energy concentration magnitude using the TFDs. The TFDs analyse ECG signals in one-minute interval instead of conventional time domain approach that analyses based on beat or frame containing several beats. The MIT-BIH normal sinus rhythm ECG database total records of 18 long-term ECG sampled at 128 Hz have been analysed. The tested TFDs include Dual-Tree Wavelet Transform, Spectrogram, Pseudo Wigner-Ville, Choi-Williams, and Born-Jordan. Each record is divided into one-minute slots, which is not considered previously, and analysed. The sample periods (slots) are randomly selected ten minutes interval for each record. This result with 99.44% detection accuracy for 15,735 ECG beats shows that Choi-Williams distribution is most reliable to be used for heart problem detection especially in automated systems that provide continuous monitoring for long time duration.