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.     

Ellagic acid attenuates oxidative stress on brain and sciatic nerve and improves histopathology of brain in streptozotocin-induced diabetic rats

The aim of this study was to investigate the possible effects of ellagic acid in brain and sciatic nerve tissues of diabetic rats. Also, the impact of ellagic acid on catalase and paraoxonase (PON-1) activities, total antioxidant status (TAS), total oxidant status (TOS), oxidative stress index (OSI), malondialdehyde (MDA) and nitric oxide (NO) were examined. The rats were randomly divided into four groups, with eight rats each: Normal controls (not diabetic), only ellagic acid treated (ellagic acid controls, not diabetic), Diabetic controls (streptozotocin, diabetic), ellagic acid-treated diabetic (streptozotocin?+?ellagic acid). After a 4?week experiment, rats were sacrificed, and biomarkers for oxidative stress in the brain and sciatic nerve tissues of the rats were measured. There was significant depletion in the PON-1, catalase, and TAS levels in the brain and sciatic nerve tissues compared to the control groups (for both parameters, p?<?0.05). The values of catalase, PON-1 and TAS reversed back to normal levels in ellagic acid-treated diabetic rats compared to untreated diabetic rats (for both parameters, p?<?0.05). The levels of MDA, TOS, NO and, OSI in the brain and sciatic nerve tissues were higher in untreated diabetic rats compared to control group (for both parameters p?<?0.05). However, MDA, TOS, OSI, and NO levels were found to be significantly reduced in the ellagic acid-treated diabetic group compared to the untreated diabetic group in these tissues (for both parameters, p?<?0.05). In conclusion, the results of the present study suggested that ellagic acid exhibits neuroprotective effects against oxidative damage in diabetic rats.