Author profiling is the task to infer some information about an author by analyzing her/his writing style. It’s application in forensics, business intelligence and psychology makes this topic interesting for researching. In this notebook, we present our baseline approach using SVM and Linear Discriminant Analysis (LDA) classifiers. We analyze features obtained from LIWC dictionaries, these are ...

Biogenic amines (BAs) were presented as significant markers for the evaluation of spoilage meat and products. In this work, a colorimetric sensor array was developed discrimination detection spermine (SP), spermidine (SD), histamine (HS), tryptamine (TP) important BAs in food assessment. For aim, two spherical plasmonic nanoparticles, namely gold nanoparticles (AuNPs) silver (AgNPs), utilized s...

OBJECTIVE To investigate the relationship between microRNA107 (miRNA107) and BACE1 messenger RNA (mRNA) gene expressions in plasma and their diagnostic capability to distinguish subjects with amnestic mild cognitive impairment from healthy controls. METHOD We recruited 97 patients with Alzheimer's disease according to diagnostic criteria of DSM-IV and National Institute of Neurologic and Comm...

Conventional electroencephalography (EEG) and magnetoencephalography (MEG) analysis often rely on averaging over multiple trials to extract statistically relevant differences between two or more experimental conditions. We demonstrate that by linearly integrating information over multiple spatially distributed sensors within a predefined time window, one can discriminate conditions on a trial-b...

Classification is a process which plays a vital role in the analysis of the gene expression data set. The paper focuses on variety of learning algorithms which are really challenging in nature. The proposed model has been implemented and evaluated by using 5 benchmark datasets and to evaluate the performance and throughput of the model, various learning algorithms has been used like Random Fore...

In adverse conditions, the speech recognition performance decreases in part due to imperfect speech/non-speech detection. In this paper, a new combination of voicing parameter and energy for speech/non-speech detection is described. This combination avoids especially the noise detections in real life very noisy environments and provides better performance for continuous speech recognition. This...

In this paper, we present an acoustic-phonetic approach to automatic pronunciation error detection. Classifiers using techniques such as Linear Discriminant Analysis or a decision tree were developed for three sounds that are frequently pronounced incorrectly by L2-learners of Dutch: /A/, /Y/ and /x/. The acoustic properties of these pronunciation errors were examined so as to define a number o...