This study examined differences between more and less effective trainee psychotherapists. Therapists were assigned to one of two groups depending on whether the preponderance of their patients' changes in symptomatology indicated more or less improvement over the course of therapy. Therapist variables included emotional adjustment, relationship skills, eliciting patient involvement, credibility, directiveness, and theoretical orientation. Less effective therapists were revealed to have lower levels of empathic understanding, to rate their patients as more involved in treatment, and to rate themselves as more supportive than the more effective therapists. Less effective therapists also valued comfort and stimulation significantly more and valued intellectual goals significantly less than did more effective therapists.

Steganographic and watermarking information inserted into a color image file, regardless of embedding algorithm, causes disturbances in the relationships between neighboring pixels. A method for steganalysis utilizing the local binary pattern (LBP) texture operator to examine the pixel texture patterns within neighborhoods across the color planes is presented. Providing the outputs of this simple algorithm to an artificial neural net capable of supervised learning results in the creation of a surprisingly reliable predictor of steganographic content, even with relatively small amounts of embedded data. Other tools for identifying images with steganographic content have been developed by forming a neural network input vector comprised of image statistics that respond to particular side effects of specific embedding algorithms. The neural net in our experiment is trained with general texture related statistics from clean images and images modified using only one embedding algorithm, and is able to correctly discriminate clean images from images altered by data embedded by one of various different watermarking and steganographic algorithms. Algorithms tested include various steganographic and watermarking programs and include spatial and transform domain image hiding techniques. The interesting result is that clean color images can be reliably distinguished from steganographically altered images based on texture alone, regardless of the embedding algorithm.

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