An Application of Bayesian Network in Cognitive Behavioral Therapy

Mental health has received increased focus in recent years, with a larger emphasis on treatment and acceptance. However, evidence-based psychological interventions are of poor availability and have room for improvement. The amount of data being gathered across applications and practices provide opportunities for deeper analysis through machine learning based technologies. By applying Bayesian networks (BNs) in a cognitive behavioral therapy for adults with ADHD, this research analyzes historic self-report data to predict the behavior of future participants at an early stage of the online intervention. Bayesian networks represent probabilistic models that describe the joint probability distribution through an acyclic graph. The contribution of this thesis is an artifact with the purpose of serving as a decision making support tool. Methods of Design Science Research was applied to achieve this, in a development cycle with three main iterations. Using Bayesian networks for analyzing behavioral patterns yield positive results with its predictive capabilities when dealing with uncertainty. Domain experts from the internet-delivered intervention provided useful feedback and insight that contributed to the novelty and research scope of this thesis. Future work should update the model when a larger population sample is available, and focus on implementing the artifact in a more user-centered desktop application.Masteroppgave i informasjonsvitenskapINFO390MASV-INF

ArraYnger: New Interface for Interactive 360° Spatialization

Interactive real-time spatialization of audio over large immersive speaker arrays poses significant interface and control challenges for live performers. Fluidly moving and mixing numerous sound objects over unique speaker configurations requires specifically designed software interfaces and systems. Currently available software solutions either impose configuration limitations, require extreme degrees of expertise, or extensive configuration time to use. A new system design, focusing on simplicity, ease of use, and live interactive spatialization is described. Automation of array calibration and tuning is included to facilitate rapid deployment and configuration. Comparisons with other solutions show favorability in terms of complexity, depth of control, and required features

Two- and three-piece implants to boost data generation in preclinical in vivo research-A short technical report.

The purpose of this technical report is to present two novel experimental implant designs to boost data generation in preclinical in vivo research. Specifically, the report describes the rationale and the components of (1) a two-piece experimental implant suitable for a small animal platform (e.g., the rabbit femur/tibial epiphysis model), consisting of a threaded apical- and a coronal cylindrical piece, which is intended for collecting two types of biomechanical data, and (2) a three-piece experimental implant suitable for a large animal platform (e.g., the mini-pig mandible model), consisting of an apical "wound chamber", which allows the collection of histological/histomorphometrical data, and a middle threaded and coronal cylindrical piece, which also allow the collection of two types of biomechanical data. The increased volume of information generated from a single experiment in a small animal platform, using the proposed two-piece implant design, may assist in a more qualified decision-making process, on whether it is relevant to proceed to further assessment using a large animal platform. Furthermore, the increased volume of information generated in a single animal experiment either in a small or large animal platform, using the proposed two- and three-piece implants, respectively, likely decreases the number of animals otherwise needed for collecting the same information with standard one-piece implants and, thus, contributes to the reduction/refinement elements of the 3R principle

Predictive Control of Demand Side Units Participating in the Primary Frequency Reserve Market

Abstract—We consider an aggregator controlling a mixed portfolio of conventional power generators and demand side units. The generators are controllable within certain power and ramp limitations while the demand side units are characterized by flexible consumptions and therefore can be treated as energy storages of limited capacity. We address the problem of reducing the load on the conventional generators by letting the flexible consumers participate in the provision of primary frequency reserve. In particular, it is desired that the flexible consumers compensate for rapid grid frequency changes. In this work, we design an aggregator control strategy based on closed-loop model predictive control. The controller is able to mobilize the flexible consumers ahead of time such that we are able to reduce the load on the conventional generators by more extensive use of the demand side units. I