Modeling knowledge states in language learning

Artificial intelligence (AI) is being increasingly applied in the field of intelligent tutoring systems (ITS). Knowledge space theory (KST) aims to model the main features of the process of learning new skills. Two basic components of ITS are the domain model and the student model. The student model provides an estimation of the state of the student’s knowledge or proficiency, based on the student’s performance on exercises. The domain model provides a model of relations between the concepts/skills in the domain. To learn the student model from data, some ITSs use the Bayesian Knowledge Tracing (BKT) algorithm, which is based on hidden Markov models (HMM). This thesis investigates the applicability of KST to constructing these models. The contribution of the thesis is twofold. Firstly, we learn the student model by a modified BKT algorithm, which models forgetting of skills (which the standard BKT model does not do). We build one BKT model for each concept. However, rather than treating a single question as a step in the HMM, we treat an entire practice session as one step, on which the student receives a score between 0 and 1, which we assume to be normally distributed. Secondly, we propose algorithms to learn the “surmise” graph—the prerequisite relation between concepts—from “mastery data,” estimated by the student model. The mastery data tells us the knowledge state of a student on a given concept. The learned graph is a representation of the knowledge domain. We use the student model to track the advancement of students, and use the domain model to propose the optimal study plan for students based on their current proficiency and targets of study

A long-range contact process in a random environment

We study survival and extinction of a long-range infection process on a diluted one-dimensional lattice in discrete time. The infection can spread to distant vertices according to a Pareto distribution, however spreading is also prohibited at random times. We prove a phase transition in the recovery parameter via block arguments. This contributes to a line of research on directed percolation with long-range correlations in nonstabilizing random environments

Curie Temperature of Diluted Magnetic Semiconductors: the Influence of the Antiferromagnetic Exchange Interaction

The coherent potential approximation and mean field approximation are used to calculate the free energy of the coupled carrier – localized spin system in III-V diluted magnetic semiconductors. Thus the magnetic transition temperature Tc can be determined and its dependence on important model parameters. We show that the strong antiferromagnetic superexchange interaction between nearest neighbour sites considerably reduces the Curie temperature

Building Footprint Extraction in Dense Areas using Super Resolution and Frame Field Learning

Despite notable results on standard aerial datasets, current state-of-the-arts fail to produce accurate building footprints in dense areas due to challenging properties posed by these areas and limited data availability. In this paper, we propose a framework to address such issues in polygonal building extraction. First, super resolution is employed to enhance the spatial resolution of aerial image, allowing for finer details to be captured. This enhanced imagery serves as input to a multitask learning module, which consists of a segmentation head and a frame field learning head to effectively handle the irregular building structures. Our model is supervised by adaptive loss weighting, enabling extraction of sharp edges and fine-grained polygons which is difficult due to overlapping buildings and low data quality. Extensive experiments on a slum area in India that mimics a dense area demonstrate that our proposed approach significantly outperforms the current state-of-the-art methods by a large margin.Comment: Accepted at The 12th International Conference on Awareness Science and Technolog

Performance analysis for three cases of outage probability in one-way DF full-duplex relaying network with presence of direct link

In this paper, the one-way decode-and-forward (DF) full-duplex relaying network system with presence of direct link is investigated. In the analysis section, we derived the exact, lower, and upper bound for outage probability (OP) with maximal ratio combining (MRC) at the receiver. Furthermore, the system performance's analytical expressions are verified by using the Monte Carlo simulation. In addition, we investigated the effect of the main parameters on the OP of the proposed system. Finally, we can sate that the simulation curves overlap the analytical curves to convince the analysis section. This research can provide a novel recommendation for the communication network

Lower and upper bound form of outage probability in one-way AF full-duplex relaying network under impact of direct link

This paper proposed and investigated the one-way amplify-and-forward (AF) full-duplex relaying network under impact of direct link. For the system performance analysis, the exact and lower and upper bound form of the system outage probability (OP) are investigated and derived. In this system model, authors assume that the E uses the MRC (maximal ratio combining) technique. Finally, we can see that the analytical and the simulation values overlap to verify the analytical section using the Monte Carlo simulation. Also, we investigate the influence of the system primary parameters on the proposed system OP

Nonlinear post-buckling of thin FGM annular spherical shells under mechanical loads and resting on elastic foundations

This paper presents an analytical approach to investigate the nonlinear buckling and post-buckling of thin annular spherical shells made of functionally graded materials (FGM) and subjected to mechanical load and resting on Winkler-Pasternak type elastic foundations. Material properties are graded in the thickness direction according to a simple power law distribution in terms of the volume fractions of constituents. Equilibrium and compatibility equations for annular spherical shells are derived by using the classical thin shell theory in terms of the shell deflection and the stress function. Approximate analytical solutions are assumed to satisfy simply supported boundary conditions and Galerkin method is applied to obtain closed-form of load-deflection paths. An analysis is carried out to show the effects of material and geometrical properties and combination of loads on the stability of the annular spherical shells