This review covers the core concepts and design decisions of TensorFlow. TensorFlow, originally created by researchers at Google, is the most popular one among the plethora of deep learning libraries. In the field of deep learning, neural networks have achieved tremendous success and gained wide popularity in various areas. This family of models…

Tensor calculus is critical in the study of the vector calculus of the surface of a body. Indeed, tensor calculus is a natural step-up for vector calculus. This paper presents some pitfalls of a traditional course in vector calculus in transitioning to tensor calculus. We show how a deeper emphasis on traditional topics such as the Jacobian can…

One of the essential problems, in educational data mining, is to predict students' performance on future learning materials, such as problems, assignments, and quizzes. Pioneer algorithms for predicting student performance mostly rely on two sources of information: students' past performance, and learning materials' domain knowledge model. The…

We propose a novel tensor factorization approach, Feedback-Driven Tensor Factorization (FDTF), for modeling student learning process and predicting student performance. This approach decomposes a tensor that is built upon students' attempt sequence, while considering the quizzes students select to work with as its feedback. FDTF does not require…

Brain connectivity of individuals with autism spectrum disorders (ASD) is heterogenous, as are the behavioral manifestations. The current study investigated brain-behavior relationships in the context of social skills and executive function profiles with data from the Autism Brain Imaging Database Exchange II. We calculated connectivity measures…

The structure tensor for vector valued images is most often defined as the average of the scalar structure tensors in each band. The problem with this definition is the assumption that all bands provide the same amount of edge information giving them the same weights. As a result non-edge pixels can be reinforced and edges can be weakened…

Purpose: The goal of this study is to validate the muscle architecture derived from both ex vivo and in vivo diffusion-weighted magnetic resonance imaging (dMRI) of the human tongue with histology of an ex vivo tongue. Method: dMRI was acquired with a 200-direction high angular resolution diffusion imaging (HARDI) diffusion scheme for both a…

The chiropractic clinical competency examination uses groups of items that are integrated by a common case vignette. The nature of the vignette items violates the assumption of local independence for items nested within a vignette. This study examines via simulation a new algorithmic approach for addressing the local independence violation problem…

Purpose: Muscle groups within the tongue in healthy and diseased populations show different behaviors during speech. Visualizing and quantifying strain patterns of these muscle groups during tongue motion can provide insights into tongue motor control and adaptive behaviors of a patient. Method: We present a pipeline to estimate the strain along…

We employed functional magnetic resonance imaging (fMRI) and diffuse tensor imaging (DTI) to study neural implications of silent reading of words in mutually comprehensible but visually and orthographically distinct languages for example Hindi and Urdu by independent groups of skilled readers. The fMRI results (conjunction analyses) showed the…

The development of internet and mobile technologies is driving an earthshaking social media revolution. They bring the internet world a huge amount of social media content, such as images, videos, comments, etc. Those massive media content and complicate social structures require the analytic expertise to transform those flood of information into…

Mirror neuron system (MNS) dysfunctions might underlie deficits in autism spectrum disorders (ASD). Diffusion tensor imaging based probabilistic tractography was conducted in 15 adult ASD patients and 13 matched, healthy controls. Fractional anisotropy (FA) was quantified to assess group differences in tract-related white matter microstructure of…

Students acquire knowledge as they interact with a variety of learning materials, such as video lectures, problems, and discussions. Modeling student knowledge at each point during their learning period and understanding the contribution of each learning material to student knowledge are essential for detecting students' knowledge gaps and…

Purpose: To better understand hypernasality (HN), we explored the relations between velopharyngeal orifice, auditory perception of HN, and acoustic-spectral measures in an in vivo within-subject design: (1) with a normally functioning velum as the control condition; and (2) with a temporarily paralyzed velum as the experimental condition. Method:…

We demonstrate that the key components of cognitive architectures (declarative and procedural memory) and their key capabilities (learning, memory retrieval, probability judgment, and utility estimation) can be implemented as algebraic operations on vectors and tensors in a high-dimensional space using a distributional semantics model.…