A linear algebra approach to OLAP

Inspired by the relational algebra of data processing, this paper addresses the foundations of data analytical processing from a linear algebra perspective. The paper investigates, in particular, how aggregation operations such as cross tabulations and data cubes essential to quantitative analysis of data can be expressed solely in terms of matrix multiplication, transposition and the Khatri–Rao variant of the Kronecker product. The approach offers a basis for deriving an algebraic theory of data consolidation, handling the quantitative as well as qualitative sides of data science in a natural, elegant and typed way. It also shows potential for parallel analytical processing, as the parallelization theory of such matrix operations is well acknowledged.     

Depth-Based Classification Method Underlain by a Remote Concentration Measure for Processing Asymmetric Data

A depth-based classification method underlain by a remote concentration measure for processing asymmetric data is developed and investigated. The motivation for the construction of the method was the inefficient use of affine invariant classifiers in combination with depth functions vanishing outside the convex hull of data. The idea of the proposed method is to map a remote space using a remote concentration measure, the Stahel–Donoho remoteness measure, and a corrected remoteness measure.     

Recognition of Actions of Medical Workers on the Basis of Accelerometer Readings with the Use of a Deep Belief Network

This paper analyzes a real set of large-volume medico-statistical data used for the recognition of actions of medical workers on the basis of accelerometer readings at definite moments of time. During the recognition process, a deep belief network was applied to unlabeled data, and then it was supervisedly learned using the error backpropagation method. The obtained results demonstrate higher recognition accuracy in comparison with basic methods. A considerable improvement in medical staff productivity is also achieved.     

Smooth Loops from Unconstrained Video

Converting unconstrained video sequences into videos that loop seamlessly is an extremely challenging problem. In this work, we take the first steps towards automating this process by focusing on an important subclass of videos containing a single dominant foreground object. Our technique makes two novel contributions over previous work: first, we propose a correspondence‐based similarity metric to automatically identify a good transition point in the video where the appearance and dynamics of the foreground are most consistent. Second, we develop a technique that aligns both the foreground and background about this transition point using a combination of global camera path planning and patch‐based video morphing. We demonstrate that this allows us to create natural, compelling, loopy videos from a wide range of videos collected from the internet.     

Taking science education beyond schooling

Abstract

The shape and content of science education has always been articulated from the scientist's perspective. Recently, an increasing number of science educators have recognized the serious limitations of this perspective and have proposed to define scientific literacy from societal or citizenship perspectives. In this article, I argue that these alternatives will remain as limited as their predecessors unless the very structures of schooling are called into question. Furthermore, I argue that alternatives cannot be designed at the drawing board by theoreticians, but have to be grounded in praxis, thereby providing concrete trajectories along which science education can actually change.     

Stabilization of One‐Dimensional Schrödinger Equation with Variable Coefficient under Delayed Boundary Output Feedback

This article considers stabilization of a one‐dimensional Schrödinger equation with variable coefficient and boundary observation which suffers from an arbitrary given time delay. We design an observer and predictor to stabilize the system. The state is estimated in the time span where the observation is available, and also predicted in the time interval where the observation is not available. It is shown that the estimated state feedback stabilizes the system exponentially. A numerical simulation is presented to illustrate the effect of the stabilizing controller.     

A new adaptive backstepping Coulomb friction compensator for servo control systems

A new Coulomb friction compensator is proposed for servo control systems in this paper. The novelty of the new approach lies in its capability of assigning the eigenvalues of the resulting closed loop system while attacking the problem. First, based on the standard backstepping methodology, an implicit Lyapunov function, with part of the components being only symbolically constructed at the very beginning, is utilized. To increase the robustness of the system against disturbance and model inaccuracy, an integral term is employed in the design. Using part of the variable gradient method, we are able to turn the implicit Lyapunov function into an explicit one, which is positive definite, and whose time‐derivative is negative definite. Second, it will be shown that the resulting closed loop error system is a switched linear system with two possible active modes that share the same set of eigenvalues, which is at our disposal. Unlike the common adaptive control design methods, such as the Control Lyapunov Function approach, in which the gains are typically positive but otherwise arbitrary, and are hence difficult to choose and have a lack of connection with the system's performance, our new scheme imposes two further constraints on the gains. It turns out that we can then match these gains with the coefficients of the desired characteristic equation of the closed loop system. In this respect, the gains are linked to the system's overall performance, which is a new and very appealing feature for such a scheme. Finally, a procedure of constructing a common Lyapunov function is provided to prove exponential stability of the aforementioned switched linear system. In addition, using the invariance principle, we will show the convergence of the estimated Coulomb friction coefficient to its real value. Numerical simulations are given to validate the effectiveness of the design and its robustness against friction time‐variations. Compared to existing results, the proposed scheme is much simpler, hence, much more advantageous computationally. Copyright © 2009 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

3D Semantic Scene Completion: A Survey

International Journal of Computer Vision - Semantic scene completion (SSC) aims to jointly estimate the complete geometry and semantics of a scene, assuming partial sparse input. In the last years...     

Designing Metallic and Insulating Nanocrystal Heterostructures to Fabricate Highly Sensitive and Solution Processed Strain Gauges for Wearable Sensors

All‐solution processed, high‐performance wearable strain sensors are demonstrated using heterostructure nanocrystal (NC) solids. By incorporating insulating artificial atoms of CdSe quantum dot NCs into metallic artificial atoms of Au NC thin film matrix, metal–insulator heterostructures are designed. This hybrid structure results in a shift close to the percolation threshold, modifying the charge transport mechanism and enhancing sensitivity in accordance with the site percolation theory. The number of electrical pathways is also manipulated by creating nanocracks to further increase its sensitivity, inspired from the bond percolation theory. The combination of the two strategies achieves gauge factor up to 5045, the highest sensitivity recorded among NC‐based strain gauges. These strain sensors show high reliability, durability, frequency stability, and negligible hysteresis. The fundamental charge transport behavior of these NC solids is investigated and the combined site and bond percolation theory is developed to illuminate the origin of their enhanced sensitivity. Finally, all NC‐based and solution‐processed strain gauge sensor arrays are fabricated, which effectively measure the motion of each finger joint, the pulse of heart rate, and the movement of vocal cords of human. This work provides a pathway for designing low‐cost and high‐performance electronic skin or wearable devices.