Coordinate descent with arbitrary sampling I: algorithms and complexity†

We study the problem of minimizing the sum of a smooth convex function and a convex block-separable regularizer and propose a new randomized coordinate descent method, which we call ALPHA. Our method at every iteration updates a random subset of coordinates, following an arbitrary distribution. No coordinate descent methods capable to handle an arbitrary sampling have been studied in the literature before for this problem. ALPHA is a very flexible algorithm: in special cases, it reduces to deterministic and randomized methods such as gradient descent, coordinate descent, parallel coordinate descent and distributed coordinate descent—both in nonaccelerated and accelerated variants. The variants with arbitrary (or importance) sampling are new. We provide a complexity analysis of ALPHA, from which we deduce as a direct corollary complexity bounds for its many variants, all matching or improving best known bounds.     

Fast template tracking in video sequences

Tracking of poorly defined, rotating and/or distorted objects in a video sequence poses significant problems especially in medical diagnostics including ultrasound (sonographic) video used for examination and diagnosis of internal movement of tissue or muscle and nerve action. Cross-correlation techniques have been successful in retrieving dynamic information directly from ultrasound video data. We outline a fast implementation of tracking based on normalized cross-correlation using an adaptive template and present results from our application, developed in MATLAB?, which successfully tracks arbitrarily selected objects in deformed or severely compromised images. Common ultrasound image evaluation is qualitative but there is need to retrieve quantitative dynamic information such as the trajectory or velocity of selected areas. Our approach uses normalized two-dimensional cross-correlation to find the position of an initially selected template enclosing the feature of interest and map its trajectory frame-by-frame to produce displacement and velocity plots. We illustrate operation of the application using routine ultrasound data and demonstrate its performance using test video of objects rotating full circle and rolling down a ramp. We analyse errors associated with sampling to compare performance of our implementation with a more rigorous but tedious and computationally expensive correlation of a resampled, rotated, and shifted template.     

Structure Processing of Web-Based Menus

Grounded in cognitive load theory, levels of processing theory, modes of learning research, and the facets of working memory (WM) framework, the primary goal of this investigation was to seek empirical evidence for a structure processing mechanism in WM that facilitates the coordination of associations made into coherent structures and the role this mechanism might play in performance and retention. This goal was motivated by a gap in the understanding of mental model production and encoding processes in WM. To carry out this goal, two usability studies were conducted to investigate retention, error, and time performance of Web-based menus created with structured or unstructured design. Relationships between these measures and coordination ability in WM, as well as storage and supervision ability, were also assessed. In Study 1, which tested simple Web-based menus, correlations of .28, ?.56, and ?.54 were detected between coordination (CC) and retention scores, CC and errors, and CC and time; in Study 2, which tested commercial Web-based menus, correlations of .46, ?.45, and ?.25 were detected. For Studies 1 and 2, differences in favor of structured design for retention, error, and time performance were highly significant (p < .001).     

Adiabatic quantum optimization with qudits

Most realistic solid state devices considered as qubits are not true two-state systems. If the energy separation of the upper energy levels from the lowest two levels is not large, then these upper states may affect the evolution of the ground state over time and therefore cannot be neglected. In this work, we study the effect of energy levels beyond the lowest two energy levels on adiabatic quantum optimization in a device with a double-well potential as the basic logical element. We show that the extra levels can be modeled by adding additional ancilla qubits coupled to the original logical qubits, and that the presence of upper levels has no effect on the final ground state. We also study the influence of upper energy levels on the minimum gap for a set of 8-qubit spin glass instances.     

Finding Your True IT Transformation

If you want to transform your business and cause a dramatic improvement for the enterprise, you'll need to start by truly transforming your IT life cycle. It's easy to believe that IT is truly reinventing itself by hiring new people, installing new tools, or preaching a new methodology. However, providing transformational leadership starts with the leadership itself along with the development of the three core competencies of strategy, solutions, and implementation. Your job in IT leadership is to develop all three competencies in your organization by cultivating the necessary skills and techniques, and then to cause each of them to happen continuously and concurrently. When these changes become the organization's new habits, you're on the path to true transformation.     

过程分析仪表

当需要监视一个不属于"四大类(压力、流量.温度、液位)"的过程变量时,可以通过一些过程分析仪表完成。这类仪表同样也有自己的"四大类":成分-探测计量过程流体中的某种化学成分;电化学-测量某种离子浓度,大多数是氢(pH);分光光度法-利用光的吸收特性测量某种成分。物理特性-测量重力、密度、粘度等物     

Physics-Informed Multistage Machine Learning Strategy for the Nanomachining-Induced Plastic Deformation Behavior

The evolution of the dislocation density induced by the nanomachining process dominates the plastic deformation behaviors of materials, thus affecting the mechanical properties significantly. However, a challenging topic related to how to establish an accurate model for predicting the dislocation density based on the limited simulations and experiments arises due to the complicated thermal–mechanical coupling mechanism during the machining process. Herein, a multistage method integrating machine learning, physics, and high-throughput atomic simulation is proposed to investigate the effect of cutting speed on the dislocation behavior in polycrystal copper. Compared with the traditional one-step machine learning method, the constraint of physical features effectively improves the accuracy and generalization ability of the model. The results indicate that the dislocation behaviors depend on the competition between the cutting force and temperature. In the low-cutting speed, the predominated role of the cutting temperature leads to a rapid decline of the dislocation density. In contrast, the dislocation density tends to be stable under a high-speed cutting process due to the dynamic balance between the effects of the cutting force and temperature. Notably, the proposed strategy provides a new and universal framework to design the machining parameters to obtain high-quality products.