Pervasive 2007: It's about the User

Pervasive computing is as much about the user as it is about the technology. So, the Fifth International Conference on Pervasive Computing emphasized desirability rather than just feasibility. Featured themes included user benefits, human-computer interaction, group and social interactions, context awareness, finding and positioning people and objects, and personal privacy.     

The Impact of Fluid Dynamic Stress in Stirred Bioreactors – The Scale of the Biological Entity: A Personal View

From the start of industrial biotechnology, there has been a perception that biological entities are damaged by stirring, so-called ‘shear damage'. Often, it was the soft option to explain a loss of performance when it was due to other factors, such as bubble ingestion with proteins or on scale-up, where tip speed increased when it was due to decreased homogeneity, especially in pH. For many years, poor control and the range of analytical tools available made a more in-depth explanation difficult; and the concepts of ‘high' and ‘low shear' impellers, now largely disproven, increased it. Here, the size of the biological entity is compared to the Kolmogorov microscale of turbulence leading to a reasonably clear picture emerging. The article starts with the author's introduction to the issue approximately 42 year ago with enzymes, conveniently also the smallest entity; and finishes with the largest, filamentous fungi.     

确保管道运输的泄漏检测技术

保证所有管道中石油从一端流向另一端不泄漏要比它的探测更加困难。比较图中的3个系统,可以看到这项技术在40多年来是如何逐步发展的。     

The Role of Deep Learning in Parking Space Identification andPredictionSystems

In today’s smart city transportation, traffic congestion is a vexing issue, and vehicles seeking parking spaces have been identified as one of the causes leading to approximately 40% of traffic congestion. Identifying parking spaces alone is insufficient because an identified available parking space may have been taken by another vehicle when it arrives, resulting in the driver’s frustration and aggravating traffic jams while searching for another parking space. This explains the need to predict the availability of parking spaces. Recently, deep learning (DL) has been shown to facilitate drivers to find parking spaces efficiently, leading to a promising performance enhancement in parking identification and prediction systems. However, no work reviews DL approaches applied to solve parking identification and prediction problems. Inspired by this gap, the purpose of this work is to investigate, highlight, and report on recent advances in DL approaches applied to predict and identify the availability of parking spaces. A taxonomy of DL-based parking identification and prediction systems is established as a methodology by classifying and categorizing existing literature, and by doing so, the salient and supportive features of different DL techniques for providing parking solutions are presented. Moreover, several open research challenges are outlined. This work identifies that there are various DL architectures, datasets, and performance measures used to address parking identification and prediction problems. Moreover, there are some open-source implementations available that can be used directly either to extend existing works or explore a new domain. This is the first short survey article that focuses on the use of DL-based techniques in parking identification and prediction systems for smart cities. This study concludes that although the deployment of DL in parking identification and prediction systems provides various benefits, the convergence of these two types of systems and DL brings about new issues that must be resolved in the near future.     

Revamping SiO2 Spheres by Core–Shell Porosity Endowment to Construct a Mazelike Nanoreactor for Enhanced Catalysis in CO2 Hydrogenation to Methanol

Beyond the catalytic activity of nanocatalysts, the support with architectural design and explicit boundary could also promote the overall performance through improving the diffusion process, highlighting additional support for the morphology-dependent activity. To delineate this, herein, a novel mazelike-reactor framework, namely multi-voids mesoporous silica sphere (MVmSiO₂), is carved through a top-down approach by endowing core-shell porosity premade Stöber SiO₂ spheres. The precisely-engineered MVmSiO₂ with peripheral one-dimensional pores in the shell and interconnecting compartmented voids in the core region is simulated to prove combined hierarchical and structural superiority over its analogous counterparts. Supported with CuZn-based alloys, mazelike MVmSiO₂ nanoreactor experimentally demonstrated its expected workability in model gas-phase CO₂ hydrogenation reaction where enhanced CO₂ activity, good methanol yield, and more importantly, a prolonged stable performance are realized. While tuning the nanoreactor composition besides morphology optimization could further increase the catalytic performance, it is accentuated that the morphological architecture of support further boosts the reaction performance apart from comprehensive compositional optimization. In addition to the found morphological restraints and size-confinement effects imposed by MVmSiO₂, active sites of catalysts are also investigated by exploring the size difference of the confined CuZn alloy nanoparticles in CO₂ hydrogenation employing both in-situ experimental characterizations and density functional theory calculations.     

Quantitative Measurements of the Critical Impeller Speed for Solid‐Liquid Suspensions

A quantitative methodology for particle suspension assessment is presented. A new parameter, f_mov/tot, the ratio of the mean number of moving particles to the total number of particles, is introduced to evaluate the minimum speed required to just suspend solids. This approach is tested to investigate the impact of impeller clearance on the minimum impeller speed, N_js, in a vessel when using a radial flow Rushton turbine. Flow patterns and power numbers obtained experimentally and computationally support the suspension findings. Image analysis is an appropriate method for determining N_js. Lowering the impeller clearance reduces the speed required for particle suspension with a change of flow pattern from a radial discharge with two loops to a single loop scouring the vessel base. The power number also falls markedly at the two‐to‐one loop transition as does the strain rate near the base.     

An Experimental Study of Indoor and Outdoor Concentrations of Fine Particles Through Nonisothermal Cracks

It has been shown that a substantial proportion of indoor exposure is from particles originating outdoors. Idealized cracks have been used to study penetration under laboratory settings and all previous studies assumed isothermal conditions. There can be 10–20°C difference between indoor and outdoor temperatures even in mild climate zones. This is the first study to investigate the influence of thermophoresis on the penetration of particles through cracks. A sandwich design consisting of two chambers (each 0.325 [W] × 0.125 [L] × 0.11 [H] m³) and a crack module was used to measure indoor-to-outdoor particle concentrations under practical indoor and outdoor conditions. An idealized aluminum smooth crack of 90 mm crack length was tested under three different pressures ranging from 4 to 8 Pa. Submicron sodium chloride particles were generated and a scanning mobility particle sizer was used to scan the concentration in outdoor and indoor chambers. To mimic summer and winter conditions in temperate climatic zones, two sets of temperature differences (indoor–outdoor) were used: +18°C and ?10°C. I/O ratio and relative difference of I/O ratio compared to the isothermal condition were calculated. Inferring from the results, it can be observed that the I/O ratios under the winter scenario are substantially higher than those under the summer and isothermal scenarios for particle sizes less than 100 nm and the influence of temperature on I/O ratios diminishes with increasing particle sizes.

Copyright 2013 American Association for Aerosol Research