Laboratory automation is an expensive and complicated endeavor with limited inflexible options for small-scale labs. We develop a prototype system for tending to a bench-top centrifuge using computer vision methods for color detection and circular Hough Transforms to detect and localize centrifuge buckets. Initial results show that the prototype is capable of automating the usage of regular bench-top lab equipment.

Current methods to determine the energy efficiency of buildings require on-site visits of certified energy auditors which makes the process slow, costly, and geographically incomplete. To accelerate the identification of promising retrofit targets on a large scale, we propose to estimate building energy efficiency from widely available and remotely sensed data sources only, namely street view, aerial view, footprint, and satellite-borne land surface temperature (LST) data. After collecting data for almost 40,000 buildings in the United Kingdom, we combine these data sources by training multiple end-to-end deep learning models with the objective to classify buildings as energy efficient (EU rating A-D) or inefficient (EU rating E-G). After evaluating the trained models quantitatively as well as qualitatively, we extend our analysis by studying the predictive power of each data source in an ablation study. We find that the end-to-end deep learning model trained on all four data sources achieves a macro-averaged F1 score of 64.64% and outperforms the k-NN and SVM-based baseline models by 14.13 to 12.02 percentage points, respectively. Thus, this work shows the potential and complementary nature of remotely sensed data in predicting energy efficiency and opens up new opportunities for future work to integrate additional data sources.

Inc. surprised some with one of its next-gen commerce announcements. Amazon Go, which promises to eliminate the checkout altogether, generated headlines in mainstream media and prompted some to contemplate the potential demise of retail as we know it. Lost in all this hype is the fact that the brick-and-mortar apocalypse is no more likely today than it was before Amazon's recent endeavor. Of course, Amazon, which is the world's largest internet retailer, has set the standard for commerce reinvention with fast delivery, near-invisible payments and other perks tied to its Amazon Prime membership platform . Amazon has outpaced the rapid growth of digital commerce in the retail industry globally, increasing its own market share from 12% in 2011 to 19% in 2016, according to the latest data from Euromonitor International.