The Multi-Lane Capsule Network (MLCN)

We introduce Multi-Lane Capsule Networks (MLCN), which are a separable and resource efficient organization of Capsule Networks (CapsNet) that allows parallel processing, while achieving high accuracy at reduced cost. A MLCN is composed of a number of (distinct) parallel lanes, each contributing to a dimension of the result, trained using the routing-by-agreement organization of CapsNet. Our results indicate similar accuracy with a much reduced cost in number of parameters for the Fashion-MNIST and Cifar10 datsets. They also indicate that the MLCN outperforms the original CapsNet when using a proposed novel configuration for the lanes. MLCN also has faster training and inference times, being more than two-fold faster than the original CapsNet in the same accelerator

The Bi-Functional Organization of Human Basement Membranes

The current basement membrane (BM) model proposes a single-layered extracellular matrix (ECM) sheet that is predominantly composed of laminins, collagen IVs and proteoglycans. The present data show that BM proteins and their domains are asymmetrically organized providing human BMs with side-specific properties: A) isolated human BMs roll up in a side-specific pattern, with the epithelial side facing outward and the stromal side inward. The rolling is independent of the curvature of the tissue from which the BMs were isolated. B) The epithelial side of BMs is twice as stiff as the stromal side, and C) epithelial cells adhere to the epithelial side of BMs only. Side-selective cell adhesion was also confirmed for BMs from mice and from chick embryos. We propose that the bi-functional organization of BMs is an inherent property of BMs and helps build the basic tissue architecture of metazoans with alternating epithelial and connective tissue layers

Financing and Deploying Automated Freight Systems

New technologies are bringing Automated Freight Systems (AFS), which aim to reduce congestion, mitigate environmental impacts and enhance public safety, to fruition. The financing and deployment issues of AFS differ from other Intelligent Transport System applications. This chapter briefly introduces major concepts of AFS. The financing strategies for these concepts are discussed, in which the government subsidies play an important role through the use of public-private partnership. Economies of scale and externalities of the current and new systems are discussed. In the discussion of the deployment of AFS, it is suggested that deployment schemes are highly correlated with financing strategies.Automated Freight, Pipeline, Trucks, Rail

Total Recall: Understanding Traffic Signs using Deep Hierarchical Convolutional Neural Networks

Recognizing Traffic Signs using intelligent systems can drastically reduce the number of accidents happening world-wide. With the arrival of Self-driving cars it has become a staple challenge to solve the automatic recognition of Traffic and Hand-held signs in the major streets. Various machine learning techniques like Random Forest, SVM as well as deep learning models has been proposed for classifying traffic signs. Though they reach state-of-the-art performance on a particular data-set, but fall short of tackling multiple Traffic Sign Recognition benchmarks. In this paper, we propose a novel and one-for-all architecture that aces multiple benchmarks with better overall score than the state-of-the-art architectures. Our model is made of residual convolutional blocks with hierarchical dilated skip connections joined in steps. With this we score 99.33% Accuracy in German sign recognition benchmark and 99.17% Accuracy in Belgian traffic sign classification benchmark. Moreover, we propose a newly devised dilated residual learning representation technique which is very low in both memory and computational complexity

A preliminary longitudinal study of white matter alteration in cocaine use disorder subjects

Background Previous diffusion tensor imaging (DTI) studies have consistently shown that subjects with cocaine use disorder (CocUD) had altered white matter microstructure in the corpus callosum. It is believed that these alterations are due to preexisting factors, chronic cocaine use, or both. However, there is no published longitudinal DTI study on human cocaine users yet which could shed light on the relationship between cocaine use and DTI findings. Methods This study used a longitudinal design and DTI to test if the white matter microstructure shows quicker alteration in CocUD subjects than controls. DTI data were acquired from eleven CocUD subjects who participated a treatment study and eleven non-drug-using controls at baseline (Scan 1) and after ten weeks (Scan 2). The baseline fractional anisotropy (FA), a general measure of white matter microstucture, and the change in FA (ΔFA, equals Scan 1 FA minus Scan 2 FA) were both compared between groups. Results The two groups did not show a difference in FA at baseline. The CocUD subjects had significantly greater ΔFA than the controls in the left splenium of the corpus callosum. In CocUD subjects, greater ΔFA in this region was associated with shorter lifetime cocaine use and greater number of positive cocaine urine samples collected during the treatment. Conclusion The finding in the left splenium is consistent with previous animal studies and provide indirect evidence about the effects of chronic cocaine use on white matter alterations. The subject sample size is small, therefore the results should be treated as preliminary