A history of the Norfolk Academy

Thesis (M.A.)--Boston University, 1948. This item was digitized by the Internet Archive

Correspondence from S. Laughton

Correspondence from S. Laughton regarding absent soldiers from Knox Count

Letter to John Hodsdon from Stephen W. Laughton, August 18, 1862

https://digitalmaine.com/adj_gen_corr_town_appleton/1006/thumbnail.jp

Correspondence from S. Laughton

Correspondence from S. Laughton regarding absent soldiers from Knox Count

Correspondence from S. Laughton

Correspondence from S. Laughton regarding absent soldiers from Knox Count

Correspondence from S. Laughton

Correspondence from S. Laughton regarding absent soldiers from Knox Count

CLAD: A Complex and Long Activities Dataset with Rich Crowdsourced Annotations

This paper introduces a novel activity dataset which exhibits real-life and diverse scenarios of complex, temporally-extended human activities and actions. The dataset presents a set of videos of actors performing everyday activities in a natural and unscripted manner. The dataset was recorded using a static Kinect 2 sensor which is commonly used on many robotic platforms. The dataset comprises of RGB-D images, point cloud data, automatically generated skeleton tracks in addition to crowdsourced annotations. Furthermore, we also describe the methodology used to acquire annotations through crowdsourcing. Finally some activity recognition benchmarks are presented using current state-of-the-art techniques. We believe that this dataset is particularly suitable as a testbed for activity recognition research but it can also be applicable for other common tasks in robotics/computer vision research such as object detection and human skeleton tracking

Symmetric sequence processing in a recurrent neural network model with a synchronous dynamics

The synchronous dynamics and the stationary states of a recurrent attractor neural network model with competing synapses between symmetric sequence processing and Hebbian pattern reconstruction is studied in this work allowing for the presence of a self-interaction for each unit. Phase diagrams of stationary states are obtained exhibiting phases of retrieval, symmetric and period-two cyclic states as well as correlated and frozen-in states, in the absence of noise. The frozen-in states are destabilised by synaptic noise and well separated regions of correlated and cyclic states are obtained. Excitatory or inhibitory self-interactions yield enlarged phases of fixed-point or cyclic behaviour.Comment: Accepted for publication in Journal of Physics A: Mathematical and Theoretica

Finite Size Effects in Separable Recurrent Neural Networks

We perform a systematic analytical study of finite size effects in separable recurrent neural network models with sequential dynamics, away from saturation. We find two types of finite size effects: thermal fluctuations, and disorder-induced `frozen' corrections to the mean-field laws. The finite size effects are described by equations that correspond to a time-dependent Ornstein-Uhlenbeck process. We show how the theory can be used to understand and quantify various finite size phenomena in recurrent neural networks, with and without detailed balance.Comment: 24 pages LaTex, with 4 postscript figures include

Where do we stand On Organ Printing

Abstract Attitude towards organ donation and the risks associated with organ transplantation drive the search for alternatives. One such alternative, albeit a conceptual level, could be the generation of an organ replacement in a controlled setting. For instance, growing suitable cells onto a printed matrix under appropriate conditions would then lead to the formation of a functional organ. How about the practical issues surrounding either duplication or de novo generation of an organ with, say, a device to print a suitable matrix and grow and differentiate cells on it? Here, we wish to outline selected safety-related questions arising from the ex vivo growth, differentiation and maintenance of cells or cell systems