GridHTM: Grid-Based Hierarchical Temporal Memory for Anomaly Detection in Videos

The interest in video anomaly detection systems that can detect different types of anomalies, such as violent behaviours in surveillance videos, has gained traction in recent years. The current approaches employ deep learning to perform anomaly detection in videos, but this approach has multiple problems. For example, deep learning in general has issues with noise, concept drift, explainability, and training data volumes. Additionally, anomaly detection in itself is a complex task and faces challenges such as unknownness, heterogeneity, and class imbalance. Anomaly detection using deep learning is therefore mainly constrained to generative models such as generative adversarial networks and autoencoders due to their unsupervised nature; however, even they suffer from general deep learning issues and are hard to properly train. In this paper, we explore the capabilities of the Hierarchical Temporal Memory (HTM) algorithm to perform anomaly detection in videos, as it has favorable properties such as noise tolerance and online learning which combats concept drift. We introduce a novel version of HTM, named GridHTM, which is a grid-based HTM architecture specifically for anomaly detection in complex videos such as surveillance footage. We have tested GridHTM using the VIRAT video surveillance dataset, and the subsequent evaluation results and online learning capabilities prove the great potential of using our system for real-time unsupervised anomaly detection in complex videos

Threshold for Onset of Injury in Chinook Salmon from Exposure to Impulsive Pile Driving Sounds

The risk of effects to fishes and other aquatic life from impulsive sound produced by activities such as pile driving and seismic exploration is increasing throughout the world, particularly with the increased exploitation of oceans for energy production. At the same time, there are few data that provide insight into the effects of these sounds on fishes. The goal of this study was to provide quantitative data to define the levels of impulsive sound that could result in the onset of barotrauma to fish. A High Intensity Controlled Impedance Fluid filled wave Tube was developed that enabled laboratory simulation of high-energy impulsive sound that were characteristic of aquatic far-field, plane-wave acoustic conditions. The sounds used were based upon the impulsive sounds generated by an impact hammer striking a steel shell pile. Neutrally buoyant juvenile Chinook salmon (Oncorhynchus tshawytscha) were exposed to impulsive sounds and subsequently evaluated for barotrauma injuries. Observed injuries ranged from mild hematomas at the lowest sound exposure levels to organ hemorrhage at the highest sound exposure levels. Frequency of observed injuries were used to compute a biological response weighted index (RWI) to evaluate the physiological impact of injuries at the different exposure levels. As single strike and cumulative sound exposure levels (SELss, SELcum respectively) increased, RWI values increased. Based on the results, tissue damage associated with adverse physiological costs occurred when the RWI was greater than 2. In terms of sound exposure levels a RWI of 2 was achieved for 1920 strikes by 177 dB re 1 µPa2⋅s SELss yielding a SELcum of 210 dB re 1 µPa2⋅s, and for 960 strikes by 180 dB re 1 µPa2⋅s SELss yielding a SELcum of 210 dB re 1 µPa2⋅s. These metrics define thresholds for onset of injury in juvenile Chinook salmon

Temperature-dependent electronic structure and ferromagnetism in the d=oo Hubbard model studied by a modfied perturbation theory

The infinite-dimensional Hubbard model is studied by means of a modified perturbation theory. The approach reduces to the iterative perturbation theory for weak coupling. It is exact in the atomic limit and correctly reproduces the dispersions and the weights of the Hubbard bands in the strong-coupling regime for arbitrary fillings. Results are presented for the hyper-cubic and an fcc-type lattice. For the latter we find ferromagnetic solutions. The filling-dependent Curie temperature is compared with the results of a recent Quantum Monte Carlo study.Comment: RevTeX, 5 pages, 6 eps figures included, Phys. Rev. B (in press), Ref. 16 correcte

HTAD: A Home-Tasks Activities Dataset with Wrist-Accelerometer and Audio Features

In this paper, we present HTAD: A Home Tasks Activities Dataset. The dataset contains wrist-accelerometer and audio data from people performing at-home tasks such as sweeping, brushing teeth, washing hands, or watching TV. These activities represent a subset of activities that are needed to be able to live independently. Being able to detect activities with wearable devices in real-time is important for the realization of assistive technologies with applications in different domains such as elderly care and mental health monitoring. Preliminary results show that using machine learning with the presented dataset leads to promising results, but also there is still improvement potential. By making this dataset public, researchers can test different machine learning algorithms for activity recognition, especially, sensor data fusion methodsacceptedVersio

Automatic Unsupervised Clustering of Videos of the Intracytoplasmic Sperm Injection (ICSI) Procedure

The in vitro fertilization procedure called intracytoplasmic sperm injection can be used to help fertilize an egg by injecting a single sperm cell directly into the cytoplasm of the egg. In order to evaluate, refine and improve the method in the fertility clinic, the procedure is usually observed at the clinic. Alternatively, a video of the procedure can be examined and labeled in a time-consuming process. To reduce the time required for the assessment, we propose an unsupervised method that automatically clusters video frames of the intracytoplasmic sperm injection procedure. Deep features are extracted from the video frames and form the basis for a clustering method. The method provides meaningful clusters representing different stages of the intracytoplasmic sperm injection procedure. The clusters can lead to more efficient examinations and possible new insights that can improve clinical practice. Further on, it may also contribute to improved clinical outcomes due to increased understanding about the technical aspects and better results of the procedure. Despite promising results, the proposed method can be further improved by increasing the amount of data and exploring other types of features

Gender differentials in the payoff to schooling in rural China

This article examines the gender differential in the payoff to schooling in rural China. The analyses are based on a framework provided by the over education/required education/under education literature, and the decomposition developed by Chiswick and Miller (2008). It shows that the payoff to correctly matched education in rural China is much higher for females than for males. Associated with this, the wage penalty where workers are under qualified in their occupation is greater for females than for males. Over educated females, however, are advantaged compared with their male counterparts. These findings are interpreted using the explanations offered for the gender differential in the payoff to schooling in the growing literature on earnings determination in China