Variational Deep Semantic Hashing for Text Documents

As the amount of textual data has been rapidly increasing over the past decade, efficient similarity search methods have become a crucial component of large-scale information retrieval systems. A popular strategy is to represent original data samples by compact binary codes through hashing. A spectrum of machine learning methods have been utilized, but they often lack expressiveness and flexibility in modeling to learn effective representations. The recent advances of deep learning in a wide range of applications has demonstrated its capability to learn robust and powerful feature representations for complex data. Especially, deep generative models naturally combine the expressiveness of probabilistic generative models with the high capacity of deep neural networks, which is very suitable for text modeling. However, little work has leveraged the recent progress in deep learning for text hashing. In this paper, we propose a series of novel deep document generative models for text hashing. The first proposed model is unsupervised while the second one is supervised by utilizing document labels/tags for hashing. The third model further considers document-specific factors that affect the generation of words. The probabilistic generative formulation of the proposed models provides a principled framework for model extension, uncertainty estimation, simulation, and interpretability. Based on variational inference and reparameterization, the proposed models can be interpreted as encoder-decoder deep neural networks and thus they are capable of learning complex nonlinear distributed representations of the original documents. We conduct a comprehensive set of experiments on four public testbeds. The experimental results have demonstrated the effectiveness of the proposed supervised learning models for text hashing.Comment: 11 pages, 4 figure

Hamstrings co-activation in ACL-deficient subjects during isometric whole-leg extensions

It has been reported that anterior cruciate ligament (ACL)-deficient subjects increase the level of hamstrings activation and this has been interpreted as a means to cope with increased anterior tibial laxity in the knee. This study aimed to establish to what extent co-activation strategies in ACL-deficient subjects are load level and knee angle dependent. Eleven chronic ACL-deficient and 15 control subjects were positioned in a range of postures and asked to exert a feedback controlled vertical ground reaction force (GRF; 30, 60% and maximum), while horizontal forces were not constrained. Surface electromyography of the leg muscles and GRF were measured. In postures with the knee over and in front of the ankle, ACL-deficient subjects generated, respectively, 2.4 and 5.1% MVC more hamstrings activation than control subjects. Enhanced hamstrings co-activation in ACL-deficient subjects was more apparent in extended than in flexed knee angles. For both ACL-deficient and control subjects, hamstrings co-activation was larger in males than in females. It is concluded that ACL-deficient subjects show a task dependent increase in hamstrings co-activation, but its clinical significance remains to be shown. © Springer-Verlag 2009

Contribution of arm movements to balance recovery after tripping in older adults

\ua9 2022 The AuthorsFalls are common in daily life, often caused by trips and slips and, particularly in older adults, with serious consequences. Although arm movements play an important role in balance control, there is limited research into the role of arm movements during balance recovery after tripping in older adults. We investigated how older adults use their arms to recover from a trip and the difference in the effects of arm movements between fallers (n = 5) and non-fallers (n = 11). Sixteen older males and females (69.7 \ub1 2.3 years) walked along a walkway and were occasionally tripped over suddenly appearing obstacles. We analysed the first trip using a biomechanical model based on full-body kinematics and force-plate data to calculate whole body orientation during the trip and recovery phase. With this model, we simulated the effects of arm movements at foot-obstacle impact and during trip recovery on body orientation. Apart from an increase in sagittal plane forward body rotation at touchdown in fallers, we found no significant differences between fallers and non-fallers in the effects of arm movements on trip recovery. Like earlier studies in young adults, we found that arm movements during the recovery phase had most favourable effects in the transverse plane: by delaying the transfer of angular momentum of the arms to the body, older adults rotated the tripped side more forward thereby allowing for a larger recovery step. Older adults that are prone to falling might improve their balance recovery after tripping by learning to prolong ongoing arm movements

The effects of ergonomic interventions on low back moments are attenuated by changes in lifting behaviour

This study investigated the effects of ergonomic interventions involving a reduction of the mass (from 16 to 11 and 6 kg) and an increase in the initial lifting height (from pallet height to 90 cm above the ground) of building blocks in a mock-up of an industrial depalletizing task, investigating lifting behaviour as well as low back moments (calculated using a 3-D linked segment model). Nine experienced construction workers participated in the experiment, in which they removed building blocks from a pallet in the way they normally did during their work. Most of the changes in lifting behaviour that were found would attenuate the effect of the investigated interventions on low back moments. When block mass was reduced from 16 to 6 kg, subjects chose to lift the building block from a 10 (SD 10) cm greater distance from the front edge of the pallet and with a 100 (SD 66) degrees/