Mining multi-modal crime patterns at different levels of granularity using hierarchical clustering

The appearance of patterns could be found in different modalities of a domain, where the different modalities refer to the data sources that constitute different aspects of a domain. Particularly, the domain of our discussion refers to crime and the different modalities refer to the different data sources such as offender data, weapon data, etc. in crime domain. In addition, patterns also exist in different levels of granularity for each modality. In order to have a thorough understanding a domain, it is important to reveal the hidden patterns through the data explorations at different levels of granularity and for each modality. Therefore, this paper presents a new model for identifying patterns that exist in different levels of granularity for different modes of crime data. A hierarchical clustering approach - growing self organising maps (GSOM) has been deployed. Furthermore, the model is enhanced with experiments that exhibit the significance of exploring data at different granularities.

Innervation zone shift at different levels of isometric contraction in the biceps brachii muscle

Experiments were carried out to examine whether innervation zone (IZ) location remains stable at different levels of isometric contraction in the biceps brachii muscle (BB), and to determine how the proximity of the IZ affects common surface electromyography (sEMG) parameters. Twelve subjects performed maximal (MVC) and submaximal voluntary isometric contractions at 10%, 20%, 30%, 40%, 50% and 75% of MVC. sEMG signals were recorded with a 13 rows  5 columns grid of electrodes from the short head of BB. The IZ shifted in the proximal direction by up to 2.4 cm, depending upon the subject and electrode column. The mean shift of all the columns was 0.6 ± 0.4 cm (10% vs. 100% MVC, P < 0.001). This shift biased the average values of mean frequency (+21.8 ± 9.9 Hz, P < 0.001), root mean square (0.16 ± 0.15 mV, P < 0.05) and conduction velocity (1.15 ± 0.93 m/s, P < 0.01) in the channels immediately proximal to the IZ. The shift in IZ could be explained by shortening of the muscle fibers, and thus lengthening of the (distal) tendon due to increasing force. These results underline the importance of individual investigation of IZ locations before the placement of sEMG electrodes, even in isometric contractions.

Data with abnormal shift pattern in a manufacturing process

The data represents a shift in process variable presented in a control chart due to the sudden change in the machine setting.

Calibration of audio-video sensors for multi-modal event indexing

This paper addresses the coordinated use of video and audio cues to capture and index surveillance events with multimodal labels. The focus of this paper is the development of a joint-sensor calibration technique that uses audio-visual observations to improve the calibration process. One significant feature of this approach is the ability to continuously check and update the calibration status of the sensor suite, making it resilient to independent drift in the individual sensors. We present scenarios in which this system is used to enhance surveillance.

A coarse-grained parallel genetic algorithm employing cluster analysis for multi-modal numerical optimisation

This paper describes a technique for improving the performance of parallel genetic algorithms on multi-modal numerical optimisation problems. It employs a cluster analysis algorithm to identify regions of the search space in which more than one sub-population is sampling. Overlapping clusters are merged in one sub-population whilst a simple derating function is applied to samples in all other sub-populations to discourage them from further sampling in that region. This approach leads to a better distribution of the search effort across multiple subpopulations and helps to prevent premature convergence. On the test problems used, significant performance improvements over the traditional island model implementation are realised.

Osteo-cise : Strong bones for life': protocol for a community-based randomised controlled trial of a multi-modal exercise and osteoporosis education program for older adults at risk of falls and fractures

Background : Osteoporosis affects over 220 million people worldwide, and currently there is no 'cure' for the disease. Thus, there is a need to develop evidence-based, safe and acceptable prevention strategies at the population level that target multiple risk factors for fragility fractures to reduce the health and economic burden of the condition.

Methods : The 'Osteo-cise: Strong Bones for Life' study will investigate the effectiveness and feasibility of a multi-component targeted exercise, osteoporosis education/awareness and behavioural change program for improving bone health and muscle function, and reducing falls risk in community-dwelling older adults at an increased risk of fracture. Men and women aged 60 years or above will participate in an 18-month randomised controlled trial comprising a 12-month structured and supervised community-based program and a 6-month 'research to practise' translational phase. Participants will be randomly assigned to either the 'Osteo-cise' intervention or a self-management control group. The intervention will comprise a multi-modal exercise program incorporating high velocity progressive resistance training, moderate impact weight-bearing exercise and high challenging balance exercises performed three times weekly at local community-based fitness centres. A behavioural change program will be used to enhance exercise adoption and adherence to the program. Community-based osteoporosis education seminars will be conducted to improve participant knowledge and understanding of the risk factors and preventative measures for osteoporosis, falls and fractures. The primary outcomes measures, to be collected at baseline, 6, 12, and 18 months, will include DXA-derived hip and spine bone mineral density measurements and functional muscle power (timed stair-climb test). Secondary outcomes measures include: MRI-assessed distal femur and proximal tibia trabecular bone micro-architecture, lower limb and back maximal muscle strength, balance and function (four square step test, functional reach test, timed up-and-go test and 30-second sit-to-stand), falls incidence and health-related quality of life. Cost-effectiveness will also be assessed.

Discussion : The findings from the Osteo-cise: Strong Bones for Life study will provide new information on the efficacy of a targeted multi-modal community-based exercise program incorporating high velocity resistance training, together with an osteoporosis education and behavioural change program for improving multiple risk factors for falls and fracture in older adults at risk of fragility fracture. Trial Registration: Australian New Zealand Clinical Trials Registry reference ACTRN12609000100291

Low actuation-voltage shift in MEMS switch using ramp dual-pulse

This paper proposes a ramp dual-pulse actuation-voltage waveform that reduces actuation-voltage shift in capacitive microelectromechanical system (MEMS) switches. The proposed waveform as well as two reported waveforms (dual pulse, and novel dual-pulse) are analyzed using equivalent-circuit and equation models. Based on the analysis outcome, the paper provides a clear understanding of trapped charge density in the dielectric. The results show that the proposed actuation-voltage waveform successfully reduces trapped charge and increases lifetime due to lowering of actuation-voltage shift. Using the proposed actuation-voltage waveform, the membrane reaches a steady state on the electrode faster.

Population consequences of a predator-induced habitat shift by trout in whole-lake experiments

In a replicated whole-lake experiment, we (a) tested for the existence of a flexible habitat shift in response to predator presence in age-0 rainbow trout (Oncorhynchus mykiss) at risk of cannibalism and (b) evaluated the population-level consequences of habitat shifts in terms of growth and survival over their first growing season. Daphnid food and adult trout predators were substantially more abundant in pelagic than in littoral habitats. Age-0 trout used all habitats in populations without adult trout predators, whereas age-0 trout were observed only in the less profitable littoral habitat in populations with adult trout. Consequently, mean fall mass of age-0 trout in the presence of predators was almost half that observed in populations without adult trout. Despite the shift in habitat use, age-0 trout experienced 90% mortality when adult trout predators were present, in comparison to only 36% mortality when absent. We conclude that the commonly observed habitat shifts by fish at risk of predation, observed at smaller scales, do in fact occur at the whole-system scale over long time intervals. These results suggest that fish are able to perceive risk at large spatial scales and thus take advantage of profitable (but normally risky) habitats when predators are absent, or move to less profitable refuge habitats when predators are present.

Multi-modal abnormality detection in video with unknown data segmentation

This paper examines a new problem in large scale stream data: abnormality detection which is localized to a data segmentation process. Unlike traditional abnormality detection methods which typically build one unified model across data stream, we propose that building multiple detection models focused on different coherent sections of the video stream would result in better detection performance. One key challenge is to segment the data into coherent sections as the number of segments is not known in advance and can vary greatly across cameras; and a principled way approach is required. To this end, we first employ the recently proposed infinite HMM and collapsed Gibbs inference to automatically infer data segmentation followed by constructing abnormality detection models which are localized to each segmentation. We demonstrate the superior performance of the proposed framework in a real-world surveillance camera data over 14 days.