Heterogeneous length-of-stay modeling of post-acute care residents in the nursing home with competing discharge dispositions

Post-acute care (PAC) residents in nursing homes (NHs) are recently hospitalized patients with medically complex diagnoses, ranging from severe orthopedic injuries to cardiovascular diseases. A major role of NHs is to maximize restoration of PAC residents during their NH stays with desirable discharge outcomes, such as higher community discharge likelihood and lower re/hospitalization risk. Accurate prediction of the PAC residents’ length-of-stay (LOS) with multiple discharge dispositions (e.g., community discharge and re/hospitalization) will allow NH management groups to stratify NH residents based on their individualized risk in realizing personalized and resident-centered NH care delivery. Due to the highly heterogeneous health conditions of PAC residents and their multiple types of correlated discharge dispositions, developing an accurate prediction model becomes challenging. Existing predictive analytics methods, such as distribution-/regression-based methods and machine learning methods, either fail to incorporate varied individual characteristics comprehensively or ignore multiple discharge dispositions. In this work, a data-driven predictive analytics approach is considered to jointly predict the individualized re/hospitalization risk and community discharge likelihood over time in the presence of varied residents’ characteristics. A sampling algorithm is further developed to generate accurate predictive samples for a heterogeneous population of PAC residents in an NH and facilitate facility-level performance evaluation. A real case study using large-scale NH data is provided to demonstrate the superior prediction performance of the proposed work at individual and facility levels through comprehensive comparison with a large number of existing prediction methods as benchmarks. The developed analytics tools will allow NH management groups to identify the most at-risk residents by providing them with more proactive and focused care to improve resident outcomes.     

Managing cognitive biases during disaster response: the development of an aide memoire

Disasters are highly complex with often extreme consequences and are often exacerbated by decision errors. Human behaviour in this domain offers a fertile     

Real-time occlusion tolerant detection of illegally parked vehicles

Illegally parked vehicle detection systems are considered crucial elements in the development of any video-surveillance based traffic-management system. The major challenges in this task lie in making the end solution real time, illumination invariant and occlusion tolerant. A two-stage application framework is presented which efficiently identifies vehicles parked illegally in restricted parking-zones. A real-time approach has been followed and an improved foreground segmentation method based on Segmentation History Images (SHI) is developed to identify stationary objects. A three step pixel based classification method is applied on the background segmentation output to segment adjacent moving pixels that become stationary for certain periods of time. The process then locks on to all identified stationary pixel patches, parts of which overlap with the regions of interest marked interactively a priori. The second stage of the process is applied subsequently to track all the stationary pixel patches detected during the first stage using an adaptive edge orientation based tracking method. Experimental results show that the tracking technique gives more than a 90% detection success rate, even if objects are partially occluded. The technique has been tested on the UK Home Office i-LIDS Parked Vehicle video sequences along with the University of Sussex Traffic Dataset and results are compared with other available state of the art methods.     

Patterns on a Surface: The Reconciliation of the Circle and the Square

The theory of heat flow on a surface shows that any curvilinear quadrilateral can be ‘tiled’ with curvilinear squares of varying size. This paper demonstrates a simple numerical technique for doing this that can also be applied to shapes other than quadrilaterals. In particular, any curvilinear triangle can be tiled with curvilinear equilateral triangles.     

Secure peer-to-peer trading in small- and large-scale multiplayer games

A fundamental aspect of many multiplayer online games is the ability to trade items between players. Trading may occur with items that were found in the virtual environment, included as pieces of the game, or purchased by the player as assets. Regardless of the types of items, any multiplayer game that supports trading or exchanging items in the game must do so in a secure manner. We have developed a protocol to solve the problem of secure peer-to-peer trading in games in which the primary concern is that items are exchanged fairly, and additionally that items are not duplicated. Our protocol enables one-way and two-way trades and can be extended to multi-item trades in both small- and large-scale games where trades last only for the duration of a session or are persistent. We show that our protocol addresses the security threats which it might encounter, and then provide an analysis to demonstrate its scalability.     

Anti-contamination device for cryogenic soft X-ray diffraction microscopy

Cryogenic microscopy allows one to view frozen hydrated biological and soft matter specimens with good structural preservation and a high degree of stability against radiation damage. We describe a liquid nitrogen-cooled anti-contamination device for cryogenic X-ray diffraction microscopy. The anti-contaminator greatly reduces the buildup of ice layers on the specimen due to condensation of residual water vapor in the experimental vacuum chamber. We show by coherent X-ray diffraction measurements that this leads to fivefold reduction of background scattering, which is important for far-field X-ray diffraction microscopy of biological specimens.