Processing multiple image streams for real-time monitoring of parking lots

We present a system to detect parked vehicles in a typical parking complex using multiple streams of images captured through IP connected devices. Compared to traditional object detection techniques and machine learning methods, our approach is significantly faster in detection speed in the presence of multiple image streams. It is also capable of comparable accuracy when put to test against existing methods. And this is achieved without the need to train the system that machine learning methods require. Our approach uses a combination of psychological insights obtained from human detection and an algorithm replicating the outcomes of a SVM learner but without the noise that compromises accuracy in the normal learning process. Performance enhancements are made on the algorithm so that it operates well in the context of multiple image streams. The result is faster detection with comparable accuracy. Our experiments on images captured from a local test site shows very promising results for an implementation that is not only effective and low cost but also opens doors to new parking applications when combined with other technologies.

Real-time electrochemical monitoring of covalent bond formation in solution via nanoparticle-electrode collisions

We describe an alternative electrochemical technique to monitor covalent bond formation in real-time using nanoparticle-electrode collisions. The method is based on recognising the redox current when MP-11 functionalised chemical reduced graphene oxide (rGO) nanosheets collide with Lomant's reagent modified gold microelectrode. This facile and highly sensitive monitoring method can be useful for investigating the fundamental of single-molecule reactions.

Measurement and data transmission validity of a multi-biosensor system for real-time remote exercise monitoring among cardiac patients

Background: Remote telemonitoring holds great potential to augment management of patients with coronary heart disease (CHD) and atrial fibrillation (AF) by enabling regular physiological monitoring during physical activity. Remote physiological monitoring may improve home and community exercise-based cardiac rehabilitation (exCR) programs and could improve assessment of the impact and management of pharmacological interventions for heart rate control in individuals with AF.

Objective: Our aim was to evaluate the measurement validity and data transmission reliability of a remote telemonitoring system comprising a wireless multi-parameter physiological sensor, custom mobile app, and middleware platform, among individuals in sinus rhythm and AF.

Methods: Participants in sinus rhythm and with AF undertook simulated daily activities, low, moderate, and/or high intensity exercise. Remote monitoring system heart rate and respiratory rate were compared to reference measures (12-lead ECG and indirect calorimeter). Wireless data transmission loss was calculated between the sensor, mobile app, and remote Internet server.

Results: Median heart rate (-0.30 to 1.10 b∙min-1) and respiratory rate (-1.25 to 0.39 br∙min-1) measurement biases were small, yet statistically significant (all P≤.003) due to the large number of observations. Measurement reliability was generally excellent (rho=.87-.97, all P<.001; intraclass correlation coefficient [ICC]=.94-.98, all P<.001; coefficient of variation [CV]=2.24-7.94%), although respiratory rate measurement reliability was poor among AF participants (rho=.43, P<.001; ICC=.55, P<.001; CV=16.61%). Data loss was minimal (<5%) when all system components were active; however, instability of the network hosting the remote data capture server resulted in data loss at the remote Internet server during some trials.

Conclusions: System validity was sufficient for remote monitoring of heart and respiratory rates across a range of exercise intensities. Remote exercise monitoring has potential to augment current exCR and heart rate control management approaches by enabling the provision of individually tailored care to individuals outside traditional clinical environments.

A real-time abnormality detection system for intensive care management

Detecting abnormalities from multiple correlated time series is valuable to those applications where a credible realtime event prediction system will minimize economic losses (e.g. stock market crash) and save lives (e.g. medical surveillance in the operating theatre). For example, in an intensive care scenario, anesthetists perform a vital role in monitoring the patient and adjusting the flow and type of anesthetics to the patient during an operation. An early awareness of possible complications is vital for an anesthetist to correctly react to a given situation. In this demonstration, we provide a comprehensive medical surveillance system to effectively detect abnormalities from multiple physiological data streams for assisting online intensive care management. Particularly, a novel online support vector regression (OSVR) algorithm is developed to approach the problem of discovering the abnormalities from multiple correlated time series for accuracy and real-time efficiency. We also utilize historical data streams to optimize the precision of the OSVR algorithm. Moreover, this system comprises a friendly user interface by integrating multiple physiological data streams and visualizing alarms of abnormalities. © 2013 IEEE.

Real-time quartz crystal microbalance monitoring of free docosahexaenoic acid interactions with supported lipid bilayers.

Docosahexaenoic acid (DHA) is the most abundant polyunsaturated omega-3 fatty acid found in mammalian neuronal cell membranes. Although DHA is known to be important for neuronal cell survival, little is know about how DHA interacts with phospholipid bilayers. This study presents a detailed quartz crystal microbalance with dissipation monitoring (QCM-D) analysis of free DHA interactions with individual and mixed phospholipid supported lipid bilayers (SLB). DHA incorporation and subsequent changes to the SLBs viscoelastic properties were observed to be concentration-dependent, influenced by the phospholipid species, the headgroup charge, and the presence or absence of calcium ions. It was observed that 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) SLBs incorporated the greatest amount of DHA concentration, whereas the presence of phospholipids, phosphatidylserine (PS), and phosphatidylinositol (PI) in a POPC SLB significantly reduced DHA incorporation and changed the SLBs physicochemical properties. These observations are hypothesized to be due to a substitution event occurring between DHA and phospholipid species. PS domain formation in POPC/PS 8:2 SLBs was observed in the presence of calcium ions, which favored DHA incorporation to a similar level as for a POPC only SLB. The changes in SLB thickness observed with different DHA concentrations are also presented. This work contributes to an understanding of the physical changes induced in a lipid bilayer as a consequence of its exposure to different DHA concentrations (from 50 to 200 μM). The capacity of DHA to influence the physical properties of SLBs indicates the potential for dietary DHA supplementation to cause changes in cellular membranes in vivo, with subsequent physiological consequences for cell function.

Effect of creatine supplementation on housekeeping genes in human skeletal muscle using real-time RT-PCR

The present study examined the validity and reliability of measuring the expression of various genes in human skeletal muscle using quantitative real-time RT-PCR on a GeneAmp 5700 sequence detection system with SYBR Green 1 chemistry. In addition, the validity of using some of these genes as endogenous controls (i.e., housekeeping genes) when human skeletal muscle was exposed to elevated total creatine levels and exercise was also examined. For all except 28S, linear relationships between the logarithm of the starting RNA concentrations and the cycle threshold (C_T) values were established for ß-actin, ß2-microglobulin (ß₂M), cyclophilin (CYC), and glyceraldehyde-3-phosphate dehydrogenase (GAPDH). We found a linear response between C_T values and the logarithm of a given amount of starting cDNA for all the genes tested. The overall intra-assay coefficient of variance for these genes was 1.3% and 21% for raw C_T values and the linear value of 2^-C_T, respectively. Interassay variability was 2.3% for raw C_T values and 34% for the linear value of 2^-C_T. We also examined the expression of various housekeeping genes in human skeletal muscle at days 0, 1, and 5 following oral supplementation with either creatine or a placebo employing a double-blind crossover study design. Treatments were separated by a 5-wk washout period. Immediately following each muscle sampling, subjects performed two 30-s all-out bouts on a cycle ergometer. Creatine supplementation increased (P < 0.05) muscle total creatine content above placebo levels; however, there were no changes (P > 0.05) in C_T values across the supplementation periods for any of the genes. Nevertheless, 95% confidence intervals showed that GAPDH was variable, whereas ß-actin, ß₂M, and CYC were the least varying genes. Normalization of the data to these housekeeping genes revealed variable behavior for ß₂M with more stable expressions for both ß-actin and CYC. We conclude that, using real-time RT-PCR, ß-actin or CYC may be used as housekeeping genes to study gene expression in human muscle in experiments employing short-term creatine supplementation combined with high-intensity exercise.

A video-based real-time vehicle detection method by classified background learning

A new two-level real-time vehicle detection method is proposed in order to meet the robustness and efficiency requirements of real world applications. At the high level, pixels of the background image are classified into three categories according to the characteristics of Red, Green, Blue (RGB) curves. The robustness of the classification is further enhanced by using
line detection and pattern connectivity. At the lower level, an exponential forgetting algorithm with adaptive parameters for different categories is utilised to calculate the background and reduce the distortion by the small motion of video cameras. Scene tests show that the proposed method is more robust and faster than previous methods, which is very suitable for real-time vehicle detection in outdoor environments, especially concerning locations where the level of illumination changes frequently and speed detection is important.

Real-time early infectious outbreak detection systems using emerging technologies

The use of emerging technologies ( such as RFID - Radio Frequency Identification and remote sensing) can be employed to reduce health care costs and also to facilitate the automatic streamlining of infectious disease outbreak detection and monitoring processes in local health departments. It can assist medical practitioners with fast and accurate diagnosis and treatments. In this paper we outline the design and application of a real-time RFID and sensor-base Early Infectious (e.g., cholera) Outbreak Detection and Monitoring (IODM) system for health care.

Animal-borne sensors successfully capture the real-time thermal properties of ocean basins

Climate change is perhaps the most pressing and urgent environmental issue facing the world today. However our ability to predict and quantify the consequences of this change is severely limited by the paucity of in situ oceanographic measurements. Marine animals equipped with sophisticated oceanographic data loggers to study their behavior offer one solution to this problem because marine animals range widely across the world’s ocean basins and visit remote and often inaccessible locations. However, unlike the information being collected from conventional oceanographic sensing equipment, which has been validated, the data collected from instruments deployed on marine animals over long periods has not. This is the first long-term study to validate in situ oceanographic data collected by animal oceanographers. We compared the ocean temperatures collected by leatherback turtles (Dermochelys coriacea) in the Atlantic Ocean with the ARGO network of ocean floats and could find no systematic errors that could be ascribed to sensor instability. Animal-borne sensors allowed water temperature to be monitored across a range of depths, over entire ocean basins, and, importantly, over long periods and so will play a key role in assessing global climate change through improved monitoring of global temperatures. This finding is especially pertinent given recent international calls for the development and implementation of a comprehensive Earth observation system (see http://iwgeo.ssc.nasa.gov/documents.asp?s=review) that includes the use of novel techniques for monitoring and understanding ocean and climate interactions to address strategic environmental and societal needs.

Emergent effects in massive agent swarms in real-time game environments

 Computational efficiency and hence the scale of agent-based swarm simulations is bound by the nearest neighbour computation for each agent. This article proposes the use of GPU texture memory to implement lookup tables for a spatial partitioning based k-Nearest Neighbours algorithm. These improvements allow simulation of swarms of 220 agents at higher rates than the current best alternative algorithms. This approach is incorporated into an existing framework for simulating steering behaviours allowing for a complete implementation of massive agent swarm simulations, with per agent behaviour preferences, on a Graphics Processing Unit. These simulations have enabled an investigation of the emergent dynamics that occur when massive swarms interact with a choke point in their environment. Various modes of sustained dynamics with temporal and spatial coherence are identified when a critical mass of agents is simulated and some elementary properties are presented. The algorithms presented in this article enable researchers and content designers in games and movies to implement truly massive agent swarms in real time and thus provide a basis for further identification and analysis of the emergent dynamics in these swarms. This will improve not only the scale of swarms used in commercial games and movies but will also improve the reliability of swarm behaviour with respect to content design goals.

Robust real-time bio-kinematic movement tracking using multiple kinects for tele-rehabilitation

This paper investigates the robust and accurate capture of human joint poses and bio-kinematic movements for exercise monitoring in real-time tele-rehabilitation applications. Recently developed model-based estimation ideas are used to improve the accuracy, robustness, and real-time characteristics considered vital for applications, where affordability and domestic use are the primary focus. We use the spatial diversity of the arbitrarily positioned Microsoft Kinect receivers to improve the reliability and promote the uptake of the concept. The skeleton-based information is fused to enhance accuracy and robustness, critical for biomedical applications. A specific version of a robust Kalman filter (KF) in a linear framework is employed to ensure superior estimator convergence and real-time use, compared to other commonly used filters. The algorithmic development was conducted in a generic form and computer simulations were conducted to verify our assertions. Hardware implementations were carried out to test the viability of the proposed state estimator in terms of the core requirements of reliability, accuracy, and real-time use. Performance of the overall system implemented in an information fusion context was evaluated against the commercially available and industry standard Vicon system for different exercise routines, producing comparable results with much less infrastructure and financial investment.

Multimodal iron oxide (Fe₃O₄)-saturated lactoferrin nanocapsules as nanotheranostics for real-time imaging and breast cancer therapy of claudin-low, triple-negative (ER-/PR-/HER2-)

AIM: To unravel the multimodal nanotheranostic ability of Fe3O4-saturated bovine lactoferrin nanocapsules (FebLf NCs) in claudin-low, triple-negative breast cancer model. MATERIALS & METHODS: Xenograft study was performed to examine biocompatibility, antitumor efficacy and multimodal nanotheranostic action in combination with near-infrared live mice imaging. RESULTS: FebLf NCs exhibited a size range of 80 nm ± 5 nm with observed superparamagnetism. FebLf NCs successfully internalized into breast cancer cells through receptor-mediated endocytosis and induced apoptosis through the downregulation of inhibitor of apoptosis survivin and livin proteins. Investigations revealed a remarkable biocompatibility, anticancer efficacy of the FebLf NCs. Near-infrared imaging observations confirmed selective localization of multimodal FebLf NCs at the tumor site and lead to time-dependent reduction of tumor growth. CONCLUSION: FebLf NCs can be safe, biocompatible nanotheranostic approach for real-time imaging and monitoring the effect of drugs in real time and have potentials in future clinical trials.

Providing real-time information services for public bus commuters

This paper investigates RTIS for public bus commuters; identifying their needs and proposing the architecture and design for this service. Considering that the service needs to be extensible, adaptable and interoperative, the new system is based on the use of XML Web Services. This gives the structure flexibility for further development and integration with other like services.

Miscibility, crystallization κinetics and real-time small-Angle x-ray scattering investigation of the semicrystalline morphology in thermosetting polymer blends of epoxy resin and poly(ethylene oxide)

Thermosetting polymer blends of poly(ethylene oxide) (PEO) and bisphenol-A-type epoxy resin (ER) were prepared using 4,4′-methylenebis(3-chloro-2,6-diethylaniline) (MCDEA) as curing agent. The miscibility and crystallization behavior of MCDEA-cured ER/PEO blends were investigated by differential scanning calorimetry (DSC). The existence of a single composition-dependent glass transition temperature (Tg) indicates that PEO is completely miscible with MCDEA-cured ER in the melt and in the amorphous state over the entire composition range. Fourier-transform infrared (FTIR) investigations indicated hydrogen-bonding interaction between the hydroxyl groups of MCDEA-cured ER and the ether oxygens of PEO in the blends, which is an important driving force for the miscibility of the blends. The average strength of the hydrogen bond in the cured ER/PEO blends is higher than in the pure MCDEA-cured ER. Crystallization kinetics of PEO from the melt is strongly influenced by the blend composition and the crystallization temperature. At high conversion, the time dependence of the relative degree of crystallinity deviated from the Avrami equation. The addition of a non-crystallizable ER component into PEO causes a depression of both the overall crystallization rate and the melting temperature. The surface free energy of folding σe displays a minimum with variation of composition. The spherulitic morphology of PEO in the ER/PEO blends exhibits typical characteristics of miscible crystalline/amorphous blends, and the PEO spherulites in the blends are always completely volume-filling. Real-time small-angle X-ray scattering (SAXS) experiments reveal that the long period L increases drastically with increasing ER content at the same temperatures. The amorphous cured ER component segregates interlamellarly during the crystallization process of PEO because of the low chain mobility of the cured ER. A model describing the semicrystalline morphology of MCDEA-cured ER/PEO blends is proposed based on the SAXS results. The semicrystalline morphology is a stack of crystalline lamellae; the amorphous fraction of PEO, the branched ER chains and imperfect ER network are located between PEO lamellae.