971 resultados para real time passenger information system
Resumo:
In this paper, a simulation model of glucose-insulin metabolism for Type 1 diabetes patients is presented. The proposed system is based on the combination of Compartmental Models (CMs) and artificial Neural Networks (NNs). This model aims at the development of an accurate system, in order to assist Type 1 diabetes patients to handle their blood glucose profile and recognize dangerous metabolic states. Data from a Type 1 diabetes patient, stored in a database, have been used as input to the hybrid system. The data contain information about measured blood glucose levels, insulin intake, and description of food intake, along with the corresponding time. The data are passed to three separate CMs, which produce estimations about (i) the effect of Short Acting (SA) insulin intake on blood insulin concentration, (ii) the effect of Intermediate Acting (IA) insulin intake on blood insulin concentration, and (iii) the effect of carbohydrate intake on blood glucose absorption from the gut. The outputs of the three CMs are passed to a Recurrent NN (RNN) in order to predict subsequent blood glucose levels. The RNN is trained with the Real Time Recurrent Learning (RTRL) algorithm. The resulted blood glucose predictions are promising for the use of the proposed model for blood glucose level estimation for Type 1 diabetes patients.
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The COSMIC-2 mission is a follow-on mission of the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) with an upgraded payload for improved radio occultation (RO) applications. The objective of this paper is to develop a near-real-time (NRT) orbit determination system, called NRT National Chiao Tung University (NCTU) system, to support COSMIC-2 in atmospheric applications and verify the orbit product of COSMIC. The system is capable of automatic determinations of the NRT GPS clocks and LEO orbit and clock. To assess the NRT (NCTU) system, we use eight days of COSMIC data (March 24-31, 2011), which contain a total of 331 GPS observation sessions and 12 393 RO observable files. The parallel scheduling for independent GPS and LEO estimations and automatic time matching improves the computational efficiency by 64% compared to the sequential scheduling. Orbit difference analyses suggest a 10-cm accuracy for the COSMIC orbits from the NRT (NCTU) system, and it is consistent as the NRT University Corporation for Atmospheric Research (URCA) system. The mean velocity accuracy from the NRT orbits of COSMIC is 0.168 mm/s, corresponding to an error of about 0.051 μrad in the bending angle. The rms differences in the NRT COSMIC clock and in GPS clocks between the NRT (NCTU) and the postprocessing products are 3.742 and 1.427 ns. The GPS clocks determined from a partial ground GPS network [from NRT (NCTU)] and a full one [from NRT (UCAR)] result in mean rms frequency stabilities of 6.1E-12 and 2.7E-12, respectively, corresponding to range fluctuations of 5.5 and 2.4 cm and bending angle errors of 3.75 and 1.66 μrad .
Resumo:
The Personal Health Assistant Project (PHA) is a pilot system implementation sponsored by the Kozani Region Governors’ Association (KRGA) and installed in one of the two major public hospitals of the city of Kozani. PHA is intended to demonstrate how a secure, networked, multipurpose electronic health and food benefits digital signage system can transform common TV sets inside patient homes or hospital rooms into health care media players and facilitate information sharing and improve administrative efficiency among private doctors, public health care providers, informal caregivers, and nutrition program private companies, while placing individual patients firmly in control of the information at hand. This case evaluation of the PHA demonstration is intended to provide critical information to other decision makers considering implementing PHA or related digital signage technology at other institutions and public hospitals around the globe.
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The previously described Nc5-specific PCR test for the diagnosis of Neospora caninum infections was used to develop a quantitative PCR assay which allows the determination of infection intensities within different experimental and diagnostic sample groups. The quantitative PCR was performed by using a dual fluorescent hybridization probe system and the LightCycler Instrument for online detection of amplified DNA. This assay was successfully applied for demonstrating the parasite proliferation kinetics in organotypic slice cultures of rat brain which were infected in vitro with N. caninum tachyzoites. This PCR-based method of parasite quantitation with organotypic brain tissue samples can be regarded as a novel ex vivo approach for exploring different aspects of cerebral N. caninum infection.
Resumo:
PURPOSE To evaluate the accuracy, safety, and efficacy of cervical nerve root injection therapy using magnetic resonance guidance in an open 1.0 T MRI system. METHODS Between September 2009 and April 2012, a total of 21 patients (9 men, 12 women; mean age 47.1 ± 11.1 years) underwent MR-guided cervical periradicular injection for cervical radicular pain in an open 1.0 T system. An interactive proton density-weighted turbo spin echo (PDw TSE) sequence was used for real-time guidance of the MR-compatible 20-gauge injection needle. Clinical outcome was evaluated on a verbal numeric rating scale (VNRS) before injection therapy (baseline) and at 1 week and 1, 3, and 6 months during follow-up. RESULTS All procedures were technically successful and there were no major complications. The mean preinterventional VNRS score was 7.42 and exhibited a statistically significant decrease (P < 0.001) at all follow-up time points: 3.86 ± 1.53 at 1 week, 3.21 ± 2.19 at 1 month, 2.58 ± 2.54 at 3 months, and 2.76 ± 2.63 at 6 months. At 6 months, 14.3 % of the patients reported complete resolution of radicular pain and 38.1 % each had either significant (4-8 VNRS score points) or mild (1-3 VNRS score points) relief of pain; 9.5 % experienced no pain relief. CONCLUSION Magnetic resonance fluoroscopy-guided periradicular cervical spine injection is an accurate, safe, and efficacious treatment option for patients with cervical radicular pain. The technique may be a promising alternative to fluoroscopy- or CT-guided injections of the cervical spine, especially in young patients and in patients requiring repeat injections.
Resumo:
Purpose: Selective retina therapy (SRT) has shown great promise compared to conventional retinal laser photocoagulation as it avoids collateral damage and selectively targets the retinal pigment epithelium (RPE). Its use, however, is challenging in terms of therapy monitoring and dosage because an immediate tissue reaction is not biomicroscopically discernibel. To overcome these limitations, real-time optical coherence tomography (OCT) might be useful to monitor retinal tissue during laser application. We have thus evaluated a proprietary OCT system for its capability of mapping optical changes introduced by SRT in retinal tissue. Methods: Freshly enucleated porcine eyes, covered in DMEM upon collection were utilized and a total of 175 scans from ex-vivo porcine eyes were analyzed. The porcine eyes were used as an ex-vivo model and results compared to two time-resolved OCT scans, recorded from a patient undergoing SRT treatment (SRT Vario, Medical Laser Center Lübeck). In addition to OCT, fluorescin angiography and fundus photography were performed on the patient and OCT scans were subsequently investigated for optical tissue changes linked to laser application. Results: Biomicroscopically invisible SRT lesions were detectable in OCT by changes in the RPE / Bruch's complex both in vivo and the porcine ex-vivo model. Laser application produced clearly visible optical effects such as hyperreflectivity and tissue distortion in the treated retina. Tissue effects were even discernible in time-resolved OCT imaging when no hyper-reflectivity persisted after treatment. Data from ex-vivo porcine eyes showed similar to identical optical changes while effects visible in OCT appeared to correlate with applied pulse energy, leading to an additional reflective layer when lesions became visible in indirect ophthalmoscopy. Conclusions: Our results support the hypothesis that real-time high-resolution OCT may be a promising modality to obtain additional information about the extent of tissue damage caused by SRT treatment. Data shows that our exvivo porcine model adequately reproduces the effects occurring in-vivo, and thus can be used to further investigate this promising imaging technique.
Resumo:
Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.
Resumo:
Service providers make use of cost-effective wireless solutions to identify, localize, and possibly track users using their carried MDs to support added services, such as geo-advertisement, security, and management. Indoor and outdoor hotspot areas play a significant role for such services. However, GPS does not work in many of these areas. To solve this problem, service providers leverage available indoor radio technologies, such as WiFi, GSM, and LTE, to identify and localize users. We focus our research on passive services provided by third parties, which are responsible for (i) data acquisition and (ii) processing, and network-based services, where (i) and (ii) are done inside the serving network. For better understanding of parameters that affect indoor localization, we investigate several factors that affect indoor signal propagation for both Bluetooth and WiFi technologies. For GSM-based passive services, we developed first a data acquisition module: a GSM receiver that can overhear GSM uplink messages transmitted by MDs while being invisible. A set of optimizations were made for the receiver components to support wideband capturing of the GSM spectrum while operating in real-time. Processing the wide-spectrum of the GSM is possible using a proposed distributed processing approach over an IP network. Then, to overcome the lack of information about tracked devices’ radio settings, we developed two novel localization algorithms that rely on proximity-based solutions to estimate in real environments devices’ locations. Given the challenging indoor environment on radio signals, such as NLOS reception and multipath propagation, we developed an original algorithm to detect and remove contaminated radio signals before being fed to the localization algorithm. To improve the localization algorithm, we extended our work with a hybrid based approach that uses both WiFi and GSM interfaces to localize users. For network-based services, we used a software implementation of a LTE base station to develop our algorithms, which characterize the indoor environment before applying the localization algorithm. Experiments were conducted without any special hardware, any prior knowledge of the indoor layout or any offline calibration of the system.
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In this paper we present an adaptive multi-camera system for real time object detection able to efficiently adjust the computational requirements of video processing blocks to the available processing power and the activity of the scene. The system is based on a two level adaptation strategy that works at local and at global level. Object detection is based on a Gaussian mixtures model background subtraction algorithm. Results show that the system can efficiently adapt the algorithm parameters without a significant loss in the detection accuracy.
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This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving
Resumo:
The purpose of this work is twofold: first, to develop a process to automatically create parametric models of the aorta that can adapt to any possible intraoperative deformation of the vessel. Second, it intends to provide the tools needed to perform this deformation in real time, by means of a non-rigid registration method. This dynamically deformable model will later be used in a VR-based surgery guidance system for aortic catheterism procedures, showing the vessel changes in real time.
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SSR es el acrónimo de SoundScape Renderer (tool for real-time spatial audio reproduction providing a variety of rendering algorithms), es un programa escrito en su mayoría en C++. El programa permite al usuario escuchar tanto sonidos grabados con anterioridad como sonidos en directo. El sonido o los sonidos se oirán, desde el punto de vista del oyente, como si el sonido se produjese en el punto que el programa decida, lo interesante de este proyecto es que el sonido podrá cambiar de lugar, moverse, etc. Todo en tiempo real. Esto se consigue sin modificar el sonido al grabarlo pero sí al emitirlo, el programa calcula las variaciones necesarias para que al emitir el sonido al oyente le llegue como si el sonido realmente se generase en un punto del espacio o lo más parecido posible. La sensación de movimiento no deja de ser el punto anterior cambiando de lugar. La idea era crear una aplicación web basada en Canvas de HTML5 que se comunicará con esta interfaz de usuario remota. Así se solucionarían todos los problemas de compatibilidad ya que cualquier dispositivo con posibilidad de visualizar páginas web podría correr una aplicación basada en estándares web, por ejemplo un sistema con Windows o un móvil con navegador. El protocolo debía de ser WebSocket porque es un protocolo HTML5 y ofrece las “garantías” de latencia que una aplicación con necesidades de información en tiempo real requiere. Nos permite una comunicación full-dúplex asíncrona sin mucho payload que es justo lo que se venía a evitar al no usar polling normal de HTML. El problema que surgió fue que la interfaz de usuario de red que tenía el programa no era compatible con WebSocket debido a un handshacking inicial y obligatorio que realiza el protocolo, por lo que se necesitaba otra interfaz de red. Se decidió entonces cambiar a JSON como formato para el intercambio de mensajes. Al final el proyecto comprende no sólo la aplicación web basada en Canvas sino también un servidor funcional y la definición de una nueva interfaz de usuario de red con su protocolo añadido. ABSTRACT. This project aims to become a part of the SSR tool to extend its capabilities in the field of the access. SSR is an acronym for SoundScape Renderer, is a program mostly written in C++ that allows you to hear already recorded or live sound with a variety of sound equipment as if the sound came from a desired place in the space. Like the web-page of the SSR says surely better explained: “The SoundScape Renderer (SSR) is a tool for real-time spatial audio reproduction providing a variety of rendering algorithms.” The application can be used with a graphical interface written in Qt but has also a network interface for external applications to use it. This network interface communicates using XML messages. A good example of it is the Android client. This Android client is already working. In order to use the application should be run it by loading an audio source and the wanted environment so that the renderer knows what to do. In that moment the server binds and anyone can use the network interface. Since the network interface is documented everyone can make an application to interact with this network interface. So the application can have as many user interfaces as wanted. The part that is developed in this project has nothing to do neither with audio rendering nor even with the reproduction of the spatial audio. The part that is developed here is about the interface used in the SSR application. As it can be deduced from the title: “Distributed Web Interface for Real-Time Spatial Audio Reproduction System”, this work aims only to offer the interface via web for the SSR (“Real-Time Spatial Audio Reproduction System”). The idea is not to make a new graphical interface for SSR but to allow more types of interfaces and communication. To accomplish the objective of allowing more graphical interfaces this project is going to use a new network interface. By now the SSR application is using only XML for data interchange but this new network interface support JSON. This project comprehends the server that launch the application, the user interface and the new network interface. It is done with these modules in order to allow creating new user interfaces that can communicate with the server or new servers that can communicate with the user interface by defining a complete network interface for data interchange.