Philips

About: Philips is a company organization based out in Vantaa, Finland. It is known for research contribution in the topics: Signal & Layer (electronics). The organization has 68260 authors who have published 99663 publications receiving 1882329 citations. The organization is also known as: Koninklijke Philips Electronics N.V. & Royal Philips Electronics.

Issues in integrating cellular networks WLANs, AND MANETs: a futuristic heterogeneous wireless network

Abstract: The popularity of wireless communication systems can be seen almost everywhere in the form of cellular networks, WLANs, and WPANs. In addition, small portable devices have been increasingly equipped with multiple communication interfaces building a heterogeneous environment in terms of access technologies. The desired ubiquitous computing environment of the future has to exploit this multitude of connectivity alternatives resulting from diverse wireless communication systems and different access technologies to provide useful services with guaranteed quality to users. Many new applications require a ubiquitous computing environment capable of accessing information from different portable devices at any time and everywhere. This has motivated researchers to integrate various wireless platforms such as cellular networks, WLANs, and MANETs. Integration of different technologies with different capabilities and functionalities is an extremely complex task and involves issues at all layers of the protocol stack. This article envisions an architecture for state-of-the-art heterogeneous multihop networks, and identifies research issues that need to be addressed for successful integration of heterogeneous technologies for the next generation of wireless and mobile networks.

Vehicle location system

Abstract: Signals from a number of NAVSTAR global positioning system (GPS) satellites (11,12,13,14) are received by a receiver (16) in a vehicle (15) and a segment of the signals is stored in a memory (18) prior to retransmission by a transmitter (19). A base station (35) receives these transmissions from the mobile unit using a first receiver (36). The base station also receives signals directly from the NAVSTAR GPS satellites using a second receiver (38). A control and calculating apparatus (37) within the base station can determine the ephemeris (course) information for the satellites and can measure the transmission times or propagation delays of signals between the satellites and the vehicle and with this information the control and calculating apparatus can calculate the position of the vehicle unit.

Automatic, three-segment, MR-based attenuation correction for whole-body PET/MR data.

Abstract: The combination of positron emission tomography (PET) and magnetic resonance (MR) tomography in a single device is anticipated to be the next step following PET/CT for future molecular imaging application. Compared to CT, the main advantages of MR are versatile soft tissue contrast and its capability to acquire functional information without ionizing radiation. However, MR is not capable of measuring a physical quantity that would allow a direct derivation of the attenuation values for high-energy photons. To overcome this problem, we propose a fully automated approach that uses a dedicated T1-weighted MR sequence in combination with a customized image processing technique to derive attenuation maps for whole-body PET. The algorithm automatically identifies the outer contour of the body and the lungs using region-growing techniques in combination with an intensity analysis for automatic threshold estimation. No user interaction is required to generate the attenuation map. The accuracy of the proposed MR-based attenuation correction (AC) approach was evaluated in a clinical study using whole-body PET/CT and MR images of the same patients (n = 15). The segmentation of the body and lung contour (L-R directions) was evaluated via a four-point scale in comparison to the original MR image (mean values >3.8). PET images were reconstructed using elastically registered MR-based and CT-based (segmented and non-segmented) attenuation maps. The MR-based AC showed similar behaviour as CT-based AC and similar accuracy as offered by segmented CT-based AC. Standardized uptake value (SUV) comparisons with reference to CT-based AC using predefined attenuation coefficients showed the largest difference for bone lesions (mean value ± standard variation of SUVmax: −3.0% ± 3.9% for MR; −6.5% ± 4.1% for segmented CT). A blind comparison of PET images corrected with segmented MR-based, CT-based and segmented CT-based AC afforded identical lesion detectability, but slight differences in image quality were found. Our MR‐based attenuation correction method offers similar correction accuracy as offered by segmented CT. According to the specialists involved in the blind study, these differences do not affect the diagnostic value of the PET images.