Sensors2014, 14(12), 22431-22446; doi:10.3390/s141222431 (registering DOI) - published 26 November 2014 Show/Hide Abstract
Abstract: A capacitance measurement system is developed for the measurement of gas-liquid two-phase flow in glass micro-pipes with inner diameters of 3.96, 2.65 and 1.56 mm, respectively. As a typical flow regime in a micro-pipe two-phase flow system, slug flow is chosen for this investigation. A capacitance sensor is designed and a high-resolution and high-speed capacitance measurement circuit is used to measure the small capacitance signals based on the differential sampling method. The performance and feasibility of the capacitance method are investigated and discussed. The capacitance signal is analyzed, which can reflect the voidage variation of two-phase flow. The gas slug velocity is determined through a cross-correlation technique using two identical capacitance sensors. The simulation and experimental results show that the presented capacitance measurement system is successful. Research work also verifies that the capacitance sensor is an effective method for the measurement of gas liquid two-phase flow parameters in micro-pipes.
Sensors2014, 14(12), 22408-22430; doi:10.3390/s141222408 (registering DOI) - published 26 November 2014 Show/Hide Abstract
Abstract: This paper presents a novel framework for the fusion of multi-focus images explicitly designed for visual sensor network (VSN) environments. Multi-scale based fusion methods can often obtain fused images with good visual effect. However, because of the defects of the fusion rules, it is almost impossible to completely avoid the loss of useful information in the thus obtained fused images. The proposed fusion scheme can be divided into two processes: initial fusion and final fusion. The initial fusion is based on a dual-tree complex wavelet transform (DTCWT). The Sum-Modified-Laplacian (SML)-based visual contrast and SML are employed to fuse the low- and high-frequency coefficients, respectively, and an initial composited image is obtained. In the final fusion process, the image block residuals technique and consistency verification are used to detect the focusing areas and then a decision map is obtained. The map is used to guide how to achieve the final fused image. The performance of the proposed method was extensively tested on a number of multi-focus images, including no-referenced images, referenced images, and images with different noise levels. The experimental results clearly indicate that the proposed method outperformed various state-of-the-art fusion methods, in terms of both subjective and objective evaluations, and is more suitable for VSNs.
Sensors2014, 14(12), 22394-22407; doi:10.3390/s141222394 (registering DOI) - published 26 November 2014 Show/Hide Abstract
Abstract: In this study we explored the positional quality of orthophotos obtained by an unmanned aerial vehicle (UAV). A multi-rotor UAV was used to obtain images using a vertically mounted digital camera. The flight was processed taking into account the photogrammetry workflow: perform the aerial triangulation, generate a digital surface model, orthorectify individual images and finally obtain a mosaic image or final orthophoto. The UAV orthophotos were assessed with various spatial quality tests used by national mapping agencies (NMAs). Results showed that the orthophotos satisfactorily passed the spatial quality tests and are therefore a useful tool for NMAs in their production flowchart.
Sensors2014, 14(12), 22372-22393; doi:10.3390/s141222372 - published 25 November 2014 Show/Hide Abstract
Abstract: This paper presents the generic concept of using cloud-based intelligent car parking services in smart cities as an important application of the Internet of Things (IoT) paradigm. This type of services will become an integral part of a generic IoT operational platform for smart cities due to its pure business-oriented features. A high-level view of the proposed middleware is outlined and the corresponding operational platform is illustrated. To demonstrate the provision of car parking services, based on the proposed middleware, a cloud-based intelligent car parking system for use within a university campus is described along with details of its design, implementation, and operation. A number of software solutions, including Kafka/Storm/Hbase clusters, OSGi web applications with distributed NoSQL, a rule engine, and mobile applications, are proposed to provide ‘best’ car parking service experience to mobile users, following the Always Best Connected and best Served (ABC&S) paradigm.
Sensors2014, 14(12), 22342-22371; doi:10.3390/s141222342 - published 25 November 2014 Show/Hide Abstract
Abstract: Geographic routing is one of the most investigated themes by researchers for reliable and efficient dissemination of information in Vehicular Ad Hoc Networks (VANETs). Recently, different Geographic Distance Routing (GEDIR) protocols have been suggested in the literature. These protocols focus on reducing the forwarding region towards destination to select the Next Hop Vehicles (NHV). Most of these protocols suffer from the problem of elevated one-hop link disconnection, high end-to-end delay and low throughput even at normal vehicle speed in high vehicle density environment. This paper proposes a Geographic Distance Routing protocol based on Segment vehicle, Link quality and Degree of connectivity (SLD-GEDIR). The protocol selects a reliable NHV using the criteria segment vehicles, one-hop link quality and degree of connectivity. The proposed protocol has been simulated in NS-2 and its performance has been compared with the state-of-the-art protocols: P-GEDIR, J-GEDIR and V-GEDIR. The empirical results clearly reveal that SLD-GEDIR has lower link disconnection and end-to-end delay, and higher throughput as compared to the state-of-the-art protocols. It should be noted that the performance of the proposed protocol is preserved irrespective of vehicle density and speed.
Sensors2014, 14(12), 22313-22341; doi:10.3390/s141222313 - published 25 November 2014 Show/Hide Abstract
Abstract: This review investigates optical sensor platforms for protein multiplexing, the ability to analyze multiple analytes simultaneously. Multiplexing is becoming increasingly important for clinical needs because disease and therapeutic response often involve the interplay between a variety of complex biological networks encompassing multiple, rather than single, proteins. Multiplexing is generally achieved through one of two routes, either through spatial separation on a surface (different wells or spots) or with the use of unique identifiers/labels (such as spectral separation—different colored dyes, or unique beads—size or color). The strengths and weaknesses of conventional platforms such as immunoassays and new platforms involving protein arrays and lab-on-a-chip technology, including commercially-available devices, are discussed. Three major public health concerns are identified whereby detecting medically-relevant markers using Point-of-Care (POC) multiplex assays could potentially allow for a more efficient diagnosis and treatment of diseases.