Analysis and Optimization Laminar Viscous Flow Through a Channel

Optimizing of laminar viscous flow through a pipe by two dimensionless values is investigated analytically. Dimensionless entropy generation and pumping power to heat transfer rate ratio are used as basis for constant viscous and the temperature dependence on the viscosity. For this matter we calculate entropy generation and pumping power for a fully developed in a pipe subjected to constant wall temperature for either constant viscosity and the variable viscosity. The variation entropy generation increase along the pipe length for viscous fluid is drawn, either the variation summation dimensionless entropy generation and the pumping power to heat transfer rate ratio are varying the fluid inlet temperature for fixed pipe length and are varying pipe length for fixed fluid inlet temperature are drawn. For low heat transfer conditions the entropy generation due to viscosity friction becomes dominant and the dependence of viscosity with the temperature becomes essentially important to be considered.     

Efficient indexing and retrieval of large-scale geo-tagged video databases

We are witnessing a significant growth in the number of smartphone users and advances in phone hardware and sensor technology. In conjunction with the popularity of video applications such as YouTube, an unprecedented number of user-generated videos (UGVs) are being generated and consumed by the public, which leads to a Big Data challenge in social media. In a very large video repository, it is difficult to index and search videos in their unstructured form. However, due to recent development, videos can be geo-tagged (e.g., locations from GPS receiver and viewing directions from digital compass) at the acquisition time, which can provide potential for efficient management of video data. Ideally, each video frame can be tagged by the spatial extent of its coverage area, termed Field-Of-View (FOV). This effectively converts a challenging video management problem into a spatial database problem. This paper attacks the challenges of large-scale video data management using spatial indexing and querying of FOVs, especially maximally harnessing the geographical properties of FOVs. Since FOVs are shaped similar to slices of pie and contain both location and orientation information, conventional spatial indexes, such as R-tree, cannot index them efficiently. The distribution of UGVs’ locations is non-uniform (e.g., more FOVs in popular locations). Consequently, even multilevel grid-based indexes, which can handle both location and orientation, have limitations in managing the skewed distribution. Additionally, since UGVs are usually captured in a casual way with diverse setups and movements, no a priori assumption can be made to condense them in an index structure. To overcome the challenges, we propose a class of new R-tree-based index structures that effectively harness FOVs’ camera locations, orientations and view-distances, in tandem, for both filtering and optimization. We also present novel search strategies and algorithms for efficient range and directional queries on our indexes. Our experiments using both real-world and large synthetic video datasets (over 30 years’ worth of videos) demonstrate the scalability and efficiency of our proposed indexes and search algorithms.     

Effect of polyaluminium chloride on phosphorus removal in constructed wetlands treated with swine wastewater

Total phosphorus (TP) removal in aged constructed wetlands poses a challenge, especially when treated with swine wastewater with high concentrations of phosphorus (P). Our earlier studies with anaerobic lagoon swine wastewater treatment in constructed wetlands showed a decline in P removal (45-22%) with increased years of operation. These particular wetlands have been treated with swine wastewater every year since the first application in 1997. Preliminary lab-scale studies were conducted to evaluate the efficiency of polyaluminium chloride (PAC) in the removal of phosphate-P (PO4-P) from swine wastewater. The experimental objective was to increase the phosphorus treatment efficiency in constructed wetland by adding PAC as a precipitating agent. PAC was added by continuous injection to each wetland system at a rate of 3 L day(-1) (1:5 dilution of concentrated PAC). Swine wastewater was added from an anaerobic lagoon to four constructed wetland cells (11m wide x 40m long) at TP loads of 5.4-6.1 kg ha(-1) day(-1) in two experimental periods, September to November of 2008 and 2009. Treatment efficiency of two wetland systems: marsh-pond-marsh (M-P-M) and continuous marsh (CM) was compared. The wetlands were planted with cattails (Typha latifolia L.) and bulrushes (Scirpus americanus). In 2008, PAC treatment showed an increase of 27.5 and 40.8% of TP removal over control in M-P-M and CM respectively. Similar trend was also observed in the following year. PAC as a flocculant and precipitating agent showed potential to enhance TP removal in constructed wetlands treated with swine wastewater.     

A hybrid aggregation and compression technique for road network databases

Vector data and in particular road networks are being queried, hosted and processed in many application domains such as in mobile computing. Many client systems such as PDAs would prefer to receive the query results in unrasterized format without introducing an overhead on overall system performance and result size. While several general vector data compression schemes have been studied by different communities, we propose a novel approach in vector data compression which is easily integrated within a geospatial query processing system. It uses line aggregation to reduce the number of relevant tuples and Huffman compression to achieve a multi-resolution compressed representation of a road network database. Our experiments performed on an end-to-end prototype verify that our approach exhibits fast query processing on both client and server sides as well as high compression ratio.

Processing Optimal Sequenced Route Queries Using Voronoi Diagrams

The Optimal Sequenced Route (OSR) query strives to find a route of minimum length starting from a given source location and passing through a number of typed locations in a specific sequence imposed on the types of the locations. In this paper, we propose a pre-computation approach to OSR query in both vector and metric spaces. We exploit the geometric properties of the solution space and theoretically prove its relation to additively weighted Voronoi diagrams. Our approach recursively accesses these diagrams to incrementally build the OSR. Introducing the analogous diagrams for the space of road networks, we show that our approach is also efficiently applicable to this metric space. Our experimental results verify that our pre-computation approach outperforms the previous index-based approaches in terms of query response time. This research has been funded in part by NSF grants EEC-9529152 (IMSC ERC), IIS-0238560 (PECASE), IIS-0324955 (ITR), IIS-0534761, and unrestricted cash gifts from Google and Microsoft. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the NSF.

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Super-Streaming: A New Object Delivery Paradigm for Continuous Media Servers

A number of studies have focused on the design of continuous media, CM, (e.g., video and audio) servers to support the real-time delivery of CM objects. These systems have been deployed in local environments such as hotels, hospitals and cruise ships to support media-on-demand applications. They typically stream CM objects to the clients with the objective of minimizing the buffer space required at the client site. This objective can now be relaxed due to the availability of inexpensive storage devices at the client side. Therefore, we propose a Super-streaming paradigm that can utilize the client side resources in order to improve the utilization of the CM server. To support super-streaming, we propose a technique to enable the CM servers to deliver CM objects at a rate higher than their display bandwidth requirement. We also propose alternative admission control policies to downgrade super-streams in favor of regular streams when the resources are scarce. We demonstrate the superiority of our paradigm over streaming with both analytical and simulation models.Moreover, new distributed applications such as distant-learning, digital libraries, and home entertainment require the delivery of CM objects to geographically disbursed clients. For quality purposes, recently many studies proposed dedicated distributed architectures to support these types of applications. We extend our super-streaming paradigm to be applicable in such distributed architectures. We propose a sophisticated resource management policy to support super-streaming in the presence of multiple servers, network links and clients. Due to the complexity involved in modeling these architectures, we only evaluate the performance of super-streaming by a simulation study.     

Coating Effects on Transient Cooling a Hot Spherical Body

A numerical solution is carried out to treat the transient cooling problem with conduction and radiation for a hot spherical body covered with a cold coating material. The solution includes the equations of radiative transfer, coupled with a transient energy equation that contains both radiative and conductive terms. The radiative transfer equation was solved by the discrete ordinates method, and a parmetric study was performed by changing various physical parameters such as the optical thicknesses, thermal conductivity of the coating, emissivity, and diffusivity of the sphere. It was found that the properties of the coating have a direct effect on the cooling rate of the sphere.     

Applying multiple decomposition methods and optimization techniques for achieving optimal cost in mixed materials heat exchanger networks

The optimization of the total annual cost in heat exchanger networks has been one of the overarching goals when synthesizing these networks. Several methodologies and techniques have been developed to achieve optimal costs in mixed material heat exchanger networks. This paper demonstrates the application of two decomposition methodologies (total decomposition and partial decomposition) for typical cost rules. The objective function was defined as the optimization and minimization of the total annual cost in mixed materials heat exchanger network. Three optimization algorithms, hybrid genetic‐particle swarm optimization (GA‐PSO), shuffled frog leaping algorithm (SFLA) techniques, and ant colony optimization (ACO), were used to further optimize the total cost in mixed materials heat exchanger network. The results indicate that the total annual cost in partial decomposition method was smaller than that in full integration method and total decomposition method. The reduction of the total annual cost was about 27% for GA‐PSO algorithm, 24% for SFLA and 10% for ACO relative to the results reported in this work. In partial decomposition method, at least one mixed material of heat exchanger was used to reduce the hot and cold utility for decreasing the total annual cost. Partial decomposition method resulted in the highest reduction of the total annual cost compared with other methods. Percentage of difference of the total annual cost were 0.36%, 1.92%, and 5.05% for full integration, total decomposition, and partial decomposition methods, respectively, in comparison with the previous studies. Results have been compared with the results of other studies to demonstrate the accuracy of the applied algorithms.     

A correlation-based approach to calculate rotation and translation of moving cells.

We present a noniterative image cross-correlation approach to track translation and rotation of crawling cells in time-lapse video microscopy sequences. The method does not rely on extracting features or moments, and therefore does not impose specific requirements on the type of microscopy used for imaging. Here we use phase-contrast images. We calculate cell rotation and translation from one image to the next in two stages. First, rotation is calculated by cross correlating the images' polar-transformed magnitude spectra (Fourier magnitudes). Rotation of the cell about any center in the original images results in translation in this representation. Then, we rotate the first image such that the cell has the same orientation in both images, and cross correlate this image with the second image to calculate translation. By calculating the rotation and translation over each interval in the movie, and thereby tracking the cell's position and orientation in each image, we can then map from the stationary reference frame in which the cell was observed to the cell's moving coordinate system. We describe our modifications enabling application to nonidentical images from video sequences of moving cells, and compare this method's performance with that of a feature extraction method and an iterative optimization method.     

Utilizing Voronoi Cells of Location Data Streams for Accurate Computation of Aggregate Functions in Sensor Networks

Sensor networks are unattended deeply distributed systems whose database schema can be conceptualized using the relational model. Aggregation queries on the data sampled at each sensor node are the main means to extract the abstract characteristics of the surrounding environment. However, the non-uniform distribution of the sensor nodes in the environment leads to inaccurate results generated by the aggregation queries. In this paper, we introduce “spatial aggregations” that take into consideration the spatial location of each measurement generated by the sensor nodes. We propose the use of spatial interpolation methods derived from the fields of spatial statistics and computational geometry to answer spatial aggregations. In particular, we study Spatial Moving Average (SMA), Voronoi Diagram and Triangulated Irregular Network (TIN). Investigating these methods for answering spatial average queries, we show that the average value on the data samples weighted by the area of the Voronoi cell of the corresponding sensor node, provides the best precision. Consequently, we introduce an algorithms to compute and maintain the accurate Voronoi cell at each sensor node while the location of the others arrive on data stream. We also propose AVC-SW, a novel algorithm to approximate this Voronoi cell over a sliding window that supports dynamism in the sensor network. To demonstrate the performance of in-network implementation of our aggregation operators, we have developed prototypes of two different approaches to distributed spatial aggregate processing. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. GIS'04, November 12–13, 2004, Washington DC, USA. Copyright 2004 ACM 1-58113-979-9/04/0011...$5.00.