Analysis and Optimization of Synthetic Aperture Ultrasound Imaging Using the Effective Aperture Approach

An effective aperture approach is used as a tool for analysis and parameter optimization of mostly known ultrasound imaging systems - phased array systems, compounding systems and synthetic aperture imaging systems. Both characteristics of an imaging system, the effective aperture function and the corresponding two-way radiation pattern, provide information about two of the most important parameters of images produced by an ultrasound system - lateral resolution and contrast. Therefore, in the design, optimization of the effective aperture function leads to optimal choice of such parameters of an imaging systems that influence on lateral resolution and contrast of images produced by this imaging system. It is shown that the effective aperture approach can be used for optimization of a sparse synthetic transmit aperture (STA) imaging system. A new two-stage algorithm is proposed for optimization of both the positions of the transmitted elements and the weights of the receive elements. The proposed system employs a 64-element array with only four active elements used during transmit. The numerical results show that Hamming apodization gives the best compromise between the contrast of images and the lateral resolution

Diagnostic System for Asynchronous Motors and Synchronous Generators Operating in Autonomous Mode Developed through the Use of DAQ Devices and Labview Programming Environment

The paper explores the possibilities for the use of DAQ devices in developing specialised diagnostic systems for monitoring and diagnostics of electrical equipment with asynchronous electric drives and autonomous synchronous generators. The primary focus is on the construction of a system responsive to different complementary diagnostic methods, such as the spectral current- voltage analysis, Park's method, instantaneous power theories, etc. Such a system might be applied locally (discretely) and/or conjointly in a centralized equipment monitoring system with the use of the LabView platform

Malaria elimination campaigns in the Lake Kariba region of Zambia: a spatial dynamical model

Background As more regions approach malaria elimination, understanding how different interventions interact to reduce transmission becomes critical. The Lake Kariba area of Southern Province, Zambia, is part of a multi-country elimination effort and presents a particular challenge as it is an interconnected region of variable transmission intensities. Methods In 2012-13, six rounds of mass-screen-and-treat drug campaigns were carried out in the Lake Kariba region. A spatial dynamical model of malaria transmission in the Lake Kariba area, with transmission and climate modeled at the village scale, was calibrated to the 2012-13 prevalence survey data, with case management rates, insecticide-treated net usage, and drug campaign coverage informed by surveillance. The model was used to simulate the effect of various interventions implemented in 2014-22 on reducing regional transmission, achieving elimination by 2022, and maintaining elimination through 2028. Findings The model captured the spatio-temporal trends of decline and rebound in malaria prevalence in 2012-13 at the village scale. Simulations predicted that elimination required repeated mass drug administrations coupled with simultaneous increase in net usage. Drug campaigns targeted only at high-burden areas were as successful as campaigns covering the entire region. Interpretation Elimination in the Lake Kariba region is possible through coordinating mass drug campaigns with high-coverage vector control. Targeting regional hotspots is a viable alternative to global campaigns when human migration within an interconnected area is responsible for maintaining transmission in low-burden areas

Optimal Topologies And Algorithms For Minimizing Data Retransmissions In Wireless Networks

Wireless networks comprise the majority of devices within the growing edge of the global communication system. Performance metrics determining the successful application of wireless networks in that setting are goodput, latency and network lifetime. Overhead retransmissions due to redundant data transfer, inefficient transmissions, low link quality, and suboptimal network layer protocols affect negatively these three metrics. Designing wireless networks to minimize the overhead retransmissions encompasses three network levels: the data, structural and procedural levels. Encoded sensing (ES) is a "data-aware" scheme that shapes the network structural level to account for correlations across data sources and common data across groups of nodes. Via new encoding algorithms, ES achieves substantial reduction of the transmissions required to convey a message to a sink node. A few beneficial properties for network hardware and design, based on sparsity of ES signals, are also discussed. The structural level is further augmented by the placement of relay nodes to minimize the overhead retransmissions in the network due to low quality and heavily loaded links. Finally, the Time Sequence Scheme operates on the network procedural level, allowing for broadcast of messages reaching all network nodes, while minimizing redundant broadcast retransmissions. Explicitly minimizing the number of retransmissions at each of the three network levels impacts beneficially performance as shown by analysis and full network stack simulations

Analysis and Optimization of Medical Ultrasound Imaging Using the Effective Aperture Approach

An effective aperture approach is used as a tool for analysis and parameter optimization of mostly known ultrasound imaging systems - phased array systems, compounding systems and synthetic aperture imaging systems. Both characteristics of an imaging system , the effective aperture function and the corresponding two-way radiation pattern, provide information about two the most important parameters of images produced by an ultrasound system - lateral resolution and contrast. Therefore, in the design, optimization of the effective aperture function leads to optimal choice of such parameters of an imaging systems that influence on lateral resolution and contrast of images produced by this imaging system. The numerical results show that Hamming apodization gives the best compromise between the contrast of images and the lateral resolution produced by a conventional phased array imaging system. In compound imaging, the number of transducers and its spatial separation should be chosen in result of optimization of the effective aperture function of a system. It is shown that the effective aperture approach can be also used for optimization of a sparse synthetic transmit aperture (STA) imaging system. A new two-stage algorithm is proposed for optimization of both the positions of the transmit elements and the weights of the receive elements. The proposed system employs a 64- element array with only four active elements used during transmit

Analysis of application-aware on-chip routing under traffic uncertainty

Application-aware routing exploits static knowledge of an applica-tion’s traffic pattern to improve performance compared to general-purpose routing algorithms. Unfortunately, traditional approaches to application-aware routing cannot efficiently handle dynamic changes in the traffic pattern limiting its usefulness in practice. In this paper, we study application-aware routing under traffic uncer-tainty. Our problem formulation allows an application to statically specify an uncertainty set of traffic patterns that each occur with a given probability, and our goal is to find a single set of combined routes that will enable high-performance across all of these traffic patterns. We show how efficient combined routes can be found for this problem using convex optimization. These combined routes are optimal when the performance for every traffic pattern using the combined routes is the same as the performance using routes that are specialized for just that traffic pattern. We derive necessary and sufficient conditions for when our optimization framework will find optimal combined routes. We use theoretical and numerical analysis for the important class of permutation traffic patterns to quantify how often optimal combined routes exist and to determine the performance loss when optimal combined routes are infeasi-ble. Finally, we use a cycle-level simulator that includes realistic pipeline latencies, arbitration, and buffered flow-control to study the latency and throughput of combined routes compared to spe-cialized routes and routes generated using general-purpose routing algorithms. The theoretical analysis, numerical analysis, and simu-lation results in this paper provide a first step towards more flexible application-aware routing