SYSTEM-ON-A-CHIP (SOC)-BASED HARDWARE ACCELERATION FOR HUMAN ACTION RECOGNITION WITH CORE COMPONENTS

Today, the implementation of machine vision algorithms on embedded platforms or in portable systems is growing rapidly due to the demand for machine vision in daily human life. Among the applications of machine vision, human action and activity recognition has become an active research area, and market demand for providing integrated smart security systems is growing rapidly. Among the available approaches, embedded vision is in the top tier; however, current embedded platforms may not be able to fully exploit the potential performance of machine vision algorithms, especially in terms of low power consumption. Complex algorithms can impose immense computation and communication demands, especially action recognition algorithms, which require various stages of preprocessing, processing and machine learning blocks that need to operate concurrently. The market demands embedded platforms that operate with a power consumption of only a few watts. Attempts have been mad to improve the performance of traditional embedded approaches by adding more powerful processors; this solution may solve the computation problem but increases the power consumption. System-on-a-chip eld-programmable gate arrays (SoC-FPGAs) have emerged as a major architecture approach for improving power eciency while increasing computational performance. In a SoC-FPGA, an embedded processor and an FPGA serving as an accelerator are fabricated in the same die to simultaneously improve power consumption and performance. Still, current SoC-FPGA-based vision implementations either shy away from supporting complex and adaptive vision algorithms or operate at very limited resolutions due to the immense communication and computation demands. The aim of this research is to develop a SoC-based hardware acceleration workflow for the realization of advanced vision algorithms. Hardware acceleration can improve performance for highly complex mathematical calculations or repeated functions. The performance of a SoC system can thus be improved by using hardware acceleration method to accelerate the element that incurs the highest performance overhead. The outcome of this research could be used for the implementation of various vision algorithms, such as face recognition, object detection or object tracking, on embedded platforms. The contributions of SoC-based hardware acceleration for hardware-software codesign platforms include the following: (1) development of frameworks for complex human action recognition in both 2D and 3D; (2) realization of a framework with four main implemented IPs, namely, foreground and background subtraction (foreground probability), human detection, 2D/3D point-of-interest detection and feature extraction, and OS-ELM as a machine learning algorithm for action identication; (3) use of an FPGA-based hardware acceleration method to resolve system bottlenecks and improve system performance; and (4) measurement and analysis of system specications, such as the acceleration factor, power consumption, and resource utilization. Experimental results show that the proposed SoC-based hardware acceleration approach provides better performance in terms of the acceleration factor, resource utilization and power consumption among all recent works. In addition, a comparison of the accuracy of the framework that runs on the proposed embedded platform (SoCFPGA) with the accuracy of other PC-based frameworks shows that the proposed approach outperforms most other approaches

On Improving Generalization of CNN-Based Image Classification with Delineation Maps Using the CORF Push-Pull Inhibition Operator

Deployed image classification pipelines are typically dependent on the images captured in real-world environments. This means that images might be affected by different sources of perturbations (e.g. sensor noise in low-light environments). The main challenge arises by the fact that image quality directly impacts the reliability and consistency of classification tasks. This challenge has, hence, attracted wide interest within the computer vision communities. We propose a transformation step that attempts to enhance the generalization ability of CNN models in the presence of unseen noise in the test set. Concretely, the delineation maps of given images are determined using the CORF push-pull inhibition operator. Such an operation transforms an input image into a space that is more robust to noise before being processed by a CNN. We evaluated our approach on the Fashion MNIST data set with an AlexNet model. It turned out that the proposed CORF-augmented pipeline achieved comparable results on noise-free images to those of a conventional AlexNet classification model without CORF delineation maps, but it consistently achieved significantly superior performance on test images perturbed with different levels of Gaussian and uniform noise

Spatio-temporal landscape transformations in Southern Chile and its implications on ecosystem services supply and beneficiaries

Human-induced global change has driven drastic modifications of ecosystems that could lead to unexpected and unprecedented transformations in the present and future decades. Current systems modifications increased the need for more comprehensive and evenly distributed databases across ecosystems and spatio-temporal scales. Moreover, base knowledge that allows a better understanding of land-use trajectories and their impacts on the supply of multiple ecosystem services and thus supports the development of highly relevant guidelines for improving landscape management decisions. Hotspots of biodiversity are biogeographical areas identified as biodiversity reservoirs that have been recognized as under threat due to human impacts. These biodiversity reservoirs require further investigation to prevent the deterioration of their ecological functions. Hence, this dissertation aims to understand the impacts and effects of human activities in a biodiversity hotspot area, the Valdivian temperate rainforest by expanding the temporal resolution of land cover data and ecosystem services assessments. The Valdivian temperate rainforest is located in Southern Chile, Northern Chilean Patagonia (73°20’ W-39°25’ S - 71°59’ W-41° 14’ S). The area has been identified as a biodiversity hotspot due to a high number of endemic species (90% at the species level and 34% at the genus level for woody species), and its intense level of human appropriation. This dissertation addresses the following three objectives: 1) Uncovering landscape transformation by expanding the temporal resolution of analyses of landscape dynamics in a biodiversity hotspot area; 2) Understanding the spatio-temporal dynamics of the supply of multiple ecosystems services at the landscape scale; 3) Assessing the contribution of an integrated landscape management strategy to reconnect fragmented ecosystems, on ecosystem services supply and its beneficiaries. The integration of different types of biophysical and socioeconomic data, as well as methodologies from diverse fields such as remote sensing, ecological modeling, and landscape ecology, were included to answer the main questions of the dissertation. A higher temporal resolution of land-cover dynamics was investigated by using all Landsat scenes available for the study area from 1985 to 2011 (7 periods) and a spatial resolution of 30 meters. An automatic classification with random forest and local ground information allowed to uncover the dynamic of land-cover composition and configuration in the area. Based on this analysis and additional biophysical and socioeconomic data, the trajectory of the ecosystem services supply in the area was revealed at the same temporal scale (7 periods) but with a spatial differentiation between the main four geomorphological units. All these datasets and the methodological procedure of this thesis resulted in the development of landscape planning recommendations that were assessed in the final chapter of this dissertation. The assessed landscape planning strategy builds on the protection of structural connectivity areas (SCA) —defined as the integration of linear (riparian corridors) and patchy (national conservation units) landscape elements— and its contribution to ecosystem services supply as well as its beneficiaries across the landscape. Results from the land-cover dynamics analysis revealed a highly dynamic and transformed landscape influenced by processes such as clear-cuts of exotic forest plantations, regrowth of secondary forest, afforestation with exotic tree species, together with deforestation and fragmentation of native forest. These modifications impacted both the composition and configuration of the landscape. Areas with exotic forest plantation drastically increase especially from 1985 until 1999 with the highest net increase of 706% from 1985 until 2011. Old-growth forests showed a continuous decrease over time, with the highest deforestation rate of 1.2% - net loss - between 1985 and 1999, this deforestation rate tends to slow down in the last study period (2010-2011). Moreover, the fragmentation of old-growth forest rose especially between 1985-1999 with the decline of patch size and an increase of the total edge length. Secondary forest showed an increase over time but with small and fragmented patches across the landscape. In the case of the ecosystem services supply, the different geomorphological units revealed a diverse pattern with higher regulation services in the Andes and Coastal range in comparison with provisioning services mostly allocated in the Central Valley. The ecosystem services supply trajectory uncovered a decrease of carbon stocks in both mountain ranges as well as an increase in the Central Valley. Regulating services such as sediment and phosphorous retention showed irregular trends which reflected the diverse management strategies used in the area in addition to the low compliance of stream buffer protection, that highlighted the importance of protecting riparian areas. Cultural ecosystem services also declined, for example, the case of aesthetic value that decreased (degree of naturalness) over time and across the study area. In the case of recreational services, even though there is an increase in the service during the study period, these areas are isolated with low or limited access, and a low type of ecosystems represented. Concerning the recommended landscape planning strategy (SCA) assessed in the last chapter, the results reported a positive contribution —maintaining and enhancing— not only to ecosystem services supply but also to the conservation in the area. The assessment revealed the high potential of SCA as a conservation strategy by reconnecting this fragmented landscape and protecting vulnerable areas (riparian corridors); due to the high amount of services that they supply (more than 60%), with an also a higher density of beneficiaries, even when SCA only account for 40% of the total study area. The results of this dissertation confirm the relevance of integrated research by combining various techniques, disciplines and the consideration of different spatio-temporal scales to achieve better awareness of the functioning of socio-ecological systems by using the ecosystem services concept as a framework. Furthermore, the results highlight the necessity of an expanded temporal resolution in land-cover and ecosystem service assessments to provide more targeted and grounded recommendations for landscape planning

Design and Evaluation of a Novel Lens-Based SPECT System Based on Laue Lens Gamma Diffraction: GEANT4/GAMOS Monte Carlo Study

Abstract While improvements in SPECT imaging techniques constitute a significant advance in biomedical science and cancer diagnosis, their limited spatial resolution has hindered their application to small animal research and early tumour detection. Using recent breakthroughs established by the high-energy astrophysics community, focusing X-ray optics provides a method to overcome the paradigm of low resolution and presents the possibility of imaging small objects with sub-millimetre resolution. This thesis aims to tackle the constraints associated with the current SPECT imaging designs by exploiting the notion of focusing high energy photons through Laue lens diffraction and developing a means of performing gamma rays imaging that would not rely on parallel or pinhole collimators. The gradual development of the novel system is discussed, starting from the single, modular, and multi-Laue lens-based SPECT. A customized 3D reconstruction algorithm was developed to reconstruct an accurate 3D radioactivity distribution from focused projections. A plug-in implementing the Laue diffraction concept was developed and used to model gamma rays focusing in the GEANT4 toolkit. The plug-in will be incorporated into GEANT4 upon final approval from its developers. The single lens-based, modular lens-based and multi lens-based SPECT models detected one hit per 42 source photons (sensitivity of 790 ⁄), three hits per 42 source photons (sensitivity of 2,373 ⁄), and one hit per 20 source photons (sensitivity of 1,670 ⁄), respectively. Based on the generated 3D reconstructed images, the achievable spatial resolution was found to be 0.1 full width at half maximum (FWHM). The proposed design’s performance parameters were compared against the existing SIEMENS parallel LEHR and multi-pinhole (5-MWB-1.0) Inveon SPECT. The achievable spatial resolution is decoupled from the sensitivity of the system, which is in stark contrast with the existing collimators that suffer from the resolution-sensitivity trade-off and are limited to a resolution of 2 . The proposed system allows discrimination between adjacent volumes as small as 0.113 , which is substantially smaller than what can be imaged by any existing SPECT or PET system. The proposed design could lay the foundation for a new SPECT imaging technology akin to a combination of tomosynthesis and lightfield imaging

Irrigation district sustainability

Presented at Irrigation district sustainability - strategies to meet the challenges: USCID irrigation district specialty conference held on June 3-6, 2009 in Reno, Nevada.Fresno Irrigation District (FID) serves irrigation water to approximately 245,000 acres including the Cities of Fresno and Clovis, in California's Central San Joaquin Valley. As Clovis has developed they have looked for ways to diversify their water supply portfolio. Until recently, this mainly consisted of groundwater wells with some surface water supplies coming from FID. Clovis, in an effort to increase their dry year supplies, partnered with FID to develop the Waldron Banking Facilities. Through the agreement developed between Clovis and FID, Clovis provided half of the capital to develop the project in return for half of the project yield. Clovis also has the first right of refusal, on an annual basis, for any yield developed from the project. The Waldron Banking Facilities are comprised of three groundwater banking facilities located in the western portion of the District. In exchange for the banked supplies, FID then provides an equivalent amount of surface water to Clovis (in the eastern portion of FID). To develop a new water supply for the City and FID, during wet years and other times when surplus surface water supplies are available these supplies are routed to the groundwater recharge basins. In dry years, these banked supplies are then recovered from the aquifer, and delivered to FID growers. Two of the recharge basin sites were existing regulation basins, which were significantly expanded to add recharge capabilities. One of the sites is new, and placed at the bifurcation of one of FID's laterals. The recharge basin sites were strategically selected in order to provide an added benefit as regulation and storage basins that could be utilized during the irrigation season. The project was built over the course of three years, in phases. Now complete, the project includes approximately 250 acres of recharge basins, new measurement and control sites, seven recovery wells, and a network of monitoring wells. This paper will discuss the financial aspects of the project, project planning issues, design considerations, and how the twelve construction contracts were developed, managed and executed

Irrigation district sustainability

Presented at Irrigation district sustainability - strategies to meet the challenges: USCID irrigation district specialty conference held on June 3-6, 2009 in Reno, Nevada.The Yolo County Flood Control & Water Conservation District (District) releases about 250,000 acre-feet per year from two water supply reservoirs in the Cache Creek watershed for the irrigation of about 60,000 acres of farmland in Yolo County, California. That water is diverted into the Winters Canal and the West Adams Canal at Capay Diversion Dam on Cache Creek. The continued operation of Capay Dam is vital to the sustained future of irrigated agriculture of the District. Urbanization and infrastructure construction in California resulted in extensive sand and gravel extraction from Cache Creek downstream of Capay Dam. Although that mineral extraction ceased many years ago, the streambed of Cache Creek has degraded. Presently the streambed elevation at the toe of Capay Dam is as much as 15 feet below the elevation of the apron of the dam and the dam is at risk due to downstream channel bed degradation and local scour during floods. Capay Dam is a concrete diversion that was constructed in 1915. The main portion of the dam is an overflow section about 475 feet long with low-level sluice gates and service spillways at both abutments. The abutments also contain the headworks for the irrigation canals. Due to streambed degradation, local scour at the toe of the apron and the more than 90-year service life of the structure, the District embarked on a program of dam inspection, including the use of non destructive testing of the concrete, and rehabilitating the dam and headworks so as to continue to provide a sustainable irrigation supply of surface water from Cache Creek. The dam inspection and rehabilitation and betterment program for Capay Diversion Dam is presented. This includes the issues of environmental permitting, stream morphology, sediment transport and historic data collection