Lookup-Table-Based Background Linearization for VCO-Based ADCs

Scaling of CMOS to nanometer dimensions has enabled dramatic improvement in digital power efficiency, with lower VDD supply voltage and decreased power consumption for logic functions. However, most traditionally prevalent ADC architectures are not well suited to the lower VDD environment. The improvement in time resolution enabled by increased digital speeds naturally drives design toward time-domain architectures such as voltage-controlled-oscillator (VCO) based ADCs. The major obstacle in the VCO-based technique is linearizing the VCO voltage-to-frequency characteristic. Achieving signal-to-noise (SNR) performance better than -40dB requires some form of calibration, which can be realized by analog or digital techniques, or some combination. A further challenge is implementing calibration without degrading energy efficiency performance. This thesis project discusses a complete design of a 10 bit three stage ring VCO-based ADC. A lookup-table (LUT) digital correction technique enabled by the Split ADC calibration approach is presented suitable for linearization of the ADC. An improvement in the calibration algorithm is introduced to ensure LUT continuity. Measured results for a 10 bit 48.8-kSps ADC show INL improvement of 10X after calibration convergence

Gabor Filter Initialization And Parameterization Strategies In Convolutional Neural Networks

Convolutional neural networks (CNN) have been widely known in literature to be extremely effective for classifying images. Some of the filters learned during training of the first layer of a CNN resemble the Gabor filter. Gabor filters are extremely good at extracting features within an image. We have taken this as an incentive by replacing the first layer of a CNN with the Gabor filter to increase speed and accuracy for classifying images. We created two simple 5-layer AlexNet-like CNNs comparing grid-search to random-search for initializing the Gabor filter bank. We trained on MNIST, CIFAR-10, and CIFAR-100 as well as a rock dataset created at Western University to study the classification of rock images using a CNN. When training on this rock dataset, we use an architecture from literature and use our Gabor filter substitution method to show the usage of the Gabor filter. Using the Gabor convolutional neural network (GCNN) showed improvements in the training speed across all datasets tested. We also found that the GCNN underperforms when dropout is added, even when overfitting becomes an issue. The size of the Gabor filter bank becomes a hyperparameter that can be tuned per dataset. Applying our Gabor filter replacement method to a 3-layer CNN reduced final accuracy at epoch 200 by 1:16% but showed large improvements in the speed of convergence during training with 93:44% accuracy on a validation set after 10 epochs compared to the original network’s 82:19%

Joint Source-Channel Coding for Image Transmission over Underlay Multichannel Cognitive Radio Networks

The increasing prominence of wireless applications exacerbates the problem of radio spectrum scarcity and promotes the usage of Cognitive Radio (CR) in wireless networks. With underlay dynamic spectrum access, CRs can operate alongside Primary Users, the incumbent of a spectrum band, as long as they limit the interference to the Primary Users below a certain threshold. Multimedia streaming transmissions face stringent Quality of Services constraints on top of the CR interference constraints, as some packets in the data stream have higher levels of importance and are the most vulnerable to packet loss over the channel. This raises a need for Unequal Error Protection (ULP) for multimedia streams transmissions, in which the channel encoder assigns different amount of error correction to different parts of the data stream, thereby protecting more the most valuable parts of the stream from packet loss problems. This research presents an end-to-end system setup for image transmission, utilizing ULP as part of a Joint Source-Channel Coding scheme over a multichannel CR network operating through underlay dynamic spectrum access. The setup features a Set Partitioning in Hierarchical Trees (SPIHT) source encoder, and Reed-Solomon forward error correction channel coding, and uses their properties to devise an ULP framework that maximizes the quality of the received image

The cooperative effects of channel length-bias, width asymmetry, gradient steepness, and contact-guidance on fibroblasts’ directional decision making

Cell migration in complex micro-environments, that are similar to tissue pores, is important for predicting locations of tissue nucleation and optimizing scaffold architectures. Firstly, how fibroblast cells - relevant to tissue engineering, affect each other’s directional decisions when encountered with a bifurcation of different channel lengths was investigated. It was found that cell sequence and cell mitosis influence the directional choices that the cells made while chemotaxing. Specifically, the fibroblasts chose to alternate between two possible paths - one longer and the other shorter - at a bifurcation. This finding was counter-intuitive given that the shorter path had a steeper chemoattractant gradient, and would thus be expected to be the preferred path, according to classical chemotaxis theory. Hence, a multiscale image-based modeling was performed in order to explain this behavior. It showed that consumption of the chemotactic signals by the neighboring cells led to the sequence-dependent directional decisions. Furthermore, it was also found that cellular division led to daughter cells making opposite directional choices from each other; even it meant that one of the daughter cells had to move against the chemotactic gradient, and overcome oncoming traffic of other cells. Secondly, a comparison of the effects of the various directional cues on the migration of individual fibroblast cells: including the chemoattractant concentration gradient, the channel width, and the contact-guidance was provided. Simple bifurcated mazes with two branches of different widths were created and fibroblasts were allowed to travel across these geometries by introducing a gradient of PDGF-BB at the ‘exit’ of the device. By incorporating image-based modeling methodology into the experimental approach, an insight into (i) how individual cells make directional decisions in the presence of complex migration cues and (ii) how the cell-cell interaction influences it was provided. It was found that a larger width ratio between the two bifurcated branches outdoes a gradient difference in attracting the cells. Also, when cells encounter a symmetric bifurcation (i.e., no difference between the branch widths), the gradient is predominant in deciding which path the cell will take. Then, in a symmetrical gradient field (i.e., inside a bifurcation of similar branch widths, and in the absence of any leading cells), the contact guidance is important for guiding the cells in making directional choices. Finally, these directional cues were ranked according to the order from the most importance to the least: vast gradient difference between the two branches, channel width bias, mild gradient difference, and contact-guidance

GIS-based modelling of agrochemical use, distribution and accumulation in the Lower Mekong Delta, Vietnam: A case study of the risk to aquaculture

In recent years, the Mekong delta has been strongly developed both for agriculture and aquaculture. However, there is scope for a negative impact of agriculture on aquaculture in term of production and quality of seafood products. Specifically, the large amount of pesticides imported and used in the Mekong delta not only help agriculture purposes but can also easily enter aquatic systems and affect aquaculture. Pesticides can be transported in the environment by chemo-dynamic procedures and hydrological processes. As a result, pesticides used in agriculture become dispersed and their residues in sediment, water and biota have been detected in the Mekong delta. This study investigated the overall pesticide process including pesticide use, modelling pesticide accumulation and evaluating the potential impact on aquaculture sites for some target aquatic species. The risk of pesticides use in the Mekong delta was addressed in three stages: (1) investigating current pesticide use status in the Mekong delta; (2) modelling pesticide loss and accumulation; (3) classifying pesticide risk areas for aquaculture of target cultured species. A survey of 334 farms covering a total area of ~20,000km2 in the Mekong delta took place between 2008 and 2009. Information on pesticide types and quantities was recorded using questionnaires, and it was found that 96 pesticides in 23 groups were popularly used for agricultural purposes. Dicarboximide, Carbamate and Conazole had the highest use at ~3000, ~2000 and ~2000 g/ha/year respectively. The survey revealed an increase in pesticide use per hectare since previous surveys in the Mekong delta in 1994, 2000, and 2004. However, the highly persistent compounds (WHO classification classes II, III and IV) appeared to have reduced in use. Insecticides previously represented >50% of the total pesticides used, however, the resent survey has shown their use has decreased to ~38%.There was a parallel increase in use of fungicides from previous levels of <30% of total pesticides to more recently ~41%. The combination of pesticide information and geo-location data enabled display and analysis of this data spatially using a Geographic Information System (GIS). A pesticide loss and accumulation model was established through combination of several sub-models including sediment loss and accumulation, direct loss, and water runoff, all of which were implemented and integrated within the GIS environment. MUSLE (Modified Universal Soil Loss Equation) was used to estimate sediment loss and accumulation in the Mekong delta and the Curve Number method (CN Method) was applied to predict water runoff and discharges and flow accumulation. Modelling commenced from the first pesticide application in April, based on 4 day time-steps. All mathematical calculations run within each time step automatically reiterated in the following time step with the new input datasets. The results from fuzzy classification of the pesticide model outcomes were considered in terms of the 96hr lethal concentration (LC50) in order to classify the risk and non-risk areas for catfish and tiger shrimp culture. The sediment loss and accumulation model shows that the highest loss of sediment was in the rainy season, especially in May to October. Vegetables and short term crop areas were found be most strongly eroded. The MUSLE model showed that the highest sediment accumulation was in the hilly areas (~1066.42 tonne/ha/year); lower in riverside areas (~230.39 tonne/ha/year) and lowest in flooded paddy areas (~150.15tonne/ha/year). Abamectin was used as an example throughout this study to estimate pesticide loss and its effects on aquaculture. The results showed that pesticide loss by runoff and sediment loss is less than the loss by half-life degradation (for Abamectin specifically). Accumulation of Abamectin occurred at highest rate in May and October and decreased with time. The spatial models showed that pesticide residues concentrated in the river and riverside areas. In order to evaluate the acute toxicity impacts, three levels of water depth in ponds were modelled as culture depths for catfish and tiger shrimp. The results show that the highest risk areas for catfish occurred in May and October with ~333,000 and ~420,000 ha at a pond depth of 0.5 m; ~136,000 and ~183,000 ha at a pond depth of 1.0 m; and ~10,840 and ~19,000 ha at a pond depth of 1.5 m. Risk areas for catfish mainly concentrated at the riverside and in part of the coastal areas. For tiger shrimp, the risk periods during the year were similar to those found for catfish. The highest risk areas for shrimp were ~648,000 and ~771,000 ha at 0.5 m pond depth; ~346,000 and ~446,700 ha at 1.0 m pond depth; and ~185,000 and ~250,000 ha at 1.5 m pond depth. Overall, deeper ponds reduced the risk. This study has developed a method to evaluate the negative impact of input pesticides to the environment from agricultural use related to fluctuation of aquaculture risk areas. The research indicates the potential relationship between pesticide input and the risk areas for aquaculture. The model has several significant uses: 1) it can provide information to policy makers for a more harmonized development of both aquaculture and agriculture in the Mekong delta in the future, 2) it provides data for aquaculture investment analysis to decrease the hazards caused by pesticide impacts, and 3) it provides a model capable of application to wide field scenarios and suitable for any pesticide type

SOME SOLUTIONS TO DEVELOP TOURISM HUMAN RESOURCES FOR ENTERPRISES IN HAI PHONG CITY, VIETNAM

The article focuses on analyzing some solutions to promote the development of tourism human resources of enterprises in Hai Phong city. Those are solutions on strengthening the state management for tourism human resource development for enterprises; improving the effectiveness of training, fostering human resource, and building a specific mechanism to attract tourism human resources for enterprises. Article visualizations