Energy efficiency analysis of rank-1 Ricean fading MIMO channels

This paper studies the energy efficiency (EE) of a point-to-point rank-1 Ricean fading multiple-input-multiple-output (MIMO) channel. In particular, a tight lower bound and an asymptotic approximation for the EE of the considered MIMO system are presented, under the assumption that the channel is unknown at the transmitter and perfectly known at the receiver. Moreover, the effects of different system parameters, namely, transmit power, spectral efficiency (SE), and number of transmit and receive antennas, on the EE are analytically investigated. An important observation is that, in the high signal-to-noise ratio regime and with the other system parameters fixed, the optimal transmit power that maximizes the EE increases as the Ricean-K factor increases. On the contrary, the optimal SE and the optimal number of transmit antennas decrease as K increases.

Massive MIMO in sparse channels

Massive multi-user multiple-input multiple-output (MU-MIMO) systems are cellular networks where the base stations (BSs) are equipped with hundreds of antennas, N, and communicate with tens of mobile stations (MSs), K, such that, N ≫ K ≫ 1. Contrary to most prior works, in this paper, we consider the uplink of a single-cell massive MIMO system operating in sparse channels with limited scattering. This case is of particular importance in most propagation scenarios, where the prevalent Rayleigh fading assumption becomes idealistic. We derive analytical approximations for the achievable rates of maximum-ratio combining (MRC) and zero-forcing (ZF) receivers. Furthermore, we study the asymptotic behavior of the achievable rates for both MRC and ZF receivers, when N and K go to infinity under the condition that N/K → c ≥ 1. Our results indicate that the achievable rate of MRC receivers reaches an asymptotic saturation limit, whereas the achievable rate of ZF receivers grows logarithmically with the number of MSs.

Circuit-aware design of energy-efficient massive MIMO systems

Densification is a key to greater throughput in cellular networks. The full potential of coordinated multipoint (CoMP) can be realized by massive multiple-input multiple-output (MIMO) systems, where each base station (BS) has very many antennas. However, the improved throughput comes at the price of more infrastructure; hardware cost and circuit power consumption scale linearly/affinely with the number of antennas. In this paper, we show that one can make the circuit power increase with only the square root of the number of antennas by circuit-aware system design. To this end, we derive achievable user rates for a system model with hardware imperfections and show how the level of imperfections can be gradually increased while maintaining high throughput. The connection between this scaling law and the circuit power consumption is established for different circuits at the BS.

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

Risque de prix et décisions de production et d'exportation : le cas de l'agriculture au Québec

Cette thèse porte sur l’effet du risque de prix sur la décision des agriculteurs et les transformateurs québécois. Elle se divise en trois chapitres. Le premier chapitre revient sur la littérature. Le deuxième chapitre examine l’effet du risque de prix sur la production de trois produits, à savoir le maïs grain, la viande de porc et la viande d’agneau dans la province Québec. Le dernier chapitre est centré sur l’analyse de changement des préférences du transformateur québécois de porc pour ce qui est du choix de marché. Le premier chapitre vise à montrer l’importance de l’effet du risque du prix sur la quantité produite par les agriculteurs, tel que mis en évidence par la littérature. En effet, la littérature révèle l’importance du risque de prix à l’exportation sur le commerce international. Le deuxième chapitre est consacré à l’étude des facteurs du risque (les anticipations des prix et la volatilité des prix) dans la fonction de l’offre. Un modèle d’hétéroscédasticité conditionnelle autorégressive généralisée (GARCH) est utilisé afin de modéliser ces facteurs du risque. Les paramètres du modèle sont estimés par la méthode de l’Information Complète Maximum Vraisemblance (FIML). Les résultats empiriques montrent l’effet négatif de la volatilité du prix sur la production alors que la prévisibilité des prix a un effet positif sur la quantité produite. Comme attendu, nous constatons que l’application du programme d’assurance-stabilisation des revenus agricoles (ASRA) au Québec induit une plus importante sensibilité de l’offre par rapport au prix effectif (le prix incluant la compensation de l’ASRA) que par rapport au prix du marché. Par ailleurs, l’offre est moins sensible au prix des intrants qu’au prix de l’output. La diminution de l’aversion au risque de producteur est une autre conséquence de l’application de ce programme. En outre, l’estimation de la prime marginale relative au risque révèle que le producteur du maïs est le producteur le moins averse au risque (comparativement à celui de porc ou d’agneau). Le troisième chapitre consiste en l’analyse du changement de préférence du transformateur québécois du porc pour ce qui est du choix de marché. Nous supposons que le transformateur a la possibilité de fournir les produits sur deux marchés : étranger et local. Le modèle théorique explique l’offre relative comme étant une fonction à la fois d’anticipation relative et de volatilité relative des prix. Ainsi, ce modèle révèle que la sensibilité de l’offre relative par rapport à la volatilité relative de prix dépend de deux facteurs : d’une part, la part de l’exportation dans la production totale et d’autre part, l’élasticité de substitution entre les deux marchés. Un modèle à correction d’erreurs est utilisé lors d’estimation des paramètres du modèle. Les résultats montrent l’effet positif et significatif de l’anticipation relative du prix sur l’offre relative à court terme. Ces résultats montrent donc qu’une hausse de la volatilité du prix sur le marché étranger par rapport à celle sur le marché local entraine une baisse de l’offre relative sur le marché étranger à long terme. De plus, selon les résultats, les marchés étranger et local sont plus substituables à long terme qu’à court terme.

Redefining Urban Alleywalls: Urban Design for Active Public Space in Maynard Alley, Chinatown-International District, Seattle

Thesis (Master's)--University of Washington, 2016-06

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

DEVELOPMENT OF A DECISION/DEPLOYMENT SUPPORT TOOL FOR VARIABLE SPEED LIMITS IN RECURRENT CONGESTION

Traffic demand increases are pushing aging ground transportation infrastructures to their theoretical capacity. The result of this demand is traffic bottlenecks that are a major cause of delay on urban freeways. In addition, the queues associated with those bottlenecks increase the probability of a crash while adversely affecting environmental measures such as emissions and fuel consumption. With limited resources available for network expansion, traffic professionals have developed active traffic management systems (ATMS) in an attempt to mitigate the negative consequences of traffic bottlenecks. Among these ATMS strategies, variable speed limits (VSL) and ramp metering (RM) have been gaining international interests for their potential to improve safety, mobility, and environmental measures at freeway bottlenecks. Though previous studies have shown the tremendous potential of variable speed limit (VSL) and VSL paired with ramp metering (VSLRM) control, little guidance has been developed to assist decision makers in the planning phase of a congestion mitigation project that is considering VSL or VSLRM control. To address this need, this study has developed a comprehensive decision/deployment support tool for the application of VSL and VSLRM control in recurrently congested environments. The decision tool will assist practitioners in deciding the most appropriate control strategy at a candidate site, which candidate sites have the most potential to benefit from the suggested control strategy, and how to most effectively design the field deployment of the suggested control strategy at each implementation site. To do so, the tool is comprised of three key modules, (1) Decision Module, (2) Benefits Module, and (3) Deployment Guidelines Module. Each module uses commonly known traffic flow and geometric parameters as inputs to statistical models and empirically based procedures to provide guidance on the application of VSL and VSLRM at each candidate site. These models and procedures were developed from the outputs of simulated experiments, calibrated with field data. To demonstrate the application of the tool, a list of real-world candidate sites were selected from the Maryland State Highway Administration Mobility Report. Here, field data from each candidate site was input into the tool to illustrate the step-by-step process required for efficient planning of VSL or VSLRM control. The output of the tool includes the suggested control system at each site, a ranking of the sites based on the expected benefit-to-cost ratio, and guidelines on how to deploy the VSL signs, ramp meters, and detectors at the deployment site(s). This research has the potential to assist traffic engineers in the planning of VSL and VSLRM control, thus enhancing the procedure for allocating limited resources for mobility and safety improvements on highways plagued by recurrent congestion.

An identification procedure of multi-input Wiener models for the distortion analysis of nonlinear circuits

In this contribution, a system identification procedure of a two-input Wiener model suitable for the analysis of the disturbance behavior of integrated nonlinear circuits is presented. The identified block model is comprised of two linear dynamic and one static nonlinear block, which are determined using an parameterized approach. In order to characterize the linear blocks, an correlation analysis using a white noise input in combination with a model reduction scheme is adopted. After having characterized the linear blocks, from the output spectrum under single tone excitation at each input a linear set of equations will be set up, whose solution gives the coefficients of the nonlinear block. By this data based black box approach, the distortion behavior of a nonlinear circuit under the influence of an interfering signal at an arbitrary input port can be determined. Such an interfering signal can be, for example, an electromagnetic interference signal which conductively couples into the port of consideration. © 2011 Author(s).

Optimization of quantum states for signaling across an arbitrary qubit noise channel with minimum-error detection

International audience

Software for Designing Custom Orbital-Craniofacial Implant Plans

Purpose: Custom cranio-orbital implants have been shown to achieve better performance than their hand-shaped counterparts by restoring skull anatomy more accurately and by reducing surgery time. Designing a custom implant involves reconstructing a model of the patient's skull using their computed tomography (CT) scan. The healthy side of the skull model, contralateral to the damaged region, can then be used to design an implant plan. Designing implants for areas of thin bone, such as the orbits, is challenging due to poor CT resolution of bone structures. This makes preoperative design time-intensive since thin bone structures in CT data must be manually segmented. The objective of this thesis was to research methods to accurately and efficiently design cranio-orbital implant plans, with a focus on the orbits, and to develop software that integrates these methods. Methods: The software consists of modules that use image and surface restoration approaches to enhance both the quality of CT data and the reconstructed model. It enables users to input CT data, and use tools to output a skull model with restored anatomy. The skull model can then be used to design the implant plan. The software was designed using 3D Slicer, an open-source medical visualization platform. It was tested on CT data from thirteen patients. Results: The average time it took to create a skull model with restored anatomy using our software was 0.33 hours ± 0.04 STD. In comparison, the design time of the manual segmentation method took between 3 and 6 hours. To assess the structural accuracy of the reconstructed models, CT data from the thirteen patients was used to compare the models created using our software with those using the manual method. When registering the skull models together, the difference between each set of skulls was found to be 0.4 mm ± 0.16 STD. Conclusions: We have developed a software to design custom cranio-orbital implant plans, with a focus on thin bone structures. The method described decreases design time, and is of similar accuracy to the manual method.

ROLE OF THE FRONTAL EYE FIELD, SUPERIOR COLLICULUS, AND BASAL GANGLIA IN FLEXIBLE SACCADE BEHAVIOR

A distributed network of cortical and subcortical brain regions mediates the control of voluntary behavior, but it is unclear how this complex system may flexibly shift between different behavioral events. This thesis describes the neurophysiological changes in several key nuclei across the brain during flexible behavior, using saccadic eye movements in rhesus macaque monkeys. We examined five nuclei critical for saccade initiation and modulation: the frontal eye field (FEF) in the cerebral cortex, the subthalamic nucleus (STN), caudate nucleus (CD), and substantia nigra pars reticulata (SNr) in the basal ganglia (BG), and the superior colliculus (SC) in the midbrain. The first study tested whether a ‘threshold’ theory of how neuronal activity cues saccade initiation is consistent with the flexible control of behavior. The theory suggests there is a fixed level of FEF and SC neuronal activation at which saccades are initiated. Our results provide strong evidence against a fixed saccade threshold in either structure during flexible behavior, and indicate that threshold variability might depend on the level of inhibitory signals applied to the FEF or SC. The next two studies investigated the BG network as a likely candidate to modulate a saccade initiation mechanism, based on strong inhibitory output signals from the BG to the FEF and SC. We investigated the STN and CD (BG input), and the SNr (BG oculomotor output) to examine changes across the BG network. This revealed robust task-contingent shifts in BG signaling (Chapter 3), which uniquely impacted saccade initiation according to behavioral condition (Chapters 3 and 4). The thesis concludes with a published short review of the mechanistic effects of BG deep brain stimulation (Chapter 5), and a general discussion including proof of concept saccade behavioral changes in an MPTP-induced Parkinsonian model (Chapter 6). The studies presented here demonstrate that the conditions for saccade initiation by the FEF and SC vary according to behavioral condition, while simultaneously, large-scale task dependent shifts occur in BG signaling consistent with the observed modulation of FEF and SC activity. Taken together, these describe a mechanistic framework by which the cortico-BG loop may contribute to the flexible control of behavior.

Mobilizing Greater Crop and Land Potentials Sustainably

The supply side of the food security engine is the way we farm. The current engine of conventional tillage farming is faltering and needs to be replaced. This presentation will address supply side issues of agriculture to meet future agricultural demands for food and industry using the alternate no-till Conservation Agriculture (CA) paradigm (involving no-till farming with mulch soil cover and diversified cropping) that is able to raise productivity sustainably and efficiently, reduce inputs, regenerate degraded land, minimise soil erosion, and harness the flow of ecosystem services. CA is an ecosystems approach to farming capable of enhancing not only the economic and environmental performance of crop production and land management, but also promotes a mindset change for producing ‘more from less’, the key attitude towards sustainable production intensification. CA is now spreading globally in all continents at an annual rate of 10 Mha and covers some 157 Mha of cropland. Today global agriculture produces enough food to feed three times the current population of 7.21 billion. In 1976, when the world population was 4.15 billion, world food production far exceeded the amount necessary to feed that population. However, our urban and industrialised lifestyle leads to wastage of food of some 30%-40%, as well as waste of enormous amount of energy and protein while transforming crop-based food into animal-derived food; we have a higher proportion of people than ever before who are obese; we continue to degrade our ecosystems including much of our agricultural land of which some 400 Mha is reported to be abandoned due to severe soil and land degradation; and yields of staple cereals appear to have stagnated. These are signs of unsustainability at the structural level in the society, and it is at the structural level, for both supply side and demand side, that we need transformed mind sets about production, consumption and distribution. CA not only provides the possibility of increased crop yields for the low input smallholder farmer, it also provides a pro-poor rural and agricultural development model to support agricultural intensification in an affordable manner. For the high output farmer, it offers greater efficiency (productivity) and profit, resilience and stewardship. For farming anywhere, it addresses the root causes of agricultural land degradation, sub-optimal ecological crop and land potentials or yield ceilings, and poor crop phenotypic expressions or yield gaps. As national economies expand and diversify, more people become integrated into the economy and are able to access food. However, for those whose livelihoods continue to depend on agriculture to feed themselves and the rest of the world population, the challenge is for agriculture to produce the needed food and raw material for industry with minimum harm to the environment and the society, and to produce it with maximum efficiency and resilience against abiotic and biotic stresses, including those arising from climate change. There is growing empirical and scientific evidence worldwide that the future global supplies of food and agricultural raw materials can be assured sustainably at much lower environmental and economic cost by shifting away from conventional tillage-based food and agriculture systems to no-till CA-based food and agriculture systems. To achieve this goal will require effective national and global policy and institutional support (including research and education).

Improving Bangla ocr output through correction algorithms

Bangla OCR (Optical Character Recognition) is a long deserving software for Bengali community all over the world. Numerous e efforts suggest that due to the inherent complex nature of Bangla alphabet and its word formation process development of high fidelity OCR producing a reasonably acceptable output still remains a challenge. One possible way of improvement is by using post processing of OCR’s output; algorithms such as Edit Distance and the use of n-grams statistical information have been used to rectify misspelled words in language processing. This work presents the first known approach to use these algorithms to replace misrecognized words produced by Bangla OCR. The assessment is made on a set of fifty documents written in Bangla script and uses a dictionary of 541,167 words. The proposed correction model can correct several words lowering the recognition error rate by 2.87% and 3.18% for the character based n- gram and edit distance algorithms respectively. The developed system suggests a list of 5 (five) alternatives for a misspelled word. It is found that in 33.82% cases, the correct word is the topmost suggestion of 5 words list for n-gram algorithm while using Edit distance algorithm the first word in the suggestion properly matches 36.31% of the cases. This work will ignite rooms of thoughts for possible improvements in character recognition endeavour.

Mapping spatial and temporal potassium balances in Brazilian soils of south-west Goias.

Introduction: Brazil, is one of the main agricultural producers in the world ranking 1st in the production of sugarcane, coffee and oranges. It is also 2nd as world producer of soybeans and a leader in the harvested yields of many other crops. The annual consumption of mineral fertilizers exceeds 20 million mt, 30% of which corresponds to potash fertilizers (ANDA, 2006). From this statistic it may be supposed that fertilizer application in Brazil is rather high, compared with many other countries. However, even if it is assumed that only one fourth of this enormous 8.5 million km2 territory is used for agriculture, average levels of fertilizer application per hectare of arable land are not high enough for sustainable production. One of the major constraints is the relatively low natural fertility status of the soils which contain excessive Fe and Al oxides. Agriculture is also often practised on sandy soils so that the heavy rainfall causes large losses of nutrients through leaching. In general, nutrient removal by crops such as sugarcane and tropical fruits is much more than the average nutrient application via fertilization, especially in regions with a long history of agricultural production. In the recently developed areas, especially in the Cerrado (Brazilian savanna) where agriculture has expanded since 1980, soils are even poorer than in the "old" agricultural regions, and high costs of mineral fertilizers have become a significant input factor in determining soybean, maize and cotton planting. The consumption of mineral fertilizers throughout Brazil is very uneven. According to the 1995/96 Agricultural Census, only in eight of the total of 26 Brazilian states, were 50 per cent or more of the farms treated "systematically" with mineral fertilizers; in many states it was less than 25 per cent, and in five states even less than 12 per cent (Brazilian Institute for Geography and Statistics; Censo Agropecuario1995/96, Instituto Brazileiro de Geografia e Estadistica; IBGE, www.ibge.gov.br). The geographical application distribution pattern of mineral fertilizers may be considered as an important field of research. Understanding geographical disparities in fertilization level requires a complex approach. This includes evaluation of the availability of nutrients in the soil (and related soil properties e.g. CEC and texture), the input of nutrients with fertilizer application, and the removal of nutrients by harvested yields. When all these data are compiled, it is possible to evaluate the balance of particular nutrients for certain areas, and make conclusions as to where agricultural practices should be optimized. This kind of research is somewhat complicated, because it relies on completely different sources of data, usually from incomparable data sources, e.g. soil characteristics attributed to soil type areas, in contrast to yields by administrative regions, or farms. A priority tool in this case is the Geographical Information System (GIS), which enables attribution of data from different fields to the same territorial units, and makes possible integration of these data in an "inputoutput" model, where "input" is the natural availability of a nutrient in the soil plus fertilization, and "output" export of the same nutrient with the removed harvested yield.