Relevant bibliographies by topics / Electric engineering, estimates

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Electric engineering, estimates'

Author: Grafiati
Published: 4 June 2021
Last updated: 29 January 2023

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Journal articles on the topic "Electric engineering, estimates"

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Peterson, Michael, Chuntao Liu, Douglas Mach, Wiebke Deierling, and Christina Kalb. "A Method of Estimating Electric Fields above Electrified Clouds from Passive Microwave Observations." Journal of Atmospheric and Oceanic Technology 32, no. 8 (August 2015): 1429–46. http://dx.doi.org/10.1175/jtech-d-14-00119.1.

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AbstractA unique dataset of coincident high-altitude passive microwave and electric field observations taken by the NASA ER-2 aircraft is used to assess the feasibility of estimating electric fields above electrified clouds using ubiquitous global and multidecadal satellite products. Once applied to a global dataset, such a product would provide a unique approach for diagnosing and monitoring the current sources of the global electric circuit (GEC).In this study an algorithm has been developed that employs ice scattering signals from 37- and 85-GHz passive microwave observations to characterize the electric fields above clouds overflown by the ER-2 aircraft at nearly 20-km altitude. Electric field estimates produced by this passive microwave algorithm are then compared to electric field observations also taken by the aircraft to assess its potential future utility with satellite datasets. The algorithm is shown to estimate observed electric field strengths over intense convective clouds at least 71% (58%) of the time over land and 43% (40%) of the time over the ocean to within a factor of 2 from 85-GHz (37 GHz) passive microwave observations. Electric fields over weaker clouds can be estimated 58% (41%) of the time over land and 22% (8%) of the time over the ocean from 85-GHz (37 GHz) passive microwave observations. The accuracy of these estimates is limited by systematic errors in the observations along with other factors. Despite these sources of error, the algorithm can produce reasonable estimates of electric fields over carefully selected individual electrified clouds that differ from observations by less than 20 V m−1 for clouds that produce 200–400 V m−1 electric fields at 20 km.
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Nasution, Aminulsyah, Badriana Badriana, and Andik Bintoro. "Application of The Combined Method in Inventory Forecasting Electricity at PT PLN (Persero) ULP Sibuhuan." International Journal of Engineering, Science and Information Technology 2, no. 4 (December 19, 2022): 111–18. http://dx.doi.org/10.52088/ijesty.v2i4.348.

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The forecast of electricity consumption is a prediction of the use of electricity for the future by referring to the use of electricity in past data. Estimates of electricity consumption needs are intended to estimate how much electricity consumption is used by customers and must be provided by PT PLN (PERSERO) ULP SIBUHUAN as a provider of electrical energy services. Population growth occurs along with the development of an area, so it affects the demand for electricity and the need for electricity consumption. Load mapping must be done to maintain the continuity and distribution of electrical energy to customers. One way to preserve the continuity of service is to estimate electric power consumption using several forecasting methods. One of the methods that can be used is to combine several load forecasting methods called the combined method. The combined method is a model that incorporates various estimation methods, including econometrics, analytics, and trends, using historical customer data originating from BPS (Central Statistics Agency) Padang Lawas Regency and PT. PLN (PERSERO) ULP SIBUHUAN. The estimated load between 2021 and 2025 is 625,070,452 kWh, with an increase in electricity consumption of 20.7%, household expenses increasing by 1.8%, and business sector expenses by 1.35%. The method used is to calculate manually using Microsoft Excel to obtain forecasting values for population growth; increasing electricity consumption is very important for planning electric power generation, development, and planning of electric power distribution and mapping of loads on customers.
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Zaichenko, Stefan, Natalia Jukova, Dmitro Yakovlev, Vadym Shalenko, and Boris Korniychuk. "Intelligent multisensor system for identification ta estimates of the technical mill of electrical engineering." Gіrnichі, budіvelnі, dorozhnі ta melіorativnі mashini, no. 97 (July 29, 2021): 62–67. http://dx.doi.org/10.32347/gbdmm2021.97.0501.

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The problem of diagnosing power generating equipment by analyzing gases released into the atmosphere. The object of study is the process of diagnosing power generating equipment based on an internal combustion engine. The purpose of the work is the research is to develop the concept of the structure of the intellectual multisensory system of technical diagnostics of the autonomous electric generator on the basis of the internal combustion engine with use of electronic gas analyzers. To achieve this goal, the following tasks have been solved. To determine the possible states of the autonomous generator of electric energy on the basis of the internal combustion engine. For each state of the autonomous generator of electric energy to define characteristic gas evaporations. Choose a set of sensors that will determine the con-centration of components in the air with high accuracy. To develop an algorithm for the operation of a set of technical diagnostic equipment for the basic work of the principles of the neural system and electronic gas sensors. To check the developed diagnostic complex of electronic gas analyzers for determination of a condition of the independent generator of electric energy on the basis of the internal combustion engine. Improving the accuracy of localization in the search for a defect by additional chemical analysis of gases of power generating equipment is provided by the analysis of concentrations of hydrogen chloride, aldehydes, phenols and light hydrocarbons. A feature of the presented system for diagnosing the state of an autonomous electric power generator based on an internal combustion engine is the ability to perform diagnostic work without removing the equipment from work, which minimizes downtime. Also, the use of this system allows you to detect the development of a defect in the early stages of development, which prevents and significantly reduces the cost of repairing the energy source.
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Burlig, Fiona, James Bushnell, David Rapson, and Catherine Wolfram. "Low Energy: Estimating Electric Vehicle Electricity Use." AEA Papers and Proceedings 111 (May 1, 2021): 430–35. http://dx.doi.org/10.1257/pandp.20211088.

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We provide the first at-scale estimate of electric vehicle (EV) home charging. Previous estimates are based on conflicting surveys or are extrapolated from a small, unrepresentative sample of households with dedicated EV meters. We combine billions of hourly electricity meter measurements with address-level EV registration records from California households, including 64,000 EV owners. The average EV increases overall household load by 2.9 kilowatt-hours per day, well under half the amount assumed by state regulators. Results imply that EVs travel less than expected on electric power, raising questions about transportation electrification for climate policy.
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Volkov, M. A., and Z. Sh Ishmatov. "Synthesis of electric drive control systems using quality coefficient estimates." Russian Electrical Engineering 78, no. 11 (November 2007): 598–602. http://dx.doi.org/10.3103/s1068371207110077.

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Gakh, S. A., O. V. Khamisov, and S. V. Podkoval’nikov. "Dual Estimates in the Model of Expansion of Electric Power Systems." Automation and Remote Control 83, no. 5 (May 2022): 706–20. http://dx.doi.org/10.1134/s0005117922050046.

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Santini, Danilo J., Philip D. Patterson, and Anant D. Vyas. "Importance of Vehicle Costs, Fuel Prices, and Fuel Efficiency in Hybrid Electric Vehicle Market Success." Transportation Research Record: Journal of the Transportation Research Board 1738, no. 1 (January 2000): 11–19. http://dx.doi.org/10.3141/1738-02.

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Toyota’s introduction of a hybrid electric vehicle (HEV) named “Prius” in Japan and Honda’s proposed introduction of an HEV in the United States have generated considerable interest in the long-term viability of such fuel-efficient vehicles. A performance and cost projection model developed entirely at Argonne National Laboratory (ANL) is used to estimate costs. ANL staff developed fuel economy estimates by extending conventional vehicle modeling done primarily under the National Cooperative Highway Research Program. Together, these estimates are employed to analyze dollar costs versus benefits of two of many possible HEV technologies. Incremental costs and fuel savings are projected for a Prius-type low-performance hybrid (14.3-s 0 to 60 mph acceleration, Z60 time) and a higher-performance “mild” hybrid vehicle (11-s Z60 time). Each HEV is compared with a U.S. Toyota Corolla with automatic transmission (11-s Z60 time). The base incremental retail price range, projected a decade hence, is $3,200–$3,750, before considering battery replacement cost. Historical data are analyzed to evaluate the effect of fuel price on consumer preferences for vehicle fuel economy, performance, and size. The relationship among fuel price, the level of change in fuel price, and consumer attitude toward higher fuel efficiency also is evaluated. A recent survey on the value of higher fuel efficiency is presented and U.S. commercial viability of the hybrids is evaluated using discount rates of 20 percent and 8 percent. The analysis, with its current HEV cost estimates and current fuel savings estimates, implies that the U.S. market for such HEVs would be quite limited.
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Krupenev, D. S., and S. M. Perzhabinsky. "A reliability optimization algorithm with average dual estimates for electric power systems." Automation and Remote Control 78, no. 12 (December 2017): 2241–47. http://dx.doi.org/10.1134/s0005117917120128.

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Langston, Lee S. "Gas Turbines and Natural Gas Synergism." Mechanical Engineering 135, no. 02 (February 1, 2013): 30–35. http://dx.doi.org/10.1115/1.2013-feb-4.

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This article presents a study on new electric power gas turbines and the advent of shale natural gas, which now are upending electrical energy markets. Energy Information Administration (EIA) results show that total electrical production cost for a conventional coal plant would be 9.8 cents/kWh, while a conventional natural gas fueled gas turbine combined cycle plant would be a much lower at 6.6 cents/kWh. Furthermore, EIA estimates that 70% of new US power plants will be fueled by natural gas. Gas turbines are the prime movers for the modern combined cycle power plant. On the natural gas side of the recently upended electrical energy markets, new shale gas production and the continued development of worldwide liquefied natural gas (LNG) facilities provide the other element of synergism. The US natural gas prices are now low enough to compete directly with coal. The study concludes that the natural gas fueled gas turbine will continue to be a growing part of the world’s electric power generation.
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Onohaebi, S. O., and S. T. Apeh. "Electricity Network Planning: The Key to Efficient and Reliable Power Supply to Consumers." Advanced Materials Research 62-64 (February 2009): 172–80. http://dx.doi.org/10.4028/www.scientific.net/amr.62-64.172.

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This paper focuses on the need and procedure for the planning of electrical engineering infrastructure for any district/community in order to enhance reliability and efficiency of power supply to consumers. Almost all the towns/cities in Nigeria are unplanned and this has resulted in haphazard approach to Electricity Network Planning and implementation. A detailed theory, methodology and technical considerations, in compliance with both National and International standards are discussed in this paper. A proposed University campus was used to demonstrate the procedures involved in electricity network planning in order to achieve an efficient power supply. This involves the electric power supply, design concepts, load estimates and analysis, network distribution/equipment and sizing of cables and electrical panels taking into account the various modes of distribution. This paper also drew a simple analogy between Benin City and the Federal Capital Territory, Abuja, to illustrate the objective of the paper while highlighting the merits associated with planned electrical engineering infrastructure and suggested the ways to remedy the unplanned networks in Nigeria.
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Dissertations / Theses on the topic "Electric engineering, estimates"

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Ye, Ziwei. "A Label-based Conditional Mutual Information Estimator using Contrastive Loss Functions." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-286781.

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In the field of machine learning, representation learning is a collection of techniques that transform raw data into a technology that can be effectively developed by machine learning. In recent years, deep neural network-based representation learning technology has been widely used in image learning, recognition, classification and other fields, and one of the representative ones is the mutual information estimator/encoder. In this thesis, a new form of contrastive loss function that can be applied to existing mutual information encoder networks is proposed. Deep learning-based representation learning is very different from traditional machine learning feature extraction algorithms. In general, the features obtained by feature extraction are surface-level and can be understood by humans, while the representation learning learns the underlying structures of data, which are easy to be understood by machines but difficult for humans. Based on the above differences, when the scale of data is small, human’s prior knowledge of the data can play a big role, so the feature extraction algorithm has a greater advantage; when the scale of data increases, the component of the prior knowledge will decline sharply. At this time, the strong computing ability of deep learning is needed to make up for this deficiency, thus the effect of representation learning will be better. The research done in this thesis is mainly aimed at a more special situation, where the scale of training data is small and the scale of test data is large. In this case, there are two issues that need to be considered, one is the distribution representation of the model, and the other is the overfitting problem of the model. The LMIE (label-based mutual information estimator) model proposed in this thesis has certain advantages regarding both issues. The LMIE model mainly contains three parts: (a) a neural network based-mutual information encoder; (b) a loss function calculation module; (c) a linear classifier. Among them, the loss function calculation module is the most important one, as well as the main factor that distinguishes this model from other models.
Inom maskininlärning är representationslärande en samling tekniker som omvandlar rådata till en teknik som effektivt kan utvecklas genom maskininlärning. Under senare år har djup neurala nätverksbaserad representationsinlärningsteknologi använts i stor utsträckning för bildinlärning, igenkänning, klassificering och andra områden, och ett av de representativa är den ömsesidiga informationsberäknaren / kodaren. I denna avhandling föreslås en ny form av kontrastiv förlustfunktion som kan tillämpas på befintliga nätverk för ömsesidig informationskodare. Djup inlärningsbaserad representationsinlärning skiljer sig mycket från traditionella maskininlärningsextraheringsalgoritmer. I allmänhet är de funktioner som erhålls genom funktionsekstraktion ytnivå och kan förstås av människor, medan representationsinlärningen lär sig de underliggande strukturerna för data, som är lätta att förstå av maskiner men svåra för människor. Baserat på ovanstående skillnader kan människans förkunskaper om uppgifterna spela en stor roll, när skalan av data är liten, så funktionsekstraktionsalgoritmen har en större fördel; när skalan på data ökar kommer komponenten i förkunskaperna att minska kraftigt. För närvarande behövs den starka beräkningsförmågan för djup inlärning för att kompensera för denna brist, varför effekten av representationslärande blir bättre. Forskningen som gjorts i denna avhandling är främst inriktad på en mer speciell situation där utbildningsdata är liten och omfattningen av testdata är stor. I det här fallet är det två frågor som måste beaktas, det ena är fördelningen av modellen, och den andra är det överpassade problemet med modellen. LMIE-modellen (labelbaserad ömsesidig informationsberäknare) som föreslås i denna avhandling har vissa fördelar när det gäller båda frågorna. LMIE-modellen innehåller huvudsakligen tre delar: (a) en neural baseradömsesidig informationskodare; (b) en beräkningsmodul för förlustfunktion; (c) en linjär klassificering. Bland dem är förlustfunktionsberäkningsmodulen den viktigaste, liksom huvudfaktorn som skiljer denna modell från andra modeller.
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Tao, Zuoyu. "Improved uncertainty estimates for geophysical parameter retrieval." Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/61516.

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Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010.
This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged from student-submitted PDF version of thesis.
Includes bibliographical references (p. 167-169).
Algorithms for retrieval of geophysical parameters from radiances measured by instruments onboard satellites play a large role in helping scientists monitor the state of the planet. Current retrieval algorithms based on neural networks are superior in accuracy and speed compared to physics-based algorithms like iterated minimum variance (IMV). However, they do not have any form of error estimation, unlike IMV. This thesis examines the suitability of several different approaches to adding in confidence intervals and other methods of error estimation to the retrieval algorithm, as well as alternative machine learning methods that can both retrieve the parameters desired and assign error bars. Test datasets included both current generation operational instruments like AIRS/AMSU, as well as a hypothetical future hyper- spectral microwave sounder. Mixture density networks (MDN) and Sparse Pseudo Input Gaussian processes (SPGP) were found to be the most accurate at variance prediction. Both of these are novel methods in the field of remote sensing. MDNs also had similar training and testing time to neural networks, while SPGPs often took three times as long to train in typical cases. As a baseline, neural networks trained to estimate variance were also tested, but found to be lacking in accuracy and reliability compared to the other methods.
by Zuoyu Tao.
M.Eng.
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Riggi, Frank Peter. "Robust invariant feature correspondence for scene geometry estimates." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=99789.

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This thesis presents a novel approach to increasing the accuracy and robustness of 3D scene geometry estimates based on two 2D images of the same scene. Our approach focuses on finding feature correspondences, i.e. matching similar features between 2 images and estimating the fundamental matrix (FM), which is a key component to understanding scene geometry given two views. The accuracy of the fundamental matrix is acutely related to the number and accuracy of the correspondences. Determining point correspondences is a difficult and open research problem because many features are not robust enough to handle changes in illumination, scale, and viewpoint. As a result, there may be an insufficient number of correspondences present to estimate the fundamental matrix. Furthermore, if the FM can be estimated, it may not be accurate enough for the required task. Invariant features have been introduced in the literature to model local geometry in such a way that they are capable of being matched over more disparate changes of illumination, viewpoint, and scale. However, cases still exist where an insufficient number of correspondences are present to be able to estimate the fundamental matrix properly. In order to address this problem, we therefore introduce the Transfer of Invariant Parameters (TIP) as a new technique that will exploit the informative geometric parameters stored in several popular classes of invariant features in order to generate additional point correspondences. We anticipate that the addition of a small number of these points for each match will greatly reduce errors in the fundamental matrix estimate and permit its computation in contexts where there are an insufficient number of matches found. In addition, we present modifications to an existing RANSAC robust estimator to better exclude outliers. We demonstrate our approach with two of the most popular scale and affine invariant feature detectors. We test our methods on real images of 3D scenes and show that, with the inclusion of TIP points, it is possible to estimate the FM with fewer than seven corresponding features while still using standard estimation approaches. The resulting estimates also show that with the inclusion of additional TIP point correspondences, the average residual error is lower, fewer estimates are deemed catastrophic failures, and epipole locations are found to be more stable when compared to standard FM estimates.
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Menezes, Karol Fidelis 1966. "Signal delay estimates for design of multichip assemblies." Thesis, The University of Arizona, 1992. http://hdl.handle.net/10150/278171.

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Signal delay estimates for high-speed interconnection nets are formulated using analytical methods. The equations are suitable for estimating delay in interconnects of printed wiring boards and multi-chip modules where the resistance of wires is small. Effects of drivers, receivers, chip interfaces and wires on delay are considered by using simple models. The wires are treated as lossless transmission lines with capacitive discontinuities modeling receiver chip interfaces. Drivers are voltage sources with series resistance. Signal delay consists of line propagation delay and delay due to the change in rise time and reflections at the discontinuities. Various commonly used net topologies are identified and wiring rules and delay predictors provided for each of them. It is shown that interconnect delay can be formulated as a non-linear function of the product of the line characteristic impedance and load capacitance. SPICE simulations are sued to validate analytical derivations.
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Phan, Andrew Minh Tri. "Obtaining dense road speed estimates from sparse GPS measurements." Thesis, McGill University, 2009. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=32609.

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A major challenge for traffic management systems is the inference of traffic flow in regions of the network for which there is little data. In this thesis, GPS-based vehicle locator data from a fleet of 40-60 roving ambulances are used to estimate traffic congestion along a network of 20,000 streets in the city of Ottawa, Canada. Essentially, the road network is represented as a directed graph and a belief propagation algorithm is used to interpolate measurements from the fleet. The system incorporates a number of novel features. It makes no distinctions between freeways and surface streets, incorporates both historical and live sensor data, handles user inputs such as road closures and manual speed overrides, and is computationally efficient - providing updates every 5 to 6 minutes on commodity hardware. Experimental results are presented which address the key issue of validating the performance and reliability of the system.
Un défi important en lien avec les systèmes de gestion de la circulation routière est de définir la situation actuelle du réseau routier dans les régions où peu de données sont disponibles. Les données provenant d'une flotte de 40-60 ambulances munies d'un GPS ont été utilisées afin d'estimer la congestion routière sur un réseau de plus de 20 000 rues dans la ville d'Ottawa, au Canada. Essentiellement, le réseau routier est représenté par un graphe orienté et un algorithme de propagation de confiance est utilisé pour interpoler les données provenant de la flotte d'ambulances. Ce système comprend des caractéristiques innovatives. Le système ne fait aucune distinction entre les autoroutes et les rues, il intègre les données archivées et actuelles, il gère les informations entrées par l'utilisateur au central concernant les fermeture des routes et les changements de vitesse sur le réseau routier et il est efficace dans ses calculs puisqu'il fournit des mises à jour de l'état du réseau routier toutes les 5-6 minutes sur un ordinateur standard. Les résultats de l'expérience, la validation de la performance ainsi que la fiabilité du système sont présentés.
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Farah, Kamal. "ROC- and LTF- based estimates of neural- behavioral and neural-neural correlations." Thesis, McGill University, 2014. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=123145.

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Observed correlations between responses in visual cortex and perceptual performance help draw a functional link between neural activity and visually guided behavior. These correlations are commonly derived with ROC-based neural-behavioral covariances (referred to as choice or detect probability) using boxcar analysis windows. Although boxcar windows capture the covariation between neural activity and behavior during steady-state stimulus presentations, they are not optimized to capture these correlations during realistic time-varying visual inputs. In this thesis, we implemented a matched-filter technique, combined with cross-validation, to improve the estimation of ROC-based neural-behavioral covariance under dynamic stimulus conditions. We show that this approach maximizes the area under the ROC curve and converges to the true neural-behavioral covariance using a Poisson spiking model. We also demonstrate that the matched filter, combined with cross-validation, reveals the dynamics of the neural-behavioral covariations of individual MT neurons during the detection of a brief motion stimulus.Temporal correlations among responses in the visual cortex, on the other hand, have a substantial effect on determining the functional connectivity between neurons. In order to study the interactions of correlations in neural processing, we measured the linear transfer function between cortical areas V1 and V2 using data collected with multi-electrode extracellular recordings. Our aim was to study the effect that a single V1 action potential has on V2 neurons using linear systems identification. A linear transfer function (referred to as a kernel) is a useful metric for understanding functional connectivity between two cortical areas because it quantifies the temporal integration by V2 of V1 inputs. We used a multiple-input single-output regression model to estimate the pairwise V1-V2 kernels. Because of the large number of simultaneous V1 inputs used in our model, this multivariate analysis has the advantage of minimizing the bias in the kernels due to correlated activity between V1 neurons.We estimated 25,470 kernels from the blank and stimulus periods. Kernel quality was evaluated based on a signal-to-noise ratio (SNR) of the estimated kernel variance to the shuffled kernel variance. Putative good kernels (high SNR > 1) were extracted from the blank (4,665) and stimulus (2,542) conditions, and both were found to be exponential in shape with 18 and 27 ms time constants, respectively. Thus, V2 neurons tended to integrate V1 inputs over an exponentially decaying window, with a combined average time constant of 21 ms, that was independent of the occurrence of a visual stimulus. Although the dynamics of cortical circuitry likely contribute to our measured kernels, the integrative properties of single neurons appear to be a dominant component of the V1-V2 linear transfer function.
Les corrélations entre le comportement du cortex visuel et les habiletés visuelles permettent de comprendre le lien fonctionnel entre l'activité des neurones et le comportement d'un sujet lors du visionnement d'un écran. Ces corrélations sont déduites à travers des courbes ROC représentant les covariances entre les comportements et les neurones (la probabilité de choix et de détection) et ce, en utilisant des filtres avec une fonction de transfert Sinc. Ces filtres capturent efficacement les covariances entre les activités neurologiques et les comportements durant des stimuli constants. Toutefois, il n'est pas optimal d'utiliser ces filtres pour capturer ces corrélations lors de situations réelles et variantes en fonction du temps. Dans cette thèse, nous présentons une technique de filtrage équivalent combinée avec une validation croisée pour améliorer l'estimation de la courbe ROC représentant les covariances entre les comportements et les neurones lors de conditions de stimulus dynamiques. Suite à l'utilisation d'un modèle de déchargement sous forme d'une distribution Poisson, nous démontrons que cette approche maximise l'aire sous la courbe ROC et converge vers la vraie covariance entre les comportements et les neurones. Nous démontrons également que le filtre équivalent combiné à une validation croisée permet de représenter la dynamique des covariances des comportements et des neurones de la région visuelle MT durant la détection de brefs stimuli. Les corrélations temporelles entre les réponses du cortex visuel ont un effet considérable sur la détermination des connections fonctionnelles entre les neurones. Pour être en mesure d'étudier les interactions des corrélations du fonctionnement des neurones, nous avons calculé les valeurs des fonctions de transfert linéaires entre les régions corticales V1 et V2 en utilisant des données collectées à l'aide d'électrodes extracellulaires multiples enregistrées. Le but derrière cette analyse est de comprendre l'effet de l'influx nerveux de V1 sur les neurones V2 en usant de systèmes d'identification linéaires. Une fonction de transfert linéaire (ou fonction « kernel ») est une métrique utile à comprendre la connexion entre deux régions du cortex puisqu'elle quantifie l'intégration temporelle des neurones V1 dans V2. Nous avons employé un modèle de régression à variables multiples pour estimer la combinaison entre les « kernels » V1-V2. Face à l'insertion simultanée d'une multitude de variables V1 dans notre modèle, cette analyse à variables multiple s'est avérée être adéquate; permettant de minimiser le biais dans les « kernels » causés par les activités corrélées entre les neurones V1.Nous avons estimé 25,470 « kernels » à l'état de repos (lorsqu'aucune image n'apparait sur l'écran) et à l'état de stimulus. La qualité a été évaluée dépendamment de la valeur du ratio du signal-bruit de la variance estimée du « kernel » sur la variance du « kernel » brouillé. Les « kernels » considérés de bonne qualité (ayant un ratio signal-bruit supérieur à 1) ont été extraits des données de l'état de repos (4,665) et celles des conditions de stimuli (2,542). Il s'est avéré que ces deux types de données suivent une forme exponentielle avec des constantes de temps égales à 18 et 27 ms respectivement. Donc la convolution des V1 avec le « kernel » est équivalente à V2. V2 à son tour tend à intégrer les variables V1 dans la fonction exponentielle décroissante dont la moyenne combinée est de 21 ms. Nous pouvons noter que la forme du « kernel » est indépendante de la manifestation du stimulus visuel. Bien que les dynamiques du circuit du cortex peuvent contribuer au « kernel » quantifié, les propriétés intégratives des neurones s'avèrent être des éléments importants de la fonction de transfert linéaire de V1-V2.
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Chan, Eric Wai Chi. "Novel motion estimators for video compression." Thesis, University of Ottawa (Canada), 1994. http://hdl.handle.net/10393/6864.

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In this thesis, the problem of motion estimation is addressed from two perspectives, namely, hardware architecture and reduced complexity algorithms in the spatial and transform domains. First, a VLSI architecture which implements the full search block matching algorithm in real time is presented. The interblock dependency is exploited and hence the architecture can meet the real time requirement in various applications. Most importantly, the architecture is simple, modular and cascadable. Hence the proposed architecture is easily implementable in VLSI as a codec. The spatial domain algorithm consists of a layered structure and alleviates the local optimum problem. Most importantly, it employs a simple matching criterion, namely, a modified pixel difference classification (MPDC) and hence results in a reduced computational complexity. In addition, the algorithm is compatible with the recently proposed MPEG-1 video compression standard. Simulation results indicate that the proposed algorithm provides a comparable performance (compared to the algorithms reported in the literature) at a significantly reduced computational complexity. In addition, the hardware implementation of the proposed algorithm is very simple because of the binary operations used in the matching criteria. Finally, we present a wavelet transform based fast multiresolution motion estimation (FMRME) scheme. Here, the wavelet transform is used to exploit both the spatial and temporal redundancies resulting in an efficient coder. In FMRME, the correlations among the orientation subimages of the wavelet pyramid structure are exploited resulting in an efficient motion estimation process. In addition, this significantly reduces side information for motion vectors which corresponds to significant improvements in coding performance of the FMRME based wavelet coder for video compression. Simulation results demonstrate the superior coding performance of the FMRME based wavelet transform coder. (Abstract shortened by UMI.)
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Miller, Erik G. (Erik Gundersen). "An analysis of surface area estimates of binary volumes under three tilings." Thesis, Massachusetts Institute of Technology, 1997. http://hdl.handle.net/1721.1/43929.

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Molins, Jiménez Antonio. "Multimodal integration of EEG and MEG data using minimum ℓ₂-norm estimates." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/40528.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (leaves 69-74).
The aim of this thesis was to study the effects of multimodal integration of electroencephalography (EEG) and magnetoencephalography (MEG) data on the minimum ℓ₂-norm estimates of cortical current densities. We investigated analytically the effect of including EEG recordings in MEG studies versus the addition of new MEG channels. To further confirm these results, clinical datasets comprising concurrent MEG/EEG acquisitions were analyzed. Minimum ℓ₂-norm estimates were computed using MEG alone, EEG alone, and the combination of the two modalities. Localization accuracy of responses to median-nerve stimulation was evaluated to study the utility of combining MEG and EEG.
by Antonio Molins Jiménez.
S.M.
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Millet, Floyd W. "Improving Electromagnetic Bias Estimates." Diss., CLICK HERE for online access, 2004. http://contentdm.lib.byu.edu/ETD/image/etd525.pdf.

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Books on the topic "Electric engineering, estimates"

1

Holt, Charles Michael. Electrical estimating. Albany, N.Y: Delmar Publishers, 1997.

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Rosenberg, Paul. Vest pocket guide for electrical estimating. Englewood Cliffs, N.J: Prentice Hall, 1989.

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Kolstad, C. Kenneth. Rapid electrical estimating and pricing: A handy, quick method of directly determining the selling prices of electrical construction work. 5th ed. New York: McGraw-Hill, 1993.

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Rosenberg, Paul. Residential and commercial unit pricing for electrical contractors. Englewood Cliffs, N.J: Prentice-Hall, 1987.

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V, Kohnert Gerald, ed. Rapid electrical estimating and pricing: A handy, quick method of directly determining the selling prices of electrical construction work. 4th ed. New York: McGraw-Hill, 1986.

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Spon's estimating costs guide to electrical works: Project costs at a glance. 2nd ed. New York: Spon Press, 2003.

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Spain, Bryan J. D. Spon's estimating costs guide to electrical works: Project costs at a glance. New York: Spon Press, 2001.

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Estimator's electrical man-hour manual. 3rd ed. Houston, Tex: Gulf Pub. Co., 1999.

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Traister, John E. Residential electrical estimating. Carlsbad, CA: Craftsman Book Co., 1995.

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F, McPartland Joseph, and McGraw-Hill Book Company, eds. McGraw-Hill's handbook of electrical construction calculations. New York: McGraw-Hill, 1993.

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Book chapters on the topic "Electric engineering, estimates"

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Kyzmina, Tatyana, and Sergey Kourkin. "Estimates for the Approval of the Project of Engineering Networks in the Organization Responsible for Connecting Consumers to the Electric Grids." In XIV International Scientific Conference “INTERAGROMASH 2021”, 917–25. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80946-1_84.

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Popovskij, Vladimir, Alexander Barkalov, and Larysa Titarenko. "Recursive Estimates of States of Network Elements." In Lecture Notes in Electrical Engineering, 67–82. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-20614-6_6.

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Chew, K. W., and Y. R. Yong. "Effectiveness Comparison of Range Estimator for Battery Electric Vehicles." In Lecture Notes in Electrical Engineering, 839–49. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-0557-2_80.

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Dimiceli, Vincent E., Steven F. Piltz, and Steve A. Amburn. "Black Globe Temperature Estimate for the WBGT Index." In Lecture Notes in Electrical Engineering, 323–34. Dordrecht: Springer Netherlands, 2012. http://dx.doi.org/10.1007/978-94-007-4786-9_26.

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El Fattahi, Loubna, and El Hassan Sbai. "Vehicle Trajectory Clustering Using Variable Kernel Estimator." In Lecture Notes in Electrical Engineering, 107–12. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-1405-6_14.

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Yu, Yongyan, Zhijian Wang, and Yuansheng Lou. "Estimate the All Vanishing Points from a Single Image." In Lecture Notes in Electrical Engineering, 47–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-21697-8_7.

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Xu, Jie, Mengdi Liang, and Yanhui Wang. "Estimate of Railway Line Capacity Under Adverse Operation Condition." In Lecture Notes in Electrical Engineering, 387–400. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-2866-8_37.

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Baccour, Nouha, Daniele Puccinelli, Thiemo Voigt, Anis Koubaa, Claro Noda, Hossein Fotouhi, Mario Alves, et al. "Performance Evaluation of Link Quality Estimators." In SpringerBriefs in Electrical and Computer Engineering, 87–116. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00774-8_4.

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Walrand, Jean. "Tracking—A." In Probability in Electrical Engineering and Computer Science, 163–92. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-49995-2_9.

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AbstractThis chapter explains how to estimate an unobserved random variable or vector from available observations. This problem arises in many examples, as illustrated in Sect. 9.1. The basic problem is defined in Sect. 9.2. One commonly used approach is the linear least squares estimate explained in Sect. 9.3. A related notion is the linear regression covered in Sect. 9.4. Section 9.5 comments on the problem of overfitting. Sections 9.6 and 9.7 explain the minimum means squares estimate that may be a nonlinear function of the observations and the remarkable fact that it is linear for jointly Gaussian random variables. Section 9.8 is devoted to the Kalman filter, which is a recursive algorithm for calculating the linear least squares estimate of the state of a system given previous observations.
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Tran, Thinh Cong, Pavel Brandstetter, Vo Hoang Duy, Chau Dong, Cuong Dinh Tran, and Sang Dang Ho. "Estimate Parameters of Induction Motor Using ANN and GA Algorithm." In Lecture Notes in Electrical Engineering, 872–82. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-69814-4_84.

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Conference papers on the topic "Electric engineering, estimates"

1

Barufaldi, Guilherme, Mauricio Andrés Varela Morales, and ROBERTO GIL ANNES DA SILVA. "A Case Study in Energy Consumption Estimates for Electric Aircraft Mission Planning." In 25th International Congress of Mechanical Engineering. ABCM, 2019. http://dx.doi.org/10.26678/abcm.cobem2019.cob2019-0186.

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Rodgers, Lennon, Daniel Frey, and Erik Wilhelm. "Estimating an Electric Vehicle’s “Distance to Empty” Using Both Past and Future Route Information." In ASME 2013 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/detc2013-12880.

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An electric vehicle’s Distance to Empty (DTE) is defined as the actual distance the vehicle can be driven before recharging is required. A real-time estimate is commonly displayed on the vehicle’s electronic instrument cluster and is used by the driver to plan their route. It is proved in this paper that the challenge for any DTE estimation algorithm is to accurately predict the future energy consumption of a vehicle. Future energy can be predicted reliably if either (i) future energy consumption is sufficiently similar to the past or (ii) applicable information about the future is known beforehand. A stochastic simulation was used to show that the average energy use (Wh/km) measured over the past ∼300 km often does an adequate job at predicting future energy use. A conventional DTE algorithm assumes this condition by “blending” both a long- and short-term average of past energy use. However, significant changes in driving conditions (e.g. traffic or auxiliary energy use) for sustained periods of time can cause large errors in DTE estimates. This paper showed that DTE error can be reduced if those future changes are detected beforehand by obtaining route information from the driver. For example, if the driver provides their destination(s) beforehand, a navigation system could obtain route, traffic and weather information via the internet and use this information to improve the DTE estimate. A multivariate linear regression model was derived that adjusts a historical average of energy consumption based on estimated changes in speeds, traffic and temperature. This method utilizes the measuring ability of the vehicle and thus does not require complex physics-based models. The algorithm could be implemented as a cloud-based mobile phone application since it is computationally light and the model is fitted using historical driving data. Finally, the algorithms were compared using a stochastic vehicle simulation and it was shown that incorporating future route information can significantly reduce DTE error.
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Krupenev, Dmitry, and Sergei Perzhabinsky. "Algorithm for the adequacy discrete optimization by using dual estimates when planning the development of electric power systems." In 2016 17th International Scientific Conference on Electric Power Engineering (EPE). IEEE, 2016. http://dx.doi.org/10.1109/epe.2016.7521739.

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Morrow, C., G. Rochau, J. Cash, and D. King. "Conceptual Analysis of the Economic Feasibility of Fission Electric Cell Reactors." In 10th International Conference on Nuclear Engineering. ASMEDC, 2002. http://dx.doi.org/10.1115/icone10-22436.

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The United States Department of Energy, Nuclear Energy Research Initiative (NERI) Direct Energy Conversion (DEC) project began in August of 1998 with the goal of developing a direct energy conversion process suitable for commercial development. With roughly two thirds of the project completed, we believe a viable direct energy device could be economic. This paper describes the financial basis behind that belief for one proposed DEC reactor, the magnetically insulated fission electric cell (FEC). It also illustrates the value of economic analysis even in these early phases of a research project. The financial basis consists of a conceptual level Economic Model comprised of five modules. The Design Model provides technical specification to other modules. The Fuel Cost Model estimates fuel expenses based on current spot market prices applied over a wide range of fuel enrichment. The Operating Cost Model uses published correlations to provide rough order of magnitude non-fuel operating costs. The Capital Cost model uses analogy and parametric estimating techniques to generate capital cost estimates for a DEC power plant. Finally, the financial model combines output from the other models to produce a Net Present Value analysis with cost of generation as the independent variable. Model results indicate that several FEC geometric configurations could be economic. Within these configurations, optimums exist. Finally, the model demonstrates that the most efficient design is not necessarily the most economic.
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Tafuri, Sebastian, Fredrik Ekstedt, Johan S. Carlson, Andreas Mark, and Fredrik Edelvik. "Improved Spray Paint Thickness Calculation From Simulated Droplets Using Density Estimation." In ASME 2012 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/detc2012-70821.

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Advancements in the simulation of electrostatic spray painting make it possible to evaluate the quality and efficiency of programs for industrial paint robots during Off-Line Programming (OLP). Simulation of the spray paint deposition process is very complex and requires physical simulation of the airflow, electric fields, breakup of paint into droplets, and tracking of these droplets until they evaporate or impact on a surface. The information from the simulated droplet impacts is then used to estimate the paint film thickness. The current common way of measuring paint thickness on complex geometrical shapes is to use histogram based methods. These methods are easy to implement but are dependent on good quality meshes. In this paper, we show that using kernel density estimation not only gives better estimates but it also is not dependent on mesh quality. We also extend the method using a multivariate bandwidth adapted using estimated gradients of the thickness. To show the advantages of the proposed method, all three methods are compared on a test case and with real thickness measurements from an industrial case study using a complex automotive part.
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Hsu, Yung-Hsiang J., Shad Laws, Christopher D. Gadda, and J. Christian Gerdes. "A Method to Estimate the Friction Coefficient and Tire Slip Angle Using Steering Torque." In ASME 2006 International Mechanical Engineering Congress and Exposition. ASMEDC, 2006. http://dx.doi.org/10.1115/imece2006-15402.

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Knowledge of tire forces is important for vehicle control systems that aim to enhance vehicle handling and passenger safety. This paper introduces a nonlinear observer that estimates the coefficient of friction and tire slip angle, both of which are key factors in characterizing the vehicle's lateral tire forces. The observer estimates the friction coefficient and slip angle based on sensor measurements available on many production vehicles. This includes steering torque measurements readily available in steer-by-wire or electric power steering (EPS) systems. Experimental results on a steer-by-wire research vehicle (Fig. 1) demonstrate the observer's ability to provide accurate estimates out to the limits of handling.
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Alabdulkarem, Abdullah, and Mohannad Abdulghani. "Estimates of Area, Output and Levelized Energy Cost of Solar Energy Schemes in Saudi Arabia." In ASME 2019 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/imece2019-10967.

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Abstract Saudi Arabia consumes a significant amount of oil domestically for transportation and energy generation purposes. The booming population and high power consumption contribute to a sharp increase in power demands. The Saudi electric utility is investing heavily in upgrading the power grid and generation infrastructure to keep up with surging consumption. The desert belt in Saudi Arabia is exposed to substantial levels of solar irradiance, which renders Saudi Arabia a good candidate for large scale solar energy schemes. Upper and lower limits of cost and energy output are to be estimated for such ambitious endeavors to enter the national and international conversations. In this work, an attempt was made to estimate the area of photovoltaic panels and levelized energy cost required for generating the peak load and baseload power demands of the entire country and contrast them against the subsidized and unsubsidized cost of electricity in the kingdom. The levelized energy cost was found to be higher than the unsubsidized cost of electricity in the kingdom. The area required for both schemes was not found to be a limiting factor when compared to the available land area.
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Addy, Nathan, Johanna L. Mathieu, Sila Kiliccote, and Duncan S. Callaway. "Understanding the Effect of Baseline Modeling Implementation Choices on Analysis of Demand Response Performance." In ASME 2013 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2013. http://dx.doi.org/10.1115/imece2013-63717.

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Accurate evaluation of the performance of buildings participating in Demand Response (DR) programs is critical to the adoption and improvement of these programs. Typically, we calculate load sheds during DR events by comparing observed electric load against counterfactual predictions made using statistical baseline models. Many baseline models exist and these models can produce different shed estimates. Moreover, modelers implementing the same baseline model can make different modeling implementation choices, which may affect shed estimates. In this work, using real data, we analyze the effect of different modeling implementation choices on shed estimates. We focus on five issues: weather data source, resolution of data, methods for determining when buildings are occupied, methods for aligning building data with temperature data, and methods for power outage filtering. Results indicate sensitivity to the weather data source and data filtration methods as well as an immediate potential for automation of methods to choose building occupied modes.
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Minas, Constantinos, and Sejalben Patel. "Probabilistic Life Prediction of Hydrogen Steel Pressure Vessels in Industrial Electric Trucks." In ASME 2014 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/imece2014-38532.

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Fuel cell powered industrial electric trucks are widely used in industry where more than 4000 systems are currently installed, achieving more than 20 million operating hours. The electric trucks are equipped with fuel cell power systems instead of an array of lead-acid batteries, which incorporate a permanently mounted pressure vessel containing compressed hydrogen gas and enabling onboard fueling. Fueling can be performed several times a day subjecting the pressure vessel to a large number of pressure cycles. It is critical to design the pressure vessel to withstand the required number of cycles which is in the thousands, over the life of the fuel cell power system estimated at 20000 hours. Steel pressure vessels which are subjected to hydrogen embrittlement are widely used in this application. In order to ensure the safety of the design, a linear elastic fracture mechanics model was developed in order to predict the life of the steel pressure vessel. The developed model was based on the ASME pressure vessel code section KD-10, which uses fatigue crack growth laws based on the relationship between the fatigue crack growth rate (da/dN) and the cyclic intensity factor (ΔK). Two samples were tested under hydrogen cyclic pressure loading. The experimental data was used to obtain estimates for the crack initiation phase. Statistical data was obtained from several hundred systems of the installed base, in order to determine the distributions of the maximum and minimum pressures the vessel is typically subjected to. The probabilistic LEFM model was used in a Monte Carlo simulation where the maximum and minimum pressure assumed a random value based on the equivalent random generator of their associated statistical distribution that is an extreme distribution and a Johnson SB distribution, respectively. The results indicated an increase by a factor of two, in the number of cycles when compared to the cycle prediction based on a constant R-ratio (maximum/minimum fill pressure). The analysis was repeated with normal distribution random generators which resulted in similar results. The results from this analysis ensure the safety of the steel pressure vessel design.
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Sandquist, Gary M., Jay F. Kunze, and Vern C. Rogers. "Oil Recovery From Shale With Nuclear Generated Heat." In 16th International Conference on Nuclear Engineering. ASMEDC, 2008. http://dx.doi.org/10.1115/icone16-48188.

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Shell Oil Corporation has developed an in-situ process for shale oil recovery that uses electric heaters to heat oil shale deposits and produce chemical reactions within the shale that can liberate the shale-oil. The major production expense is electrical power used to heat the shale. Significantly, small mobile nuclear reactors are now under development and testing that could provide high-temperature working fluids (both gaseous and liquid) at lower unit energy cost to replace current electrical heating. Nuclear generated steam is particularly cost effective and technically attractive for oil shale recovery. Estimates are that US oil shale deposits could be made to produce about 2 million barrels of oil per acre ($200 million/acre of oil at $100/barrel) if properly processed using high temperature steam. Furthermore, a these small nuclear reactors could be delivered by heavy haul truck, carefully buried for adequate shielding and safety, remotely operated, and moved as needed to process large oil shale fields.
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