Academic literature on the topic 'Race Model Architecture'
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Journal articles on the topic "Race Model Architecture"
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Townsend, James T., and Georgie Nozawa. "Serial exhaustive models can violate the race model inequality: Implications for architecture and capacity." Psychological Review 104, no. 3 (1997): 595–602. http://dx.doi.org/10.1037/0033-295x.104.3.595.
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Samuel, Arthur G. "Merge: Contorted architecture, distorted facts, and purported autonomy." Behavioral and Brain Sciences 23, no. 3 (June 2000): 345–46. http://dx.doi.org/10.1017/s0140525x00443244.
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Norris, McQueen & Cutler claim that Merge is an autonomous model, superior to the interactive TRACE model and the autonomous Race model. Merge is actually an interactive model, despite claims to the contrary. The presentation of the literature seriously distorts many findings, in order to advocate autonomy. It is Merge's interactivity that allows it to simulate findings in the literature.
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Pugin, Konstantin V., Kirill A. Mamrosenko, and Alexander M. Giatsintov. "Software architecture for display controller and operating system interaction." Radioelectronics. Nanosystems. Information Technologies. 13, no. 1 (March 27, 2021): 87–94. http://dx.doi.org/10.17725/rensit.2021.13.087.
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Article describes solutions for developing programs that provide interaction between Linux operating system and multiple display controller hardware blocks (outputs), that use one clock generation IP-block with phase-locked loop (PLL). There is no API for such devices in Linux, thus new software model was developed. This model is based on official Linux GPU developer driver model, but was modified to cover case described earlier. Article describes three models for display controller driver development – monolithic, component and semi-monolithic. These models cannot cover case described earlier, because they assume that one clock generator should be attached to one output. A new model was developed, that is based on component model, but has additional mechanics to prevent race condition that can happen while using one clock generator with multiple outputs. Article also presents modified model for bootloaders graphics drivers. This model has been simplified over developed Linux model, but also has component nature (with less components) and race prevention mechanics (but with weaker conditions). Hardware interaction driver components that are developed using provided software models are interchangeable between Linux and bootloader.
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Otto, Thomas U., and Pascal Mamassian. "Multisensory Decisions: the Test of a Race Model, Its Logic, and Power." Multisensory Research 30, no. 1 (2017): 1–24. http://dx.doi.org/10.1163/22134808-00002541.
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The use of separate multisensory signals is often beneficial. A prominent example is the speed-up of responses to two redundant signals relative to the components, which is known as the redundant signals effect (RSE). A convenient explanation for the effect is statistical facilitation, which is inherent in the basic architecture of race models (Raab, 1962,Trans. N. Y. Acad. Sci.24, 574–590). However, this class of models has been largely rejected in multisensory research, which we think results from an ambiguity in definitions and misinterpretations of the influential race model test (Miller, 1982,Cogn. Psychol.14, 247–279). To resolve these issues, we here discuss four main items. First, we clarify definitions and ask how successful models of perceptual decision making can be extended from uni- to multisensory decisions. Second, we review the race model test and emphasize elements leading to confusion with its interpretation. Third, we introduce a new approach to study the RSE. As a major change of direction, our working hypothesis is that the basic race model architecture is correct even if the race model test seems to suggest otherwise. Based on this approach, we argue that understanding the variability of responses is the key to understand the RSE. Finally, we highlight the critical role of model testability to advance research on multisensory decisions. Despite being largely rejected, it should be recognized that race models, as part of a broader class of parallel decision models, demonstrate, in fact, a convincing explanatory power in a range of experimental paradigms. To improve research consistency in the future, we conclude with a short checklist for RSE studies.
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Maull, Thomas, and Adriano Schommer. "Optimizing Torque Delivery for an Energy-Limited Electric Race Car Using Model Predictive Control." World Electric Vehicle Journal 13, no. 12 (November 24, 2022): 224. http://dx.doi.org/10.3390/wevj13120224.
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This paper presents a torque controller for the energy optimization of the powertrain of an electric Formula Student race car. Limited battery capacity within electric race car designs requires energy management solutions to minimize lap time while simultaneously controlling and managing the overall energy consumption to finish the race. The energy-managing torque control algorithm developed in this work optimizes the finite onboard energy from the battery pack to reduce lap time and energy consumption when energy deficits occur. The longitudinal dynamics of the vehicle were represented by a linearized first-principles model and validated against a parameterized electric Formula Student race car model in commercial lap time simulation software. A Simulink-based model predictive controller (MPC) architecture was created to balance energy use requirements with optimum lap time. This controller was tested against a hardware-limited and torque-limited system in a constant torque request and a varying torque request scenario. The controller decreased the elapsed time to complete a 150 m straight-line acceleration by 11.4% over the torque-limited solution and 13.5% in a 150 m Formula Student manoeuvre.
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Marewski, Julian N., and Katja Mehlhorn. "Using the ACT-R architecture to specify 39 quantitative process models of decision making." Judgment and Decision Making 6, no. 6 (August 2011): 439–519. http://dx.doi.org/10.1017/s1930297500002473.
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AbstractHypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a methodological primer on how detailed cognitive architectures such as ACT-R allow remedying these problems. To make our point, we address a controversy, namely, whether noncompensatory or compensatory processes better describe how people make decisions from the accessibility of memories. We specify 39 models of accessibility-based decision processes in ACT-R, including the noncompensatory recognition heuristic and various other popular noncompensatory and compensatory decision models. Additionally, to illustrate how such models can be tested, we conduct a model comparison, fitting the models to one experiment and letting them generalize to another. Behavioral data are best accounted for by race models. These race models embody the noncompensatory recognition heuristic and compensatory models as a race between competing processes, dissolving the dichotomy between existing decision models.
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Venkataratamani, Prasanna Venkhatesh, and Aditya Murthy. "Distinct mechanisms explain the control of reach speed planning: evidence from a race model framework." Journal of Neurophysiology 120, no. 3 (September 1, 2018): 1293–306. http://dx.doi.org/10.1152/jn.00707.2017.
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Previous studies have investigated the computational architecture underlying the voluntary control of reach movements that demands a change in position or direction of movement planning. Here we used a novel task in which subjects had to either increase or decrease the movement speed according to a change in target color that occurred randomly during a trial. The applicability of different race models to such a speed redirect task was assessed. We found that the predictions of an independent race model that instantiated an abort-and-replan strategy was consistent with all aspects of performance in the fast-to-slow speed condition. The results from modeling indicated a peculiar asymmetry, in that although the fast-to-slow speed change required inhibition, none of the standard race models was able to explain how movements changed from slow to fast speeds. Interestingly, a weighted averaging model that simulated the gradual merging of two kinematic plans explained behavior in the slow-to-fast speed task. In summary, our work shows how a race model framework can provide an understanding of how the brain controls different aspects of reach movement planning and help distinguish between an abort-and-replan strategy and merging of plans. NEW & NOTEWORTHY For the first time, a race model framework was used to understand how reach speeds are modified. We provide evidence that a fast-to-slow speed change required aborting the current plan and a complete respecification of a new plan, while none of the race models was able to explain an instructed increase of hand movement speed, which was instead accomplished by a merging of a new kinematic plan with the existing kinematic plan.
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Spataro, Davide, Donato D’Ambrosio, Giuseppe Filippone, Rocco Rongo, William Spataro, and Davide Marocco. "The new SCIARA-fv3 numerical model and acceleration by GPGPU strategies." International Journal of High Performance Computing Applications 31, no. 2 (July 27, 2016): 163–76. http://dx.doi.org/10.1177/1094342015584520.
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This paper presents the parallel implementation, using the Compute Unified Device Architecture (CUDA) architecture, of the SCIARA-fv3 Complex Cellular Automata model for simulating lava flows. The computational model is based on a Bingham-like rheology and both flow velocity and the physical time corresponding to a computational step have been made explicit. The parallelization design has involved, among other issues, the application of strategies that can avoid incorrect computation results due to race conditions and achieving the best performance and occupancy of the underlying available hardware. Two hardware types were adopted for testing different versions of the CUDA implementations of the SCIARA-fv3 model, namely the GTX 580 and GTX 680 graphic processors. Despite its computational complexity, carried out experiments of the model parallelization have shown significant performance improvements, confirming that graphic hardware can represent a valid solution for the implementation of Cellular Automata models.
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Pinho, João, Gabriel Costa, Pedro U. Lima, and Miguel Ayala Botto. "Learning-Based Model Predictive Control for Autonomous Racing." World Electric Vehicle Journal 14, no. 7 (June 21, 2023): 163. http://dx.doi.org/10.3390/wevj14070163.
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In this paper, we present the adaptation of the terminal component learning-based model predictive control (TC-LMPC) architecture for autonomous racing to the Formula Student Driverless (FSD) context. We test the TC-LMPC architecture, a reference-free controller that is able to learn from previous iterations by building an appropriate terminal safe set and terminal cost from collected trajectories and input sequences, in a vehicle simulator dedicated to the FSD competition. One major problem in autonomous racing is the difficulty in obtaining accurate highly nonlinear vehicle models that cover the entire performance envelope. This is more severe as the controller pushes for incrementally more aggressive behavior. To address this problem, we use offline and online measurements and machine learning (ML) techniques for the online adaptation of the vehicle model. We test two sparse Gaussian process regression (GPR) approximations for model learning. The novelty in the model learning segment is the use of a selection method for the initial training dataset that maximizes the information gain criterion. The TC-LMPC with model learning achieves a 5.9 s reduction (3%) in the total 10-lap FSD race time.
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Corneil, Brian D., and James K. Elsley. "Countermanding Eye-Head Gaze Shifts in Humans: Marching Orders Are Delivered to the Head First." Journal of Neurophysiology 94, no. 1 (July 2005): 883–95. http://dx.doi.org/10.1152/jn.01171.2004.
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The countermanding task requires subjects to cancel a planned movement on appearance of a stop signal, providing insights into response generation and suppression. Here, we studied human eye-head gaze shifts in a countermanding task with targets located beyond the horizontal oculomotor range. Consistent with head-restrained saccadic countermanding studies, the proportion of gaze shifts on stop trials increased the longer the stop signal was delayed after target presentation, and gaze shift stop-signal reaction times (SSRTs: a derived statistic measuring how long it takes to cancel a movement) averaged ∼120 ms across seven subjects. We also observed a marked proportion of trials (13% of all stop trials) during which gaze remained stable but the head moved toward the target. Such head movements were more common at intermediate stop signal delays. We never observed the converse sequence wherein gaze moved while the head remained stable. SSRTs for head movements averaged ∼190 ms or ∼70–75 ms longer than gaze SSRTs. Although our findings are inconsistent with a single race to threshold as proposed for controlling saccadic eye movements, movement parameters on stop trials attested to interactions consistent with a race model architecture. To explain our data, we tested two extensions to the saccadic race model. The first assumed that gaze shifts and head movements are controlled by parallel but independent races. The second model assumed that gaze shifts and head movements are controlled by a single race, preceded by terminal ballistic intervals not under inhibitory control, and that the head-movement branch is activated at a lower threshold. Although simulations of both models produced acceptable fits to the empirical data, we favor the second alternative as it is more parsimonious with recent findings in the oculomotor system. Using the second model, estimates for gaze and head ballistic intervals were ∼25 and 90 ms, respectively, consistent with the known physiology of the final motor paths. Further, the threshold of the head movement branch was estimated to be 85% of that required to activate gaze shifts. From these results, we conclude that a commitment to a head movement is made in advance of gaze shifts and that the comparative SSRT differences result primarily from biomechanical differences inherent to eye and head motion.
Dissertations / Theses on the topic "Race Model Architecture"
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Martínez, Marigorta Urko 1983. "Genetic architecture of complex disease in humans :a cross-population exploration." Doctoral thesis, Universitat Pompeu Fabra, 2012. http://hdl.handle.net/10803/96909.
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The aetiology of common diseases is shaped by the effects of genetic and environmental factors. Big efforts have been devoted to unravel the genetic basis of disease with the hope that it will help to develop new therapeutic treatments and to achieve personalized medicine. With the development of high-throughput genotyping technologies, hundreds of association studies have described many loci associated to disease. However, the depiction of disease architecture remains incomplete. The aim of this work is to perform exhaustive comparisons across human populations to evaluate pressing questions. Our results provide new insights in the allele frequency of risk variants, their sharing across populations and the likely architecture of diseaseLa etiología de las enfermedades comunes está formada por factores genéticos y ambientales. Se ha puesto mucho empeño en describir sus bases genéticas. Este conocimiento será útil para desarrollar nuevas terapias y la medicina personalizada. Gracias a las técnicas de genotipado masivo, centenares de estudios de asociación han descrito una infinidad de genes asociados a enfermedad. Pese a ello, la arquitectura genética de las enfermedades no ha sido totalmente descrita. Esta tesis pretende llevar a cabo exhaustivas comparaciones entre poblaciones para responder diversas preguntas candentes. Nuestros resultados dan pistas sobre la frecuencia de los alelos de riesgo, su presencia entre poblaciones y la probable arquitectura de las enfermedades.
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Stevenson, Clint W. "A Logistic Regression Analysis of Utah Colleges Exit Poll Response Rates Using SAS Software." BYU ScholarsArchive, 2006. https://scholarsarchive.byu.edu/etd/1116.
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In this study I examine voter response at an interview level using a dataset of 7562 voter contacts (including responses and nonresponses) in the 2004 Utah Colleges Exit Poll. In 2004, 4908 of the 7562 voters approached responded to the exit poll for an overall response rate of 65 percent. Logistic regression is used to estimate factors that contribute to a success or failure of each interview attempt. This logistic regression model uses interviewer characteristics, voter characteristics (both respondents and nonrespondents), and exogenous factors as independent variables. Voter characteristics such as race, gender, and age are strongly associated with response. An interviewer's prior retail sales experience is associated with whether a voter will decide to respond to a questionnaire or not. The only exogenous factor that is associated with voter response is whether the interview occurred in the morning or afternoon.
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Xiujuan, Wang. "Un modèle probabiliste de fleur de fertilité et facteurs influant sur la production de semences en colza d'hiver." Phd thesis, Ecole Centrale Paris, 2011. http://tel.archives-ouvertes.fr/tel-00612716.
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Le nombre de siliques par plante et le nombre de graines par silique sont les composantes du rendement du colza d'hiver qui présentent la plus grande variabilité. La production d'une graine résulte de la combinaison de plusieurs processus physiologiques, à savoir la formation des ovules et des grains de pollen, la fécondation des ovules et le développement de jeunes embryons. Un problème survenu à n'importe quelles des étapes peut entraîner l'avortement de graines ou de la silique. Le nombre potentiel d'ovules par silique et le nombre graines arrivant la maturité dépendraient de la position du dans l'architecture de plante et le temps de son apparition, mais le mode complexe de développement de colza rend difficile l'analyse des causes et effets. Dans cette étude, la variabilité des composantes du rendement suivantes est étudiée: (a) nombre d'ovules par silique, (b) nombre de graines par silique, et (c) nombre de siliques par axe en fonction d'une part, l'emplacement de la fleur dans l'inflorescence, et la position de cette dernière sur la tige, et l'autre part, le temps d'apparition de la silique, qui affectent la disponibilité d'assimilats. Basé sur les processus biologiques de la fertilité des fleurs, un modèle probabiliste est développé pour simuler le développement des graines. Le nombre de grains de pollen par fleur peut être déduit par le modèle et ainsi que les facteurs qui influent le rendement. Des expériences de terrain ont été menées en 2008 et 2009. Le nombre et la position des fleurs qui s'épanouissaient dans l'inflorescence ont été enregistrés sur la base des observations tous les deux à trois jours pendant la saison de floraison. Différents états trophiques ont été créés par tailler de la tige principale ou des ramifications à étudier l'effet de l'assimilation de la compétition. Les résultats montrent que la quantité d'assimilâtes disponibles a été le principal déterminant de la production de graines et de siliques. La répartition d'assimilâtes a été sensiblement affectée par l'emplacement de silique au sein d'une inflorescence et la location de l'inflorescence sur la tige colza. En outre, le paramètre de la distribution du nombre de pollen a indiqué que la production de graines pourrait être limitée par la pollinisation. La réduction de la viabilité des ovules pourrait entraîner la diminution du nombre de siliques et le nombre de graines par silique à l'extrémité de l'inflorescence. Le modèle proposé pourrait être un outil pour étudier la stratégie de l'amélioration du rendement des plantes à fleurs.
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Venkhatesh, V. Prasanna. "Computational Mechanisms Underlying the Voluntary Control of Reach Movement Planning and Execution." Thesis, 2017. http://etd.iisc.ac.in/handle/2005/4235.
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In everyday life we make a variety of reaching movements. Most of these reaching movements have a clear objective of bringing the hand to the spatial location of the object of interest. Although we typically do not explicitly or at least are not aware of formulating a movement plan during reaching, a number of psychophysical studies on simple reaching movements highlight the notion that movement attributes and plans are likely to be represented/programmed in the central nervous system well before execution. In my thesis I have investigated the computational mechanisms underlying change of such movement plans.
I used a REDIRECT task in which targets occasionally changed their locations, to study the control of reaching movements. This task also gives a unique opportunity to address control before movement execution and while the movement is made. I used nine different race model architectures that can explain the redirect behavior of reaching movements. I showed that only the independent GO-STOP-GO model successfully explains the various behavioral measures. Second, using a particular outcome of the task called the hypometric response, EMG measurements and computational modelling I showed that redirecting a movement before initiation and during motor execution shared the same mechanisms.
Based on the race model framework developed in the previous chapter I next addressed whether and how kinematic plans maybe changed online. Reports from various studies suggest the kinematic representation constitutes an important aspect of motor planning. Unlike eye movements for which the kinematics are relatively fixed, hand movements exhibit a large scope for modification of the kinematics. I designed a novel velocity redirect task to understand the computational mechanisms behind the subject’s ability to change the speed of their movement. In two separate tasks the subjects either had to increase or decrease the speed of the movement according to the change in the target color. The applicability of different race model architectures to the velocity redirect task was assessed, similar to the position redirect task. I found that the GO-STOP-GO independent explained all aspects of behavior in the fast to slow velocity condition. The modeling results indicated a peculiar asymmetry in that while the FS model required inhibition, none of the GO-GO or GO-STOP models were able to explain the slow to fast velocity data. Interestingly, a vector averaging model was used to demonstrate the gradual merge of two kinematic plans in the SF task. Further, I undertook a novel approach to investigate the nature of kinematic planning borrowing from a well known paradigm in cognitive control called task switching. Using the logic of the task switch paradigm I showed the existence of a switch cost when subjects switched between slow and fast velocity movements indicating the existence of a kinematic plan well before the target onset, suggesting that such a plan may be part of a motor set. In summary, my work shows how a race model framework can provide a mechanistic understanding of motor control of different aspects of reach movement planning.
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Eloff, Corné. "Spatial technology as a tool to analyse and combat crime." Thesis, 2006. http://hdl.handle.net/10500/1193.
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This study explores the utilisation of spatial technologies as a tool to analyse and combat crime. The study deals specifically with remote sensing and its potential for being integrated with geographical information systems (GIS). The integrated spatial approach resulted in the understanding of land use class behaviour over time and its relationship to specific crime incidents per police precinct area.
The incorporation of spatial technologies to test criminological theories in practice, such as the ecological theories of criminology, provides the science with strategic value. It proves the value of combining multi-disciplinary scientific fields to create a more advanced platform to understand land use behaviour and its relationship to crime.
Crime in South Africa is a serious concern and it impacts negatively on so many lives. The fear of crime, the loss of life, the socio-economic impact of crime, etc. create the impression that the battle against crime has been lost. The limited knowledge base within the law enforcement agencies, limited logistical resources and low retention rate of critical staff all contribute to making the reduction of crime more difficult to achieve.
A practical procedure of using remote sensing technology integrated with geographical information systems (GIS), overlaid with geo-coded crime data to provide a spatial technological basis to analyse and combat crime, is illustrated by a practical study of the Tshwane municipality area. The methodology applied in this study required multi-skilled resources incorporating GIS and the understanding of crime to integrate the diverse scientific fields into a consolidated process that can contribute to the combating of crime in general.
The existence of informal settlement areas in South Africa stresses the socio-economic problems that need to be addressed as there is a clear correlation of land use data with serious crime incidents in these areas. The fact that no formal cadastre exists for these areas, combined with a great diversity in densification and growth of the periphery, makes analysis very difficult without remote sensing imagery. Revisits over time to assess changes in these areas in order to adapt policing strategies will create an improved information layer for responding to crime. Final computerised maps generated from remote sensing and GIS layers are not the only information that can be used to prevent and combat crime. An important recipe for ultimately successfully managing and controlling crime in South Africa is to strategically combine training of the law enforcement agencies in the use of spatial information with police science.
The researcher concludes with the hope that this study will contribute to the improved utilisation of spatial technology to analyse and combat crime in South Africa. The ultimate vision is the expansion of the science of criminology by adding an advanced spatial technology module to its curriculum.Criminology
D.Litt. et Phil. (Criminology)
Books on the topic "Race Model Architecture"
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Oesterreich, Mark H. Modal analysis of the 72 Inch TAC-4 Ruggedized Rack (CLIN 0003AA). Monterey, Calif: Naval Postgraduate School, 1997.
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Clarke, Andrew. The Metabolic Theory of Ecology. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780199551668.003.0012.
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The model of West, Brown & Enquist (WBE) is built on the assumption that the metabolic rate of cells is determined by the architecture of the vascular network that supplies them with oxygen and nutrients. For a fractal-like network, and assuming that evolution has minimised cardiovascular costs, the WBE model predicts that s=metabolism should scale with mass with an exponent, b, of 0.75 at infinite size, and ~ 0.8 at realistic larger sizes. Scaling exponents ~ 0.75 for standard or resting metabolic rate are observed widely, but far from universally, including in some invertebrates with cardiovascular systems very different from that assumed in the WBE model. Data for field metabolic rate in vertebrates typically exhibit b ~ 0.8, which matches the WBE prediction. Addition of a simple Boltzmann factor to capture the effects of body temperature on metabolic rate yields the central equation of the Metabolic Theory of Ecology (MTE). The MTE has become an important strand in ecology, and the WBE model is the most widely accepted physical explanation for the scaling of metabolic rate with body mass. Capturing the effect of temperature through a Boltzmann factor is a useful statistical description but too simple to qualify as a complete physical theory of thermal ecology.
Book chapters on the topic "Race Model Architecture"
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Saidi, Abdessamad, Mohamed Hadj Kacem, Imen Tounsi, and Ahmed Hadj Kacem. "Adopting the Internet of Things Technology to Remotely Monitor COVID-19 Patients." In Lecture Notes in Computer Science, 166–80. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-09593-1_13.
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AbstractThe coronavirus known as COVID-19 is the topic of the hour all over the world. This virus has invaded the world with its invariants, which are characterized by their rapid spread. COVID-19 has impacted the health of people and the economy of countries. For that, laboratories, researchers, and doctors are in a race against time to find a cure for this pandemic. To combat this virus, cutting-edge technologies such as artificial intelligence, cloud computing, and big data have been put in place. In our work, we use Internet of Things (IoT) technology. The use of IoT in an efficient way can lead to detecting infected people and avoiding being contaminated. In this paper, we are interested in the remote medical monitoring of patients who have tested positive for COVID-19. We propose a meta-modeling technique to model the IoT architecture. Then we implement two IoT solutions that permit the remote medical monitoring of patients infected with COVID-19 and the respect of social distancing by instantiating correct models that conform to the proposed meta-model in order to mitigate the COVID-19 outbreak.
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Springer, Virginia, and Dimitri Petrik. "Towards a Taxonomy of Impact Factors for Digital Platform Pricing." In Agile Processes in Software Engineering and Extreme Programming – Workshops, 115–24. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-88583-0_11.
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AbstractSolving the chicken-or-egg problem and leveraging value contributing actors on the platform is crucial to establish dynamic platform-based ecosystems. A digital platform provider is challenged to manage multilateral platform architecture and governance mechanisms to establish an attractive platform-based ecosystem to foster third-party complementors to join. One of the key issues while establishing a platform-based ecosystem remains the decision about an adequate pricing model. Despite a large number of publications on platform governance, detailed pricing model analyses remain rare. In this explorative paper, we conduct a literature review, studying 62 relevant papers to explore the pricing impact factors to create a foundation for future research of price models in the under-researched setting of the Industrial Internet of Things (IIoT). The most relevant pricing factors and their distinctive characteristics are summed up in a multi-dimensional taxonomy. The developed taxonomy includes 13 impact factors and 38 characteristics of platform pricing. Our findings enable the decomposition and understanding of price models for their future improvement.
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Hashemi, Atiye Sadat, Andreas Bär, Saeed Mozaffari, and Tim Fingscheidt. "Improving Transferability of Generated Universal Adversarial Perturbations for Image Classification and Segmentation." In Deep Neural Networks and Data for Automated Driving, 171–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-01233-4_6.
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AbstractAlthough deep neural networks (DNNs) are high-performance methods for various complex tasks, e.g., environment perception in automated vehicles (AVs), they are vulnerable to adversarial perturbations. Recent works have proven the existence of universal adversarial perturbations (UAPs), which, when added to most images, destroy the output of the respective perception function. Existing attack methods often show a low success rate when attacking target models which are different from the one that the attack was optimized on. To address such weak transferability, we propose a novel learning criterion by combining a low-level feature loss, addressing the similarity of feature representations in the first layer of various model architectures, with a cross-entropy loss. Experimental results on ImageNet and Cityscapes datasets show that our method effectively generates universal adversarial perturbations achieving state-of-the-art fooling rates across different models, tasks, and datasets. Due to their effectiveness, we propose the use of such novel generated UAPs in robustness evaluation of DNN-based environment perception functions for AVs.
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Li, Mingxiao. "A High-Efficiency Knowledge Distillation Image Caption Technology." In Proceeding of 2021 International Conference on Wireless Communications, Networking and Applications, 912–17. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-2456-9_92.
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AbstractImage caption is wildly considered in the application of machine learning. Its purpose is describing one given picture into text accurately. Currently, it uses the Encoder-Decoder architecture from deep learning. To further increase the semantic transmitted after distillation by feature representation, this paper proposes a knowledge distillation framework to increase the results of the teacher section, extracting features by different semantic levels from different fields of view, and the loss function adopts the method of label normalization. Handle unmatched image-sentence pairs. In order to achieve the purpose of a more efficient process. Experimental results prove that this knowledge distillation architecture can strengthen the semantic information transmitted after distillation in the feature representation, achieve a more efficient training model on less data, and obtain a higher accuracy rate.
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Lorch, Christopher, and Bernd Lüdemann-Ravit. "A New IT Architecture for the Digital Factory." In Advances in Automotive Production Technology – Towards Software-Defined Manufacturing and Resilient Supply Chains, 219–29. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-27933-1_21.
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AbstractIn general, current systems for the Digital Factory implement a product-process-resource (PPR) data model in a monolithic rich-client/server architecture with a single database persistence layer. Common data objects are the product bills of material, descriptions of the production processes, or the resource structure, e.g. bill of equipment. The main drawback of the current monolithic architecture is the slow rate of development, which prevents fast adoption of the software to the new production planning process (i.e., due to new technologies for the transformation of the automotive industry with the goal of electrification) is not possible. Furthermore, time-consuming and error-prone export-import operations characterize the collaboration of the engineering supply chain. Mercedes-Benz has created a new IT system architecture for their Digital Factory. The core idea of this architecture is a module-based approach. Each planning step has its own module, e.g. product analysis, layout planning or cost calculation. One single module consists of a server-based business logic, a web-based user interface and its own database. Each module is the source of master data objects that originate from the corresponding planning step and refers to data objects from predecessor planning steps. The single modules communicate mostly via KAFKA. The usage of a model based application engine allows the fast creation of different modules. Best-of-breed third-party systems for specific planning steps can be integrated into the system architecture. Web technologies allow suppliers to access the Mercedes-Benz systems directly for a fully integrated supplier collaboration. Roll-out has started and has already led to significant efficiencies.
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Aburasain, R. Y., E. A. Edirisinghe, and M. Y. Zamim. "A Coarse-to-Fine Multi-class Object Detection in Drone Images Using Convolutional Neural Networks." In Digital Interaction and Machine Intelligence, 12–33. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-11432-8_2.
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AbstractMulti-class object detection has a rapid evolution in the last few years with the rise of deep Convolutional Neural Networks (CNNs) learning based, in particular. However, the success approaches are based on high resolution ground level images and extremely large volume of data as in COCO and VOC datasets. On the other hand, the availability of the drones has been increased in the last few years and hence several new applications have been established. One of such is understanding drone footage by analysing, detecting, recognizing different objects in the covered area. In this study conducted, a collection of large images captured by a drone flying at a fixed altitude in a desert area located within the United Arab Emirates (UAE) is given and it is utilised for training and evaluating the CNN networks to be investigated. Three state-of-the-art CNN architectures, namely SSD-500 with VGGNet-16 meta-architecture, SSD-500 with ResNet meta-architecture and YOLO-V3 with Darknet-53 are optimally configured, re-trained, tested and evaluated for the detection of three different classes of objects in the captured footage, namely, palm trees, group-of-animals/cattle and animal sheds in farms. Our preliminary experiments revealed that YOLO-V3 outperformed SSD-500 with VGGNet-16 by a large margin and has a considerable improvement as compared to using SSD-500 with ResNet. Therefore, it has been selected for further investigation, aiming to propose an efficient coarse-to-fine object detection model for multi-class object detection in drone images. To this end, the impact of changing the activation function of the hidden units and the pooling type in the pooling layer has been investigated in detail. In addition, the impact of tuning the learning rate and the selection of the most effective optimization method for general hyper-parameters tuning is also investigated. The result demonstrated that the multi-class object detector developed has precision of 0.99, a recall of 0.94 and an F-score of 0.96, proving the efficiency of the multi-class object detection network developed.
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Kruschke, Thomas, Theresa Riedelsheimer, and Kai Lindow. "Considering LCA in System Architectures of Smart-Circular PSS." In Lecture Notes in Mechanical Engineering, 694–702. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-28839-5_78.
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AbstractThe realization of smart-circular Product-Service Systems has theoretically promising advantages compared to traditional products. Nevertheless, the sustainability improvement, especially for the ecological dimension is not yet satisfactorily proved. In this paper, the authors examined the current state of research within a systematic literature review with a specific focus on the overlap of the topics: Life Cycle Assessment, Model-Based Systems Engineering, Product-Service Systems, and Circular Economy. The aim is to analyze the potential of a proactive quantification of the ecological impact in an early stage during the development of smart-circular PSS – the system architecture definition. As a result of the systematic review, 27 relevant papers were identified and analyzed and the findings are presented in a structured way. The main finding is that the current state of the art in this research field still is in the conceptualization stage. In addition, a proactive approach is rare and circularity is not considered to its fullest. Quantified use cases do not draw the system boundaries Cradle-to-Cradle and not every of the 9R-strategies is considered. Furthermore, the potentials and challenges of the revealed research gap are summarized.
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Taylor-Pirie, Emilie. "Introduction: Stories of Science and Empire." In Empire Under the Microscope, 1–35. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84717-3_1.
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AbstractIn this introduction, Taylor-Pirie appraises the intersections of the ‘imaginative architecture of science and empire’ by examining how, as a fledging medical discipline at the fin de siècle, parasitology entered into significant encounters and exchanges with the literary and historical imagination. Introducing readers to Nobel Prize–winning parasitologist Ronald Ross (1857–1932), Taylor-Pirie lays the foundations for the rest of the book by examining how forms such as poetry and biography, genres such as imperial romance and detective fiction, and modes such as adventure and the Gothic together informed how tropical diseases, their parasites, and their vectors were understood in relation to race, gender, and nation. In addition to considering the contemporaneous public understanding of science, she also explores how parasitologists were often engaged in writing their own histories of the discipline, a practice that led to a predominantly white, predominantly male understanding of science that finds a legacy in gender disparities in STEM and biases in popular histories of medicine in favour of a mode of ‘heroic biography’. She provides a brief critical overview of the field of literature and science and places her methodology and the field in the context of contemporary topics like the Covid-19 pandemic, Black Lives Matter protests, and the heritage culture wars.
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Paviotti, Marco, Simon Cooksey, Anouk Paradis, Daniel Wright, Scott Owens, and Mark Batty. "Modular Relaxed Dependencies in Weak Memory Concurrency." In Programming Languages and Systems, 599–625. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-44914-8_22.
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AbstractWe present a denotational semantics for weak memory concurrency that avoids thin-air reads, provides data-race free programs with sequentially consistent semantics (DRF-SC), and supports a compositional refinement relation for validating optimisations. Our semantics identifies false program dependencies that might be removed by compiler optimisation, and leaves in place just the dependencies necessary to rule out thin-air reads. We show that our dependency calculation can be used to rule out thin-air reads in any axiomatic concurrency model, in particular C++. We present a tool that automatically evaluates litmus tests, show that we can augment C++ to fix the thin-air problem, and we prove that our augmentation is compatible with the previously used compilation mappings over key processor architectures. We argue that our dependency calculation offers a practical route to fixing the longstanding problem of thin-air reads in the C++ specification.
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Liu, Zidong, Yan Li, and Xiao Xiao. "Predicting the Vitality of Stores Along the Street Based on Business Type Sequence via Recurrent Neural Network." In Computational Design and Robotic Fabrication, 326–36. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-8637-6_29.
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AbstractThe rational planning of store types and locations to maximize street vitality is essential in real estate planning. Traditional business planning relies heavily on the subjective experience of developers. Currently, developers have access to low-resolution urban data to support their decision making, and researchers have done much image-based machine learning research from the scale of urban texture. However, there is still a lack of research on the functional layout with shop-level accuracy. This paper uses a sequence-based neural network (RNN) to explore the relationship between the sequence of store types along a street and its commercial vitality. Currently, the use of RNNs in the architectural and urban fields is very rare. We use customer review data of 80streets from O2O platforms to represent the store vitality degree. In the machine learning model, the input is the sequence of store types on the street, and the output is the corresponding sequence of business vitality indexes. After training and evaluation, the model was shown to have acceptable accuracy. We further combined this evaluation model with a genetic algorithm to develop a business planning optimization tool to maximize the overall street business value, thus guiding real estate business planning at a high resolution.
Conference papers on the topic "Race Model Architecture"
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Nisar, Farhan, Samad Baseer, and Arshad khan. "Survey on ARIMA Model Workloads in a DataCenter with respect to Cloud Architecture." In 2019 International Symposium on Recent Advances in Electrical Engineering (RAEE). IEEE, 2019. http://dx.doi.org/10.1109/raee.2019.8887075.
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Hower, Derek R., Blake A. Hechtman, Bradford M. Beckmann, Benedict R. Gaster, Mark D. Hill, Steven K. Reinhardt, and David A. Wood. "Heterogeneous-race-free memory models." In ASPLOS '14: Architectural Support for Programming Languages and Operating Systems. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2541940.2541981.
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Ur, Rahman Khalil, Gyunyoung Heo, Man Cheol Kim, and Muhammad Zubair. "Formulation and Reliability Feature Analysis of Analog, Digital and Hybrid I&C Architectures for Research Reactors." In 2014 22nd International Conference on Nuclear Engineering. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/icone22-30375.
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Optimized design of Instrumentation and Control (I&C), having rationally good reliability features like high availability, low spurious trip rate and low cost, is very important for safety and economical use of nuclear reactors. The demand for optimization becomes more significant in case of small size educational or research reactor due to less margin of cost. The aim of study, in this article, is to develop analog, digital and hybrid architectures for reactor protection I&C system and identification of suitable one for research reactor. The reliability feature analysis of proposed architectures has been performed in three parts (i) analytical analysis for redundancy (ii) Bayesian network model for estimation channel failure λdc and (iii) unavailability or Probability of Failure on Demand (PFD) for each I&C system architecture. It is found here that 2oo3 (2 out of 3) architecture is highly suitable for research reactor as it has low nuisance process trip rate, rational availability (reasonable high) and low probable to CCF failure, if compared with other ones. Results have shown that hybrid configuration can perform better than analog, digital architectures. This research would be helpful for the designers to consider appropriate model with defined cost and availability for their design.
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Kim, Changhee, Kyongsu Yi, and Jaeyong Park. "Hierarchical Motion Planning and Control Algorithm of Autonomous Racing Vehicles for Overtaking Maneuvers." In WCX SAE World Congress Experience. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2023. http://dx.doi.org/10.4271/2023-01-0698.
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<div class="section abstract"><div class="htmlview paragraph">This paper describes a hierarchical motion planning and control framework for overtaking maneuvers under racing circumstances. Unlike urban or highway autonomous driving conditions, race track driving requires longer prediction and planning horizons in order to respond to upcoming corners at high speed. In addition, the subject vehicle should determine the optimal action among possible driving modes when opponent vehicles are present. In order to meet these requirements and secure real time performance, a hierarchical architecture for decision making, motion planning, and control for an autonomous racing vehicle is proposed. The supervisor determines whether the subject vehicle should stay behind the preceding vehicle or overtake, and its direction when overtaking. Next, a high level trajectory planner generates the desired path and velocity profile in a receding horizon fashion. In order to reduce the computational burden despite maintaining a sufficiently long planning horizon, a low fidelity kinematic vehicle model is utilized for the planner. Finally, a model predictive control (MPC) based low level trajectory tracker generates the lateral and longitudinal control inputs. A high fidelity dynamic vehicle model is introduced to provide a high quality control input for a relatively short control horizon compared with the motion planner. Simulation results demonstrate that the proposed algorithm successfully controls the subject vehicle to deal with preceding opponent vehicles under racing track environments.</div></div>
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Isuyama, Vivian Kimie, and Bruno De Carvalho Albertini. "Comparison of Convolutional Neural Network Models for Mobile Devices." In Workshop em Desempenho de Sistemas Computacionais e de Comunicação. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/wperformance.2021.15724.
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In recent years mobile devices have become an important part of our daily lives and Deep Convolutional Neural Networks have been performing well in the task of image classification. Some considerations have to be made when running a Neural Network inside a mobile device such as computational complexity and storage size. In this paper, common architectures for image classification were analyzed to retrieve the values of accuracy rate, model complexity, memory usage, and inference time. Those values were compared and it was possible to show which architecture to choose from considering mobile restrictions.
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Matchision, Lauren. "Sustaining Educational Equity: Architecture Development Programs as Transformative Models to Increase Inclusivity." In 2019 ACSA Fall Conference. ACSA Press, 2019. http://dx.doi.org/10.35483/acsa.fall.19.13.
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The desire to increase inclusivity in the field of architecture is concurrent with a perceptible growing trend in the United States in which many institutions of higher education have begun to take a closer look at student enrollment in the realization that various degree programs, including architecture, have historically lacked representation from people of color. Emerging architecture pipeline programs are poised to erode the demographic status quo by creating opportuniti es to engage historically underrepresented students while they are still in high school. Many of the explicit and implicit competencies these programs impart are valuable additions toward increasing the likelihood of more underrepresented students successfully applying to study architecture at the university level. These programs are only a small part of a growing number of efforts intended to address long-standing inequiti es in architecture education. This paper aims to assess such programs in light of Sharon Sutton’s imperative to achieve and sustain educational equity set forth in her recent book, When Ivory Towers Were Black: A Story About Race in America’s Cities and Universities. This paper first briefly identifies numerous diversity, equity, and inclusion initiatives currently taking hold in the discipline and profession of architecture. Next, it carefully examines Sutton’s account of the Columbia University School of Architecture’s attempt to transform the demographic status quo. Lastly, it considers the lessons learned from the experiment and applies them to emerging pipeline programs, referred to here as Architecture Development Programs, ultimately seeking to explore successful methods to attract, educate, and support historically under represented young people in the classroom and the profession.
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Saad, Ali, Ali Usman, Saad Arif, and Marcus Liwicki. "Bearing Fault Detection Scheme Using Machine Learning for Condition Monitoring Applications." In International Conference on Mechanical, Automotive and Mechatronics Engineering. Aksaray: ECER, 2023. http://dx.doi.org/10.53375/icmame.2023.137.
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Bearings are the significant components among the rolling machine elements subjected to high wear and tear. The timely detection of faults in such components rotating at higher frequencies can save substantial maintenance costs and production setbacks. Physical examination and fault detection by human experts is always challenging at runtime. Predictive maintenance and real-time condition monitoring are gaining higher utility with the advent of suitable instrumentation and machine learning classifiers. A convolutional neural network (CNN) based bearing fault detection scheme is developed in this research work. The acquired sensory data of vibration signals are converted into the frequency domain and then fed to the classifier for spectral feature extraction and fault classification. The CNN architecture is trained and tested using a bearing dataset available online. The model is further tested and validated with the data acquired from an indigenously designed bearing test rig. The proposed scheme has successfully detected inner and outer race faults and no fault or normal state. This multiclass fault classification has shown promising results with 97.68% accuracy, 96.9% precision, 99.14% sensitivity, 98.01% F1-score, and 93.65% specificity. The achieved results validate the utility of the proposed detection system. Hence the presented scheme has deployment potential for real-time condition monitoring and predictive maintenance applications.
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Khan, Zurwa, Amine Meziou, Reza Tafreshi, Matthew Franchek, and Karolos Grigoriadis. "Automated Subsea Architecture Optimization Using Low-Dimensional Multiphase Flow Models." In ASME 2019 38th International Conference on Ocean, Offshore and Arctic Engineering. American Society of Mechanical Engineers, 2019. http://dx.doi.org/10.1115/omae2019-96293.
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Abstract Due to the global increase in energy demand, the need for economic oil and gas production is rising more than ever. Therefore, it is necessary to ensure that subsea architecture designs are economical and safety oriented. While numerous challenges are encountered during subsea system’s installation and operation phases, most of these challenges can be avoided by ensuring an economical and reliable design. For a safe and cost-effective design and operating scenario, it is essential to predict the hydraulic and thermal behavior of multiphase fluid encountered in petroleum pipelines for a range of conditions. This cannot be accomplished by empirical models, which are dependent on limited data available. Consequently, mechanistic low-dimensional models have been used for two-phase gas-liquid steady-state flow. However, mechanistic low-dimensional models assume adiabatic conditions, which is rarely the case in subsea architectures, which encounter cold surroundings. Therefore, to predict the temperature-based characteristics of multiphase flow in environments with thermal gradients, a thermal model has been developed and validated with experimental data. 80% of the validation data was predicted by this developed thermal model with error difference of less than 30%. The developed two-phase gasliquid thermal model was merged with Beggs and Brill hydraulic multiphase flow model to predict the overall behavior of two-phase gas-liquid flow, and used to develop an optimal model-based multi-well subsea architecture design. A case study of a four-well subsea system was used to demonstrate the automated subsea architecture optimization technique. Through this case study, it was shown that approximately 23% of savings in pipelines procurement could be made relative to the conventional designing approach. Industry standards, safety factors, and multiphase flow models were used to design jumpers and place the manifold for a subsea multi-well system. Merging hydraulic and thermal multiphase flow models showed the effect of temperature on the flow, which led to an optimized design for the subsea insulation in which issues such as wax deposition can be prevented. The resulting optimized subsea architecture was then implemented in Simscape® environment to obtain the transient response. Along with optimized subsea architecture automated design, the developed thermal model has the potential to be used for real-time prediction of two-phase flow rate, pressure drop and void fraction as virtual sensors to provide economical alternative to expensive and impractical hardware sensors. Furthermore, the developed model can also be used to design effective control strategies for multiphase flow regulation in jumpers and prevention of backflow at the manifold.
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Kwon, Hyukjoon, and Monika Ivantysynova. "System and Thermal Modeling for a Novel On-Road Hydraulic Hybrid Vehicle by Comparison With Measurements in the Vehicle." In ASME/BATH 2017 Symposium on Fluid Power and Motion Control. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/fpmc2017-4303.
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Hydraulic hybrid powertrains, which can be applied to many types of vehicles including cars, have several important advantages over electric hybrids, such as lower costs, higher power density, and more regenerative energy available from braking. There have been various investigations for hydraulic hybrid architectures and there always exists room for improvement in terms of performance and efficiency. In order to achieve improved performance and efficiency, a novel hydraulic hybrid transmission architecture has recently been suggested in Maha Fluid Power Research Center, which is implemented in the platform of 1999 Range Rover. Previous studies of the Maha hydraulic hybrid vehicle (HHV) mainly focused on the optimization of system components and controller. In order to further study and optimize hydraulic hybrid architectures, the thermal behavior has to be considered as well. A few existing thermal studies on other hydraulic systems have mostly focused on steady state characteristics due to the difficulty of simulating the unsteady state conditions. In this paper, a novel approach to thermal modeling of HHV for a novel HHV architecture is presented. The results have been validated with the measured data collected while driving the vehicle. The thermal model utilizes the flow rate and pressure obtained from the hydraulic system model and calculates the system temperature at different locations. In order to capture the rapid transition of the hydraulic system in HHV, a novel simulation scheme considering the flow direction for the control volume inputs is applied in the presented study. In addition, the presented model considers compressible flow in order to improve the accuracy of the model.
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Sharad, M., Vijaya Sankara P. Rao, and P. Mandal. "A New Double Data Rate(DDR) Dual-Mode Duobinary Transmitter Architecture." In 2011 24th International Conference on VLSI Design: concurrently with the 10th International Conference on Embedded Systems Design. IEEE, 2011. http://dx.doi.org/10.1109/vlsid.2011.52.
Full textReports on the topic "Race Model Architecture"
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Tschirhart, V., S. Pehrsson, N. Wodicka, J. A. Percival, C. W. Jefferson, T. Peterson, and R G Berman. Geophysical contributions to a synthesis of western Churchill geology and metallogeny. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/330639.
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The geophysical data sets available for the western Churchill Province have had a bearing on the understanding of its structure, evolution and metal endowment. New data were acquired and interpreted during the Geo-mapping for Energy and Minerals (GEM) Program (2008-2020). Regional, high-resolution aeromagnetic, and targeted gravity and magnetotelluric surveys were collected in GEM, in conjunction with geological mapping projects, in order to provide control on bedrock features beneath widespread glacial overburden and flat-lying sedimentary basins. Quantitative estimates of three-dimensional geometry were obtained in key areas through geophysical models integrating the geophysical characteristics with local rock property measurements. These geophysical data sets contributed to new knowledge and interpretations in three related research fields: 1) location and nature of Rae cratonmp;gt;'s boundaries within the western Churchill Province; 2) definition of internal Rae architecture; and 3) identification of reactivated structures controlling gold and uranium mineralization. The new data, models and emerging tectonic and metallogenic frameworks will serve as guides for future exploration in this remote, complex, challenging region.
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Weller, Joel I., Derek M. Bickhart, Micha Ron, Eyal Seroussi, George Liu, and George R. Wiggans. Determination of actual polymorphisms responsible for economic trait variation in dairy cattle. United States Department of Agriculture, January 2015. http://dx.doi.org/10.32747/2015.7600017.bard.
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The project’s general objectives were to determine specific polymorphisms at the DNA level responsible for observed quantitative trait loci (QTLs) and to estimate their effects, frequencies, and selection potential in the Holstein dairy cattle breed. The specific objectives were to (1) localize the causative polymorphisms to small chromosomal segments based on analysis of 52 U.S. Holstein bulls each with at least 100 sons with high-reliability genetic evaluations using the a posteriori granddaughter design; (2) sequence the complete genomes of at least 40 of those bulls to 20 coverage; (3) determine causative polymorphisms based on concordance between the bulls’ genotypes for specific polymorphisms and their status for a QTL; (4) validate putative quantitative trait variants by genotyping a sample of Israeli Holstein cows; and (5) perform gene expression analysis using statistical methodologies, including determination of signatures of selection, based on somatic cells of cows that are homozygous for contrasting quantitative trait variants; and (6) analyze genes with putative quantitative trait variants using data mining techniques. Current methods for genomic evaluation are based on population-wide linkage disequilibrium between markers and actual alleles that affect traits of interest. Those methods have approximately doubled the rate of genetic gain for most traits in the U.S. Holstein population. With determination of causative polymorphisms, increasing the accuracy of genomic evaluations should be possible by including those genotypes as fixed effects in the analysis models. Determination of causative polymorphisms should also yield useful information on gene function and genetic architecture of complex traits. Concordance between QTL genotype as determined by the a posteriori granddaughter design and marker genotype was determined for 30 trait-by-chromosomal segment effects that are segregating in the U.S. Holstein population; a probability of <10²⁰ was used to accept the null hypothesis that no segregating gene within the chromosomal segment was affecting the trait. Genotypes for 83 grandsires and 17,217 sons were determined by either complete sequence or imputation for 3,148,506 polymorphisms across the entire genome. Variant sites were identified from previous studies (such as the 1000 Bull Genomes Project) and from DNA sequencing of bulls unique to this project, which is one of the largest marker variant surveys conducted for the Holstein breed of cattle. Effects for stature on chromosome 11, daughter pregnancy rate on chromosome 18, and protein percentage on chromosome 20 met 3 criteria: (1) complete or nearly complete concordance, (2) nominal significance of the polymorphism effect after correction for all other polymorphisms, and (3) marker coefficient of determination >40% of total multiple-regression coefficient of determination for the 30 polymorphisms with highest concordance. The missense polymorphism Phe279Tyr in GHR at 31,909,478 base pairs on chromosome 20 was confirmed as the causative mutation for fat and protein concentration. For effect on fat percentage, 12 additional missensepolymorphisms on chromosome 14 were found that had nearly complete concordance with the suggested causative polymorphism (missense mutation Ala232Glu in DGAT1). The markers used in routine U.S. genomic evaluations were increased from 60,000 to 80,000 by adding markers for known QTLs and markers detected in BARD and other research projects. Objectives 1 and 2 were completely accomplished, and objective 3 was partially accomplished. Because no new clear-cut causative polymorphisms were discovered, objectives 4 through 6 were not completed.