Libri sul tema "PUF Modeling"

Pictures are important parts of communicative acts, along with language, gesture, facial expressions, and props. They express wide ranges of thoughts, make assertions, offer warnings, instructions, and commands. Pictures are also representations. They have meanings, which help explain the range of communicative uses to which they can be put. Modeling the meanings of pictures is accounting for the ways in which pictures manage to be meaningful, with an eye toward how those meanings let us use them as we do. The philosophy of language is the most obvious place to look for tools that model meanings. This book offers an account of the many ways in which pictures can be meaningful, which is inspired by the philosophy of language. Its aim is to do justice to the range of communicative uses to which pictures are put. Two main threads run through the book. The first is the meaning thread: Chapters 2, 4, 5, and 6. It unpacks and models many kinds of pictorial meaning. The other is the parts thread: Chapters 3, 7, and 8. This explains how pictures have meaningful parts, why this matters for understanding their uses in communication, and also how this offers a new way to understand what makes pictorial representations so different from language.

This article discusses the results of a study in Bayesian reliability analysis concerning train door failures in a European underground system over a period of nine years. It examines failure data from forty underground trains, which were delivered to an European transportation company between November 1989 and March 1991. All of the trains were put in service from 20 March 1990 to 20 July 1992. Failure monitoring ended on 31 December 1998. The goal of the study was to find models able to assess the failure history and to predict the number of failures in future time intervals in order to help the company determine the reliability level of the train doors before warranty expiration. The article describes the development and application of a novel bivariate Poisson process as a natural way to extend the usual Poisson models for analysing the occurrence of failures in repairable systems.

Simulation modeling makes use of computational resources in fields that are not of a mathematical nature. The first part of this chapter introduces four phases of the historical development of computation and simulation (C&S) and discusses their relationship to interdisciplinarity. Starting with a pioneering phase, C&S went through disciplinary specialization, ubiquitous diffusion, and a recent infrastructural turn. The second part of the chapter explores aspects of the interdisciplinary dynamics of C&S, especially the interplay between complexity, experimentation, and visualization. Then, C&S is put in relationship to Shinn’s “research technology” and Galison’s “trading zones.” Finally, the chapter observes a recent turn toward network-like interdisciplinary integration.

This chapter first reviews early methodological and theoretical debates regarding the nature of variation above the level of phonology. These debates include whether or not the notion of the linguistic variable can be legitimately extended to morphosyntactic variation; the nature of the relationship between quantitative data and the statistical results based on them and linguistic competence; and what role linguistic introspection should play. The discussion deals with current trends in modeling morphosyntactic variation, or, put differently, with the emerging field of socio-syntax. There are two main responses to the question of where morphosyntactic variation comes from. One perspective involves the postulation of multiple grammars, most prominently in Kroch’s Competing Grammars model. The other relies on the Minimalist operations of feature interpretation and feature checking.

Der Bericht ist ausschließlich als PDF-Dokument erschienen! Inhalt Vorwort 1 Keynote Mobilitätsszenarien und deren Einfluss auf Einsatz und Entwicklung von Kupplungssystemen – Einfluss aktueller Trends auf die Anforderungen an Kupplungssysteme 3 A. Albers, S. Ott, IPEK-Institut für Produktentwicklung am KIT, Karlsruhe Trockenlaufende Kupplungen – energieeffiziente und zukunftsfähige Systeme Trockenlaufende Lamellenkupplungen – Eine neue Option zur Verwirklichung einer hochintegrierten aktiven Drehmomentregelung für konventionelle und elektrifizierte Antriebe 13 F. Nickel, M. Mühlegger, Miba Frictec GmbH, Roitham, Austria Experimental characterization and modeling of automotive dry clutch friction lining wear – Clutch lifetime prediction 25 M. Hoic´, B. Škugor, J. Deur, University of Zagreb, Zagreb; Croatia; A. Tissot, Ford-Werke GmbH, Cologne Analyse des Schädigungs- und Erholungsverhaltens trockenlaufender Friktionspaarungen 37 T. Klotz, S. Ott, A. Albers, IPEK – In...

Dieser VDI-Bericht ist ausschließlich als PDF-Dokument erschienen! Content half of it… Analysis of Drive Trains Model-Based Chiptuning Detection of Diesel Engines 1 M. Hinrichs, P. Pickel, John Deere GmbH, Kaiserslautern R. Isermann, Institute of Automatic Control, Darmstadt An Analysis of the Energy Consumption in the High-Pressure System of an Agricultural Tractor through Modeling and Experiment 9 X. Tian, A. Vacca, Purdue University, West Lafayette, IN, USA; S. Fiorati, F. Pintore, CNH Industrial S.p.A, Modena, Italy Multi-Domain Simulation for the Assessment of the NVH Behaviour of a Tractor with Hydrostatic-Mechanical Power Split Transmission 19 G. Pasch, G. Jacobs, G. Höpfner, J. Berroth, Institute for Machine Elements and Systems Engineering, RWTH Aachen University, Aachen Methods to evaluate steering performance of agricultural tractors 29 S. Liljenberg, M. Frederiksen, T. H. Langer, Danfoss Power Solutions, Nordborg, Denmark Tyres and Soil Soil pressure and pulling be...

Dieser VDI-Bericht ist ausschließlich als PDF-Dokument erschienen! Sie möchten erfahren, was alles an spannenden Themen auf der Tagung in Mannheim präsentiert wurde? Inhalt Jahrmarkt der Innovationen Modellbasierte Folgeregelung für nichtlineare Regelstrecken am Beispiel der Ladedruckregelung – Ein applikationsnaher Entwurf 1 K. Wulff, J. Willkomm, J. Reger, Fachgebiet Regelungstechnik, Technische Universität Ilmenau Nichtlineare modellbasierte prädiktive Regelung der Fahrzeugdynamik in Bezug auf eine aktive Wankstabilisierung und eine Nickreduzierung 3 P. M. Sieberg, S. Blume, S. Reicherts, D. Schramm, Lehrstuhl für Mechatronik, Universität Duisburg-Essen (Doppelpublikation: VDI Verlag Düsseldorf – Springer Nature) Identifikation lokal linearer Modelle am Beispiel der Ladedruckstrecke eines Ottomotors 19 S. Kettlitz, E. Schulz, M. Schultalbers, IAV Automotive Engineering, Gifhorn Generic Sensor Modelling – A Virtual Integration Approach for the Test of ADAS 21 A. Prinz,...

Most users of management software packages don't realize how much effort analysts, designers, programmers, and installers put into creating these solutions. Due to the rapid progress of information technologies, the software and computer hardware of the used systems become outdated quite quickly. After some time, both manufacturing and service enterprises face the dilemma of modernizing the systems in use, including switching to a newer version of the package. But sometimes, as a result of the analysis, it turns out that the amount of necessary changes exceeds 40%. So, should you adapt one of the off-the-shelf versions or perhaps build your own custom cyber-resistant system? The proposed study guide for students, and not only, of "Management, logistics and administration" specialties corresponds to the education of IT system designers in the fields of activity, especially in enterprises, which are so needed in practice. The first part of the manual presents individual examples of computerized control systems as a perspective on the construction of various applications. The second part introduces the reader to a set of tools that help create new and implemented solutions in information technology and engineering. Of particular note is the instruction on how to use the UML language in the creation of flowcharts so that structural sequences of source codes for software solutions can be automatically generated from them. It is worth adding that a valuable addition to this work is a more detailed explanation of the concepts and presentation of formulas, especially in the field of econometrics, which are necessary in the modeling of algorithms of economic phenomena.

Bones are multifunctional passive organs of movement that supports soft tissue and directly attached muscles. They also protect internal organs and are a reserve of calcium, phosphorus and magnesium. Each bone is covered with periosteum, and the adjacent bone surfaces are covered by articular cartilage. Histologically, the bone is an organ composed of many different tissues. The main component is bone tissue (cortical and spongy) composed of a set of bone cells and intercellular substance (mineral and organic), it also contains fat, hematopoietic (bone marrow) and cartilaginous tissue. Bones are a tissue that even in adult life retains the ability to change shape and structure depending on changes in their mechanical and hormonal environment, as well as self-renewal and repair capabilities. This process is called bone turnover. The basic processes of bone turnover are: • bone modeling (incessantly changes in bone shape during individual growth) following resorption and tissue formation at various locations (e.g. bone marrow formation) to increase mass and skeletal morphology. This process occurs in the bones of growing individuals and stops after reaching puberty • bone remodeling (processes involve in maintaining bone tissue by resorbing and replacing old bone tissue with new tissue in the same place, e.g. repairing micro fractures). It is a process involving the removal and internal remodeling of existing bone and is responsible for maintaining tissue mass and architecture of mature bones. Bone turnover is regulated by two types of transformation: • osteoclastogenesis, i.e. formation of cells responsible for bone resorption • osteoblastogenesis, i.e. formation of cells responsible for bone formation (bone matrix synthesis and mineralization) Bone maturity can be defined as the completion of basic structural development and mineralization leading to maximum mass and optimal mechanical strength. The highest rate of increase in pig bone mass is observed in the first twelve weeks after birth. This period of growth is considered crucial for optimizing the growth of the skeleton of pigs, because the degree of bone mineralization in later life stages (adulthood) depends largely on the amount of bone minerals accumulated in the early stages of their growth. The development of the technique allows to determine the condition of the skeletal system (or individual bones) in living animals by methods used in human medicine, or after their slaughter. For in vivo determination of bone properties, Abstract 10 double energy X-ray absorptiometry or computed tomography scanning techniques are used. Both methods allow the quantification of mineral content and bone mineral density. The most important property from a practical point of view is the bone’s bending strength, which is directly determined by the maximum bending force. The most important factors affecting bone strength are: • age (growth period), • gender and the associated hormonal balance, • genotype and modification of genes responsible for bone growth • chemical composition of the body (protein and fat content, and the proportion between these components), • physical activity and related bone load, • nutritional factors: – protein intake influencing synthesis of organic matrix of bone, – content of minerals in the feed (CA, P, Zn, Ca/P, Mg, Mn, Na, Cl, K, Cu ratio) influencing synthesis of the inorganic matrix of bone, – mineral/protein ratio in the diet (Ca/protein, P/protein, Zn/protein) – feed energy concentration, – energy source (content of saturated fatty acids - SFA, content of polyun saturated fatty acids - PUFA, in particular ALA, EPA, DPA, DHA), – feed additives, in particular: enzymes (e.g. phytase releasing of minerals bounded in phytin complexes), probiotics and prebiotics (e.g. inulin improving the function of the digestive tract by increasing absorption of nutrients), – vitamin content that regulate metabolism and biochemical changes occurring in bone tissue (e.g. vitamin D3, B6, C and K). This study was based on the results of research experiments from available literature, and studies on growing pigs carried out at the Kielanowski Institute of Animal Physiology and Nutrition, Polish Academy of Sciences. The tests were performed in total on 300 pigs of Duroc, Pietrain, Puławska breeds, line 990 and hybrids (Great White × Duroc, Great White × Landrace), PIC pigs, slaughtered at different body weight during the growth period from 15 to 130 kg. Bones for biomechanical tests were collected after slaughter from each pig. Their length, mass and volume were determined. Based on these measurements, the specific weight (density, g/cm3) was calculated. Then each bone was cut in the middle of the shaft and the outer and inner diameters were measured both horizontally and vertically. Based on these measurements, the following indicators were calculated: • cortical thickness, • cortical surface, • cortical index. Abstract 11 Bone strength was tested by a three-point bending test. The obtained data enabled the determination of: • bending force (the magnitude of the maximum force at which disintegration and disruption of bone structure occurs), • strength (the amount of maximum force needed to break/crack of bone), • stiffness (quotient of the force acting on the bone and the amount of displacement occurring under the influence of this force). Investigation of changes in physical and biomechanical features of bones during growth was performed on pigs of the synthetic 990 line growing from 15 to 130 kg body weight. The animals were slaughtered successively at a body weight of 15, 30, 40, 50, 70, 90, 110 and 130 kg. After slaughter, the following bones were separated from the right half-carcass: humerus, 3rd and 4th metatarsal bone, femur, tibia and fibula as well as 3rd and 4th metatarsal bone. The features of bones were determined using methods described in the methodology. Describing bone growth with the Gompertz equation, it was found that the earliest slowdown of bone growth curve was observed for metacarpal and metatarsal bones. This means that these bones matured the most quickly. The established data also indicate that the rib is the slowest maturing bone. The femur, humerus, tibia and fibula were between the values of these features for the metatarsal, metacarpal and rib bones. The rate of increase in bone mass and length differed significantly between the examined bones, but in all cases it was lower (coefficient b <1) than the growth rate of the whole body of the animal. The fastest growth rate was estimated for the rib mass (coefficient b = 0.93). Among the long bones, the humerus (coefficient b = 0.81) was characterized by the fastest rate of weight gain, however femur the smallest (coefficient b = 0.71). The lowest rate of bone mass increase was observed in the foot bones, with the metacarpal bones having a slightly higher value of coefficient b than the metatarsal bones (0.67 vs 0.62). The third bone had a lower growth rate than the fourth bone, regardless of whether they were metatarsal or metacarpal. The value of the bending force increased as the animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. The rate of change in the value of this indicator increased at a similar rate as the body weight changes of the animals in the case of the fibula and the fourth metacarpal bone (b value = 0.98), and more slowly in the case of the metatarsal bone, the third metacarpal bone, and the tibia bone (values of the b ratio 0.81–0.85), and the slowest femur, humerus and rib (value of b = 0.60–0.66). Bone stiffness increased as animals grew. Regardless of the growth point tested, the highest values were observed for the humerus, tibia and femur, smaller for the metatarsal and metacarpal bone, and the lowest for the fibula and rib. Abstract 12 The rate of change in the value of this indicator changed at a faster rate than the increase in weight of pigs in the case of metacarpal and metatarsal bones (coefficient b = 1.01–1.22), slightly slower in the case of fibula (coefficient b = 0.92), definitely slower in the case of the tibia (b = 0.73), ribs (b = 0.66), femur (b = 0.59) and humerus (b = 0.50). Bone strength increased as animals grew. Regardless of the growth point tested, bone strength was as follows femur > tibia > humerus > 4 metacarpal> 3 metacarpal> 3 metatarsal > 4 metatarsal > rib> fibula. The rate of increase in strength of all examined bones was greater than the rate of weight gain of pigs (value of the coefficient b = 2.04–3.26). As the animals grew, the bone density increased. However, the growth rate of this indicator for the majority of bones was slower than the rate of weight gain (the value of the coefficient b ranged from 0.37 – humerus to 0.84 – fibula). The exception was the rib, whose density increased at a similar pace increasing the body weight of animals (value of the coefficient b = 0.97). The study on the influence of the breed and the feeding intensity on bone characteristics (physical and biomechanical) was performed on pigs of the breeds Duroc, Pietrain, and synthetic 990 during a growth period of 15 to 70 kg body weight. Animals were fed ad libitum or dosed system. After slaughter at a body weight of 70 kg, three bones were taken from the right half-carcass: femur, three metatarsal, and three metacarpal and subjected to the determinations described in the methodology. The weight of bones of animals fed aa libitum was significantly lower than in pigs fed restrictively All bones of Duroc breed were significantly heavier and longer than Pietrain and 990 pig bones. The average values of bending force for the examined bones took the following order: III metatarsal bone (63.5 kg) <III metacarpal bone (77.9 kg) <femur (271.5 kg). The feeding system and breed of pigs had no significant effect on the value of this indicator. The average values of the bones strength took the following order: III metatarsal bone (92.6 kg) <III metacarpal (107.2 kg) <femur (353.1 kg). Feeding intensity and breed of animals had no significant effect on the value of this feature of the bones tested. The average bone density took the following order: femur (1.23 g/cm3) <III metatarsal bone (1.26 g/cm3) <III metacarpal bone (1.34 g / cm3). The density of bones of animals fed aa libitum was higher (P<0.01) than in animals fed with a dosing system. The density of examined bones within the breeds took the following order: Pietrain race> line 990> Duroc race. The differences between the “extreme” breeds were: 7.2% (III metatarsal bone), 8.3% (III metacarpal bone), 8.4% (femur). Abstract 13 The average bone stiffness took the following order: III metatarsal bone (35.1 kg/mm) <III metacarpus (41.5 kg/mm) <femur (60.5 kg/mm). This indicator did not differ between the groups of pigs fed at different intensity, except for the metacarpal bone, which was more stiffer in pigs fed aa libitum (P<0.05). The femur of animals fed ad libitum showed a tendency (P<0.09) to be more stiffer and a force of 4.5 kg required for its displacement by 1 mm. Breed differences in stiffness were found for the femur (P <0.05) and III metacarpal bone (P <0.05). For femur, the highest value of this indicator was found in Pietrain pigs (64.5 kg/mm), lower in pigs of 990 line (61.6 kg/mm) and the lowest in Duroc pigs (55.3 kg/mm). In turn, the 3rd metacarpal bone of Duroc and Pietrain pigs had similar stiffness (39.0 and 40.0 kg/mm respectively) and was smaller than that of line 990 pigs (45.4 kg/mm). The thickness of the cortical bone layer took the following order: III metatarsal bone (2.25 mm) <III metacarpal bone (2.41 mm) <femur (5.12 mm). The feeding system did not affect this indicator. Breed differences (P <0.05) for this trait were found only for the femur bone: Duroc (5.42 mm)> line 990 (5.13 mm)> Pietrain (4.81 mm). The cross sectional area of the examined bones was arranged in the following order: III metatarsal bone (84 mm2) <III metacarpal bone (90 mm2) <femur (286 mm2). The feeding system had no effect on the value of this bone trait, with the exception of the femur, which in animals fed the dosing system was 4.7% higher (P<0.05) than in pigs fed ad libitum. Breed differences (P<0.01) in the coross sectional area were found only in femur and III metatarsal bone. The value of this indicator was the highest in Duroc pigs, lower in 990 animals and the lowest in Pietrain pigs. The cortical index of individual bones was in the following order: III metatarsal bone (31.86) <III metacarpal bone (33.86) <femur (44.75). However, its value did not significantly depend on the intensity of feeding or the breed of pigs.