Search results for "Bust"
showing 10 items of 1000 documents
Focus on failure avoidance and risk reduction through Variation Mode and Effect Analysis
2009
Variation Mode and Effect Analysis (VMEA) is a quality improvement tool initially thought to help product development engineers focusing on variation. The method was inspired by the wide use of Failure Mode and Effect Analysis (FMEA) in business and industry and the increased attention on robust design. However, FMEA is based on the concept of failure while VMEA is developed on the concept of variation, i.e. it implies a step further toward the awareness of variation and its implications in terms of risk and failures. VMEA helps identifying, scrutinizing and measuring the sources of variation and the way they channel through and impact on important characteristics of the system under study.…
Statistical-based tolerance setting by eliciting the loss function reasoining
2009
An issue still open in the statistical-engineering literature concerns the tolerance allocation, i.e. the setting of admitted limits for critical characteristics or performances of interest of the system under study. A common approach to tolerance allocation is based on the idea of Loss function initially developed by Taguchi. Unfortunately, some obstacles prevent from a full exploitation of the Taguchi approach, since despite its clarity and elegance, it is poorly operational. Based on Taguchi’s proposal, researchers have been more concerned on developing different analytical models of loss function than clarifying the reasoning behind the loss function idea. So there is a missing link for…
New frontiers of Robust Design with applications to motorcycles
2012
Most of the literature on Robust Design has so far focused on making technical performances of products and processes as much insensitive as possible to the action of noise factors, often representing physical variables. When studying the human-machine interaction, we can try to achieve system robustness to “human” noise factors in general, by considering variations in: psychological impact, body shapes and cognitive psychology in usage. These are new frontiers of Robust Design. This work started from three research lines, namely Kansei Engineering, Robust Ergonomic Design, and Human Machine interface design, the former involving cognitive and psychological aspects within product placement,…
Geospatial analysis of drought tendencies in the Carpathians as reflected in a 50-year time series
2019
Climate change is one of the most important issues of anthropogenic activities. The increasing drought conditions can cause water shortage and heat waves and can influence the agricultural production or the water supply of cities. The Carpathian region is also affected by this phenomenon; thus, we aimed at identifying the tendencies between 1960 and 2010 applying the CarpatClim (CC) database. We calculated the trends for each grid point of CC, plotted the results on maps, and applied statistical analysis on annual and seasonal level. We revealed that monthly average temperature, maximum temperature and evapotranspiration had similar patterns and had positive trends in all seasons except aut…
A vision-based fully automated approach to robust image cropping detection
2020
Abstract The definition of valid and robust methodologies for assessing the authenticity of digital information is nowadays critical to contrast social manipulation through the media. A key research topic in multimedia forensics is the development of methods for detecting tampered content in large image collections without any human intervention. This paper introduces AMARCORD (Automatic Manhattan-scene AsymmetRically CrOpped imageRy Detector), a fully automated detector for exposing evidences of asymmetrical image cropping on Manhattan-World scenes. The proposed solution estimates and exploits the camera principal point, i.e., a physical feature extracted directly from the image content th…
Robust Dynamic Comfort Modeling for Motorcycle Riding
2014
Comfort modeling is considered a prerequisite in motorcycle design, primarily to address safety concerns and to position the product on the market. However, a comprehensive methodology for comfort modeling during the earliest development phases of a motorcycle model is still missing. Anthropometrical variation is the main noise factor to consider in comfort modeling in relation to the unavoidable variability of body segments. However, comfort is a subjective concept influencing riders' choice of motorcycle model. This work is a generalization of the robust ergonomic design methodology aimed at designing products whose ergonomic performance is insensitive to anthropometrical variation. This …
On the robust design of unknown inputs Takagi-Sugeno observer
2012
This paper deals with the observer design for Takagi-Sugeno (T-S) fuzzy models subject to unknown inputs and disturbance affecting both states and outputs of the system. Sufficient conditions to design an unknown input T-S observer are given in Linear Matrix Inequalities (LMIs) terms. Relaxations are introduced by using intermediate variables. Numerical example is given to illustrate the effectiveness of the given result.
Robusta binārā klasifikācija ar loģistisko regresiju
2019
Darbs veltīts loģistiskās regresijas izpētei, kas ir viena no populārākajām metodēm, risinot klasifikācijas uzdevumus. Kļūdas atkarīgajā mainīgajā var būtiski ietekmēt klasificēšanas veiktspēju. Darbā uzsvars likts uz robustu loģistiskās regresijas paplašinājumu, kas ir balstīts uz kļūdaino klašu ietveršanu modeļa apmācībā, lai modelis nezaudētu savu klasifikācijas veiktspēju. Modeļa apmācība noris līdzīgi kā loģistiskajā regresijā. Darbā aplūkota gan loģistiskā regresija, gan robustā loģistiskā regresija ar nobīdes parametriem. Abas metodes pielietotas praktiski programmā R Studio uz reāliem datiem. Darba mērķis ir pārbaudīt, kā abas metodes darbojās un salīdzināt sniegtos rezultātus.
Improving Reliability of Road Safety Estimates Based on High Correlated Accident Counts
2007
Calibrating a safety performance function (SPF) with many years of accident data creates a temporal correlation that traditional model calibration procedures cannot deal with. It is well known that generalized estimating equations (GEE) models are able to incorporate trends into accident data and thus overcome difficulties in accounting for correlation; the usual application of GEEs to safety analysis uses robust (or sandwich) estimates of regression coefficients under the independence hypothesis for the working correlation matrix. This practice is justified by the robustness of the GEE procedure against misspecification of the response correlation structure. Nevertheless, with this method…
DECENTRALIZED SUBSPACE PROJECTION IN LARGE NETWORKS
2018
A great number of applications in wireless sensor networks involve projecting a vector of observations onto a subspace dictated by prior information. Accomplishing such a task in a centralized fashion entails great power consumption, congestion at certain nodes, and suffers from robustness issues. A sensible alternative is to compute such projections in a decentralized fashion. To this end, recent works proposed schemes based on graph filters, which compute projections exactly with a finite number of local exchanges among sensor nodes. However, existing methods to obtain these filters are confined to reduced families of projection matrices or small networks. This paper proposes a method tha…