Готові списки джерел за темами / DRIVING FACTOR

Добірка наукової літератури з теми "DRIVING FACTOR"

Автор: Grafiati
Опубліковано: 11 вересня 2023

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Статті в журналах з теми "DRIVING FACTOR"

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Trinh,, Pham T. T., and Le P. A. Nhan,. "The Global Factors Driving Common Inflation In ASEAN." GLOBAL BUSINESS FINANCE REVIEW 28, no. 4 (August 31, 2023): 90–103. http://dx.doi.org/10.17549/gbfr.2023.28.4.90.

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Purpose: This study investigates the comovements of inflation across ASEAN countries and identifies the global factors driving the common inflation dynamics of the region. Design/methodology/approach: The study uses a two-step approach. The dynamic latent factor model is first employed to estimate the common inflation of the region in the period between 2000Q1 and 2022Q2. In the second step, a bound test approach to autoregressive distributed lag (ARDL) methodology is employed to estimate the model of common inflation, which is constructed based on the aggregate supply - aggregate demand (AS-AD) framework. Findings: The study finds a common factor of inflation across ASEAN countries. The analysis of variance decomposition indicates the significant role of common inflation in the variations of individual countries' inflation. World economic growth, oil price change, non-fuel commodity price change, and trade openness are the main drivers of ASEAN common inflation in both short and long terms. Research limitations/implications: The study focuses mainly on supply-side factors, although some demand-side factors are involved. Future studies should pay more concerns on the trade linkages among regional countries and the similarities in goals in the region. Originality/value: The study examines the common inflation component across ASEAN countries, which has not been sufficiently investigated. It also evaluates the drivers at the global level of common inflation, which has limited empirical evidence.
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Zhang, Hong Wu, Lin Yun Shi, Zi Rui Lan, and Jia Hui Yin. "Regional Difference and its Influencing Factors of China's CO2 Emission Changes." Advanced Materials Research 524-527 (May 2012): 3655–61. http://dx.doi.org/10.4028/www.scientific.net/amr.524-527.3655.

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Abstract. Regional difference of China's CO2 emission is basically in line with the trend of China's economic development that the emission is higher in the eastern coastal areas and lower in the western inland areas. The characteristic of the changes of the total CO2 emission is that the growth rate significantly accelerated after 2000. The basic factor which acts as a drive of CO2 emission increase is economic scale factor and the energy saving factor contributes to the decrease of CO2 emission. The driving power of the population factor and energy conversion factor is weak especially the influence of energy conversion factor is very instable. All the provinces are driven by positive driving force in economic scale factor and most provinces with great driving power are located in the eastern coastal areas. All the provinces are driven by positive driving force without expectation in energy conversion factor and most provinces whose energy saving efficiency improvement is of range small are driven poorly are located in the inland. Provinces are mostly driven positively in population size factor and this is related with size and orientation of driving force and population growth. The reason of the great difference of energy conversion factor is connected with energy consumption scale and change of CO2 emission energy unit consumption.
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Wu, Chaozhong, Wenhui Chu, Hui Zhang, and Türker Özkan. "Interactions between Driving Skills on Aggressive Driving: Study among Chinese Drivers." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 31 (October 14, 2018): 10–20. http://dx.doi.org/10.1177/0361198118755683.

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Aggressive driving has attracted significant attention recently with the increase in related road traffic collisions occurring in China. This study aims to investigate the effect of driving skills on aggressive driving behaviors and traffic accidents to find implications for traffic safety improvement in China. A total of 735 Chinese drivers were recruited to complete a self-reported survey including demographic information, the translated Driver Skill Inventory (DSI), and Driver Aggression Indicator Scale (DAIS). Exploratory factor analysis was first conducted to investigate the factor structures of DSI and DAIS among Chinese drivers. Unlike the two-factor solution (i.e., perceptual-motor and safety skills) found in other studies, the current study result revealed a three-factor solution (i.e., perceptual-motor, safety, and emotional control skills) of DSI. Then, the interaction between DSI factors on DAIS factors, demographic variables, and the number of self-reported traffic accidents and offenses was tested by using moderated regression methods. The results revealed the interaction between perceptual-motor skills and safety skills on aggressive warnings committed by drivers themselves. The interactive effect between safety skills and emotional control skills on perceived aggressive warnings was also found. The results suggested that higher ratings of safety skills are essential for buffering the effect of high-level perceptual-motor skills and emotional control skills on aggressive driving in China. In conclusion, policy makers should be interested in understanding the effect of Chinese drivers’ skills on the aggression drivers committed and conceived in traffic. Successful intervention strategies should include all skill factors in the driver training contents.
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Patterson, Loretta, Nadia Mullen, Arne Stinchcombe, Bruce Weaver, and Michel Bédard. "Measuring the impact of driving status: The Centre for Research on Safe Driving–Impact of Driving Status on Quality of Life (CRSD-IDSQoL) tool." Canadian Journal of Occupational Therapy 86, no. 1 (February 2019): 30–39. http://dx.doi.org/10.1177/0008417418824980.

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Background. Driving an automobile is often considered an activity of daily living and is crucial to quality of life for many individuals. Following driving cessation, quality of life may become compromised. Purpose. The Centre for Research on Safe Driving–Impact of Driving Status on Quality of Life (CRSD-IDSQoL) was designed to measure various elements of quality of life and how those elements are affected by driving status. Method. The CRSD-IDSQoL was cross-sectionally administered to a convenience sample of 114 individuals (mean age 65.8 years). Exploratory factor analysis was used to examine the factor structure. Findings. The results supported three factors. Following adjustments for conceptual fit, Cronbach’s alphas for the Community Mobility, Emotional, and Resources and Safety domains were .82, .84, and .74, respectively. Community Mobility was positively associated with distance driven per week. Implications. The CRSD-IDSQoL may be a useful tool to study quality-of-life impacts of driving cessation. Further evaluation of the tool is warranted.
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mahmodzadeh, mahmod, and mehdi fathabadi. "Driving Factors of Total Factor Productivity in Iranian Manufacturing Industries." Journal of Research in Economic Modeling 7, no. 26 (March 1, 2017): 141–65. http://dx.doi.org/10.18869/acadpub.jemr.7.26.141.

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Schweizer, Karl, and Siegbert Reiß. "On the Contextual Conditions Driving a Difficulty Factor." International Journal of Statistics and Probability 8, no. 5 (July 29, 2019): 1. http://dx.doi.org/10.5539/ijsp.v8n5p1.

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This paper reports three simulation studies conducted to identify the contextual conditions leading to the observation of a difficulty factor in confirmatory factor analysis. The data of each study were generated to show one underlying source of responding only whereas the difficulties of the simulated items constituting the contextual condition were varied. The first study showed that a broad range of difficulties of items was insufficient for driving a difficulty factor. The second study revealed that very large and small difficulties of the same size could lead to a difficulty factor if the confirmatory factor model included two correlated factors. In the third study a subgroup of simulated items showed very large difficulties of the same size while the difficulties of the other simulated item were varied. In this study almost all combinations of difficulties led to the observation of a difficulty factor that was correlated or uncorrelated with the genuine factor.
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Hwa, Mei Yin, Tai Yi Yu, Wen Chung Hsu, and Chien An Chen. "Establishment of Typical Driving Patterns for Light-Duty Vehicles on Different Roads in Hsin-Chu Area of Taiwan." Advanced Materials Research 356-360 (October 2011): 1505–9. http://dx.doi.org/10.4028/www.scientific.net/amr.356-360.1505.

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This study utilized the car chasing method to chase 86 light-duty vehicles on seven major roads in the Shin-Chu area and establish the typical driving patterns for various roads. The 23 parameters that associated with the driving were considered to elucidate the features of driving patterns. This work examined two manners, corrected Euclidean distance and traditional Euclidean distance methods, to elucidate a representative driven cycle. In the screening procedure of the typical driven cycle, factor analysis was applied to correct Euclidean distance and examine the 23 variables of driving conditions. The results indicated that the first five of the 23 principal components explained at least 94% of the variance for seven roads. The physical interpretation based on factor analysis was better than the traditional Euclidean distance method, so the results of factor analysis were used to select the typical driven cycle. The average speeds were 34.1 kmh-1 for the city road; 36.8, 26.1 and 30.4 kmh-1 for county roads 118, 120 and 122; 38.7 and 36.5 kmh-1/ for provincial roads 1 and 3; 85.9 kmh-1 for freeway.
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Strahan, Robert F., Cletus R. Mercier, Joyce M. Mercier, and Michael W. O'Boyle. "Personality Structure of Elderly Drivers." Perceptual and Motor Skills 85, no. 2 (October 1997): 747–55. http://dx.doi.org/10.2466/pms.1997.85.2.747.

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This paper reports the factor structure of a 37-item personality questionnaire intended to be predictive of driving performance in elderly persons. Subjects were 191 persons 63 years of age or older, about half of whom also were given perceptual/cognitive tasks and drove on a closed driving course. Although the personality questionnaire did not predict driving skill, the factor structure of the questionnaire is of interest. Of several factor analyses, the most satisfactory was a 2-factor solution. We interpreted the approximately orthogonal factors as measuring what we labeled Competence and Emotionality.
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Carvalho, Janessa O., Beth Springate, Rachel A. Bernier, and Jennifer Davis. "Psychometrics of the AAN Caregiver Driving Safety Questionnaire and contributors to caregiver concern about driving safety in older adults." International Psychogeriatrics 30, no. 3 (October 2, 2017): 355–64. http://dx.doi.org/10.1017/s1041610217001727.

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ABSTRACTBackground:The American Academy of Neurology (AAN) updated their practice parameters in the evaluation of driving risk in dementia and developed a Caregiver Driving Safety Questionnaire, detailed in their original manuscript (Iverson Gronseth, Reger, Classen, Dubinsky, & Rizzo, 2010). They described four factors associated with decreased driving ability in dementia patients: history of crashes or citations, informant-reported concerns, reduced mileage, and aggressive driving.Method:An informant-reported AAN Caregiver Driving Safety Questionnaire was designed with these elements, and the current study was the first to explore the factor structure of this questionnaire. Additionally, we examined associations between these factors and cognitive and behavioral measures in patients with mild cognitive impairment or early Alzheimer's disease and their informants.Results:Exploratory factor analysis revealed a four-component structure, consistent with the theory behind the AAN scale composition. These four factor scores also were significantly associated with performance on cognitive screening instruments and informant reported behavioral dysfunction. Regressions revealed that behavioral dysfunction predicted caregiver concerns about driving safety beyond objective patient cognitive dysfunction.Conclusions:In this first known quantitative exploration of the scale, our results support continued use of this scale in office driving safety assessments. Additionally, patient behavioral changes predicted caregiver concerns about driving safety over and above cognitive status, which suggests that caregivers may benefit from psychoeducation about cognitive factors that may negatively impact driving safety.
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Xin-gang, Zhao, and Wang Wei. "Driving force for China’s photovoltaic industry output growth: Factor-driven or technological innovation-driven?" Journal of Cleaner Production 274 (November 2020): 122848. http://dx.doi.org/10.1016/j.jclepro.2020.122848.

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Дисертації з теми "DRIVING FACTOR"

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CHAUHAN, VIKAS. "SOCIAL MEDIA." Thesis, DELHI TECHNOLOGICAL UNIVERSITY, 2021. http://dspace.dtu.ac.in:8080/jspui/handle/repository/18357.

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PURPOSE: The main purpose of this research paper is to determine the important characteristics of social media, advantages, disadvantages, risks, and roles during the covid-19 pandemic. And also to find out from common people through questionnaires whether they think social media is one of the main diving factor of a business or a startup.  METHODOLOGY: Secondary evidence gathered from findings in online social media apps and resources, websites, research papers, interview forms mailed to business development managers, and self-made questionnaire. Also case studies of companies who took help of social media to regain their lost audience are there in this paper as well.  FINDINGS After going through qualitative data we found out how much social media is important for a business/startup growth and development. And in questionnaire after taking responses from 100 people and then analysing it, we found that almost 80%+ responders responded in such a way that it confirmed the social media is one of the most important driving factor of a business and a Startup.
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Finamore, Kevin. "Motion Cueing Algorithm Development in a 2DOF Driving Simulator: a Driving Behaviour-Centered Approach." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2018.

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I simulatori di guida sono strumenti altamente tecnologici che permettono di svolgere attività di ricerca in vari ambiti quali la psicologia, la medicina e l’ingegneria. Tuttavia, affinché i dati ottenuti mediante le simulazioni siano rapportabili alla loro controparte reale, la fedeltà delle componenti del simulatore di guida deve essere elevata. Questo lavoro tratta del miglioramento del sistema di restituzione del movimento nel simulatore a due gradi di libertà (2DOF) SIMU-LACET Driving Simulator, costruito e sviluppato presso il laboratorio LEPSIS dell’IFSTTAR (Istituto Francese delle Scienze e Tecnologie dei Trasporti, dello Sviluppo e delle Reti), in particolare nella sua sede di Parigi – Marne-la-Vallée. Si è deciso di andare a riprogettare la parte software del sistema di restituzione del movimento (motion cueing), operando su due elementi principali: lo scale factor (fattore di scala) applicato agli impulsi dinamici provenienti dal modello veicolare e i Motion Cueing Algorihms (MCA, algoritmi di restituzione del movimento), questo per entrambi i gradi di libertà. Si è quindi intervenuti sul modello esistente implementato in MATLAB-Simulink nello specifico blocco del motion cueing sul surge (traslazione longitudinale) e sul yaw (imbardata). Riguardo lo scale factor, è stata introdotta una metodologia per creare uno scale factor non lineare in forma esponenziale, tale da migliorare la restituzione degli impulsi meno ampi, pur rispettando i limiti fisici della piattaforma di movimento. Per quanto concerne il MCA, si sono vagliate diverse transfer function dell’algoritmo classico. La scelta finale dei MCA e la validazione del motion cueig in genere è stata effettuata mediante due esperimenti ed il giudizio dei soggetti che vi hanno partecipato. Inoltre, in virtù dei risultati del primo esperimento, si è investigata l’influenza che la strategia in merito al cambio delle marce avesse sulla percezione del movimento da parte del guidatore.
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Smetters, Harriet L. "Factor analyses of the Alcadd Test and the Manson Evaluation for DUI drivers /." The Ohio State University, 1986. http://rave.ohiolink.edu/etdc/view?acc_num=osu1487267546983199.

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Maisel, Sabrina, and Sabrina Maisel. "The Role of Alternative Epidermal Growth Factor Receptor Trafficking in Driving Cancer Progression." Diss., The University of Arizona, 2017. http://hdl.handle.net/10150/624472.

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The Epidermal Growth Factor Receptor (EGFR) is associated with a variety of cancers, including brain, lung, cervix, renal and breast. It is part of a family of receptors known as the ErbB receptors (ErbB1/EGFR, ErbB2/HER2, ErbB3/HER3, and ErbB4/HER4), transmembrane proteins found on epithelial cells responsible for a multitude of signaling events. In cancers, EGFR is frequently mutated or improperly expressed, upregulated in more than 50 percent of basal-like cancers. Mutations commonly promote constitutive activation or increase receptor recycling. In basal-like breast cancers such as triple negative breast cancer (TNBC), named for the lack of hormone receptors (estrogen and progesterone) and the HER2 receptor, EGFR is highly upregulated and associated with a variety of oncogenic activity, including increased proliferation and migration, and inhibition of cell death. Changes in these pathways are predicated on altered trafficking and activation of EGFR, events driven by variation in stimuli and interacting partners, such as other ErbB family members or oncogenic adaptor proteins such as MUC1, a member of the mucin family. In TNBC, upon stimulus with epidermal growth factor (EGF), EGFR colocalizes with MUC1 in intracellular vesicles distributed throughout the cytoplasm. These intracellular vesicles are associated with early endosomes, as indicated by the presence of early endosome antigen 1 (EEA1). Association with MUC1 prolongs the presence of EGFR in these vesicles, as EGFR's stay is significantly reduced in cells lacking MUC1. Retention in these vesicles by MUC1 inhibits trafficking of EGFR to the lysosome for degradation and is also associated with an increase in EGF-dependent migratory ability. Introduction of late endosome inhibitors (thereby preventing lysosomal targeting) increases migration in the absence of MUC1, the same effect as in the presence of MUC1. Further, inhibition of retrograde trafficking significantly decreases the rate of migration and changes cellular distribution of filopodia corresponding to migratory ability in MUC1-containing cells. Taken together, these data indicate that MUC1 is responsible for altering EGFR trafficking by retaining EGFR in EEA1-positive vesicles for prolonged periods, allowing for increased signal transduction through retrograde trafficking of EGFR and structural reorganization promoting a migratory phenotype. Loss of the polarity protein Llgl1 is associated with alterations in EGFR trafficking, promoting highly diffuse EGFR distribution throughout the cytoplasm versus along basolateral membranes. These changes in trafficking are also associated with increases in AKT and dual-phosphorylated-ERK signal transduction, both downstream targets of activated EGFR. Altering localization of EGFR to other membranes and intracellular vesicles without inducing polarity loss through a point mutation at amino acid 667 was found to also upregulate the AKT pathway. Mislocalization driven by polarity loss or point mutation in the basolateral targeting domain is sufficient to increase migration speeds of non-cancerous epithelial cell lines in vitro. This increased oncogenic activity is likely attributed to increased nuclear localization of the transcription factor TAZ (transcription co-activator with a PDZ-binding domain), whose nuclear translocation is associated with increased stem-like properties such as migration and survival. Together, these data reveal the oncogenic potential caused by alterations in EGFR trafficking that occur when polarity is lost or EGFR is improperly associated with proteins that promote changes to canonical EGFR localization and degradation, such as MUC1.
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Phan, Alexandra. "Identification of MMP-9 as a Driving Factor in SARS-CoV-2 Entry." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42771.

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Since its emergence in December 2019, SARS-CoV-2 has infected over 200 million people globally. SARS-CoV-2 spike (S) decorates the viral envelope and is responsible for facilitating viral entry into the host cell. To mediate membrane fusion, S must be proteolytically cleaved. For the closely related SARS-CoV S, cleavage at the host cell surface must be facilitated by the serine protease TMPRSS2. We demonstrated that SARS-CoV-2 S can facilitate fusion independent of TMPRSS2 and sought to identify other proteases capable of driving SARS-CoV-2 S-mediated fusion. We show that the ADAMs and MMP inhibitor GI 254023X is capable of substantially reducing SARS-CoV-2 S-mediated syncytium formation. Additionally, we identified MMP-9, a protein target of GI 254023X, as a host protease capable of enhancing SARS-CoV-2 lentivirus entry in HEK293T-ACE2 cells. These results implicate ADAM and MMP proteases, in particular MMP-9, as potential antiviral drug targets against COVID-19 pathogenesis.
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Jung, Heejin. "A comparison of driving characteristics and environmental characteristics using factor analysis and k-means clustering algorithm." Diss., Virginia Tech, 2012. http://hdl.handle.net/10919/28778.

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The dissertation aims to classify drivers based on driving and environmental behaviors. The research determined significant factors using factor analysis, identified different driver types using k-means clustering, and studied how the same drivers map in each classification domain. The research consists of two study cases. In the first study case, a new variable is proposed and then is used for classification. The drivers were divided into three groups. Two alternatives were designed to evaluate the environmental impact of driving behavior changes. In the second study case, two types of data sets were constructed: driving data and environmental data. The driving data represents driving behavior of individual drivers. The environmental data represents emissions and fuel consumption estimated by microscopic energy and emissions models. Significant factors were explored in each data set using factor analysis. A pair of factors was defined for each data set. Each pair of factors was used for each k-means clustering: driving clustering and environmental clustering. Then the factors were used to identify groups of drivers in each clustering domain. In the driving clustering, drivers were grouped into three clusters. In the environmental clustering, drivers were clustered into two groups. The groups from the driving clustering were compared to the groups from the environmental clustering in terms of emissions and fuel consumption. The three groups of drivers from the driving clustering were also mapped in the environmental domain. The results indicate that the differences in driving patterns among the three driver groups significantly influenced the emissions of HC, CO, and NOx. As a result, it was determined that the average target operating acceleration and braking did essentially influence the amount of emissions in terms of HC, CO, and NOx. Therefore, if drivers were to change their driving behavior to be more defensive, it is expected that emissions of HC, CO, and NOx would decrease. It was also found that spacing-based driving tended to produce less emissions but consumed more fuel than other groups, while speed-based driving produced relatively more emissions. On the other hand, the defensively moderate drivers consumed less fuel and produced fewer emissions.
Ph. D.
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Ali, Ahmed M. "DRIVING SIMULATION AND REACTION TIME INVESTIGATION ON DRIVER FOOTEDNESS." University of Akron / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=akron1561991269668204.

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Yan, Kenneth. "Examination of the associations between different measures of driving exposures and sleepiness as a risk factor for motor vehicle crashes." Thesis, The University of Sydney, 2004. https://hdl.handle.net/2123/28024.

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While sleepiness has been extensively studied previously to determine if it is a risk factor for motor vehicle crashes, the importance of controlling for driving exposure has often been overlooked. On the other hand, measures of driving exposure have been controversial in studies on other risk factors for motor vehicle crashes. Driving time and driving distance are the two that have been studied most, but it is still unclear as to which offers as a better measure of driving exposure. We aim to firstly study the association between driving time and sleepiness and the association between driving distance and sleepiness. We then aim to examine the two associations together to see whether driving time or driving distance is a more appropriate measure of driving exposure to be controlled for in future studies.
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Foster, Tammy. "Water Availability as the Driving Factor of Growth and Physiological Function of Co-occurring Scrub Species in Central Florida." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5020.

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Florida scrub is a xeromorphic upland shrub community dominated by evergreen oaks that resprout after fire, occurring on moderately to excessively well-drained nutrient-poor sand. Scrub is home to several threatened and endangered animal species (e.g., Florida scrub-jay, gopher tortoise, and indigo snake) and rare and endemic plants. Urban development and agriculture has greatly reduced and fragmented scrub habitat, and because of this Florida scrub is considered one of the most endangered ecosystems in the United States. Climate change is a further threat to Florida scrub. Under a warmer and drier climate, scrub species will be exposed to more frequent and more severe droughts. In order to understand how scrub will respond to a changing climate, we must first have a better understanding of how scrub species respond to climate and water availability. In this dissertation, I use a combination of dendrochronology and plant physiological techniques to examine species responses to climate and water availability. In chapter two, I use dendrochronology to examine the importance of seasonal climate on growth of three co-occurring species in Florida scrub, myrtle oak (Quercus myrtifolia Willd.), Chapman oak (Quercus chapmanii Sarg.), and south Florida slash pine (Pinus elliottii Engelmann var. densa Little & K.W. Dorman). This is the first dendrochronology study on co-occurring scrub species. Therefore, my first goal was to ask whether Chapman oak and myrtle oak put on distinct annual rings with year to year variability that would enable successful crossdating. Because I found that each species does have annual rings that can be crossdated, my second goal was to ask how growth in each species responds to climate and its extremes, drought and extreme precipitation. Growth in both oaks was positively correlated with spring precipitation, while slash pine total and latewood growth was positively correlated with April and September precipitation. Slash pine earlywood growth was positively correlated associated with increased winter precipitation. In all three species, growth was sensitive to both annual and spring droughts. However, only slash pine exhibited increased growth with precipitation associated with tropical weather during July-September. Earlywood growth of slash pine was positively correlated with the Ni[ntilde]o 3.4 index: colder, wetter winters tended to be associated with increased earlywood growth. The between-species differences in response to seasonal climate may be due to differences in growth phenology. For both oaks, the climatic limiting factor was water availability in the spring, which is when the majority of radial growth occurs. By contrast, for slash pine, growth was limited by precipitation in the spring and late summer, its peak growth period. During the period for which we have a dendrochronological record (1920 to present), precipitation in April has become increasingly correlated with growth for all three species; as it has become the driest spring month during this period. In chapter three, I use dendrochronology to determine the climate-growth relationships of the dominant oak in Florida scrub, myrtle oak, for five sites occurring on three different scrub ridges in central Florida. My goals were twofold: 1) to ask whether the climate-growth responses of myrtle oak were robust across sites and 2) to ask how myrtle oak growth was affected by droughts (determined on both seasonal and annual basis). Myrtle oak growth increased with increased spring precipitation; temperature had little effect on myrtle oak growth. The growth response of myrtle oak to moisture availability (measured by the standardized precipitation index (SPI)) in March, April, May, and June, was robust across sites, with the exception of Malabar West. Myrtle oaks at Malabar West grew on poorly drained soils and were less responsive to precipitation and drought than were oaks growing on the other sites. March, April, May, and June SPI explained between 21.5 to 58.3% of the variation in myrtle oak growth for each site. Seasonal droughts explained more of the variation in growth than annual droughts. Spring droughts decreased myrtle oak growth at all sites, and drought during the previous summer decreased growth at Malabar West. Drought impacted growth for a single year; growth was normal or greater than normal during the year after drought. These results suggest that the timing of drought is important for myrtle oak growth, and that seasonal measures of drought are more important than annual measures of drought for determining growth impacts. In chapter four, I examine how the distribution and physiological functioning of scrub species vary along the ridge-swale topography at the Kennedy Space Center. Climatic factors often limit species distributions and plant physiological functions over large elevation gradients. However, on small elevation gradients, hydrologic variation may have strong effects on the distribution of species and the physiological function within a species. I used point-intercept sampling along a ridge-swale gradient at Kennedy Space Center on Merritt Island, Florida, to study how species distribution varied over a 1.2 m elevation gradient. Data from water monitoring wells along the elevation gradient were used to ask whether elevation may serve as a proxy for depth to water table. Elevation served as a good proxy for depth to water table; water table depth increased with elevation. I focused especially on understanding how the distribution and physiological functioning of three co-occurring Florida scrub oak species (Chapman oak, sand live oak (Quercus geminata) and myrtle oak) varied along the elevation gradient. Cover of all three scrub oaks increased with increasing elevation. Only sand live oak exhibited differences in physiological functioning along the elevation gradient; individuals at lower elevations were more sensitive to drought than individuals on the ridge. All three oaks exhibited stomatal regulation of water use efficiency drought. Chapman oak did not exhibit decreased photosynthetic activity during drought. Leaf phenology may play a role in the different responses to drought exhibited.
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Whaley, Michael T. "Developing freeway merging calibration techniques for analysis of ramp metering In Georgia through VISSIM simulation." Thesis, Georgia Institute of Technology, 2016. http://hdl.handle.net/1853/55068.

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Freeway merging VISSIM calibration techniques were developed for the analysis of ramp metering in Georgia. An analysis of VISSIM’s advanced merging and cooperative lane change settings was undertaken to determine their effects on merging behavior. Another analysis was performed to determine the effects of the safety reduction factor and the maximum deceleration for cooperative braking parameter on the simulated merging behavior. Results indicated that having both the advanced merging and cooperative lane change setting active produced the best results and that the safety reduction factor had more influence on the merging behavior than the maximum deceleration for cooperative braking parameter. Results also indicated that the on-ramp experienced unrealistic congestion when on-ramp traffic was unable to immediately find an acceptable gap when entering the acceleration lane. These vehicles would form a queue at the end of the acceleration lane and then be unable to merge into the freeway lane due to the speed differential between the freeway and the queued ramp traffic. An Incremental Desired Speed algorithm was developed to maintain an acceptable speed differential between the merging traffic and the freeway traffic. The Incremental Desired Speed algorithm resulted in a smoother merging behavior. Lastly, a ramp meter was introduced and an increase in both the freeway throughput and overall speeds was found. Implications of these findings on the future research is discussed.
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Книги з теми "DRIVING FACTOR"

1

Ernst, Claus-Peter H. Factors Driving Social Network Site Usage. Wiesbaden: Springer Fachmedien Wiesbaden, 2015. http://dx.doi.org/10.1007/978-3-658-09918-3.

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name, No. Human factors in driving, seating & vision. Warrendale, PA: Society of Automotive Engineers, 2002.

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Driving simulation forward: Making driving simulators more useful for behavioral research. Washington, D.C.]: U.S. Dept. of Transportation, Federal Highway Administration, 2010.

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Hessler, Peter. Country driving: A journey from farm to factory. New York: Harper, 2010.

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contributor, Alexander Gerson J., ed. Human factors in traffic safety. Tucson, Arizona: Lawyers & Judges Publishing Company, Inc., 2015.

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Abiad, Abdul. Underlying factors driving fiscal effort in emerging market economies. [Washington, D.C.]: International Monetary Fund, Fiscal affairs dept., 2005.

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Cándida, Castro, ed. Human factors of visual and cognitive performance in driving. Boca Raton: Taylor & Francis, 2009.

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8

SAE International Congress & Exposition (1998 Detroit, Mich.). Human factors in driving, vehicle seating, and rear vision. Warrendale, PA: Society of Automotive Engineers, 1998.

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Hessler, Peter. Country driving: A journey through China from farm to factory. New York: Harper, 2010.

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Engineers, Society of Automotive. Human factors in driving and automotive telematics and seat comfort. Warrendale, PA: SAE International, 2006.

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Частини книг з теми "DRIVING FACTOR"

1

Chu, Yueying, and Peng Liu. "Human Factor Risks in Driving Automation Crashes." In HCI in Mobility, Transport, and Automotive Systems, 3–12. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-35678-0_1.

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2

Cole, B. L., and J. D. Maddocks. "Defective colour vision is a risk factor in driving." In Documenta Ophthalmologica Proceedings Series, 471–81. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-011-5408-6_54.

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3

Nagar, Seema, Sameer Gupta, C. S. Bahushruth, Ferdous Ahmed Barbhuiya, and Kuntal Dey. "Homophily - a Driving Factor for Hate Speech on Twitter." In Complex Networks & Their Applications X, 78–88. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-93413-2_7.

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4

Kabene, Stefane, Said Baadel, and Angelika C. Dankert. "Managerial Recruitment Issues in China: The Expatriate Factor." In Leadership, Innovation and Entrepreneurship as Driving Forces of the Global Economy, 431–36. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-43434-6_37.

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Lambrechts, Johannes, and Saurabh Sinha. "Microsensing Networks for Sustainable Cities: Pollution as a Key Driving Factor." In Microsensing Networks for Sustainable Cities, 1–27. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-28358-6_1.

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6

Sun, Jingqi, Hongze Li, Bao Wang, and Sen Guo. "The Change Trend and Driving Factors of Beijing’s Total-Factor Energy Efficiency: An Empirical Study." In Advances in Computer Science, Intelligent System and Environment, 255–63. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23753-9_41.

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7

Song, Jinghua, and Sirui Sun. "Research on Architectural Form Optimization Method Based on Environmental Performance-Driven Design." In Proceedings of the 2020 DigitalFUTURES, 217–28. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4400-6_21.

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AbstractIn the context of contemporary environment and society, the architectural form optimization based on Environmental performance-driven design is a method by using environmental performance data to optimize the architectural form. Its value lies in dealing with the interaction between architecture and environment, and developing architecture with environmental sustainability. This thesis summarizes the similarities and differences between performance-driven form design and traditional bionic form design. The traditional bionic design separates the bionic object from its complex living environment, and its simple imitation tends to fall into the local rather than the global optimum. However, performance-driven design is different from bionic design. It advocates environmental factors as a driving factor rather than a confrontational factor. It is a systematic global optimal method for studying architectural form. This paper puts forward the specific architectural form optimization simulation process based on the performance-driven thought. Taking the multilayer parking building design of the riparian zone on the south bank of Chongqing as an example, the parametric design method is used to obtain architectural optimization form adapted to the environment.
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Barrett, Katherine L., and Gary E. Belovsky. "Invertebrates and Phytoplankton of Great Salt Lake: Is Salinity the Driving Factor?" In Great Salt Lake Biology, 145–73. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-40352-2_6.

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9

Barrios-Rodiles, Miriam, Alicia Viloria-Petit, Kevin R. Brown, Igor Jurisica та Jeffrey L. Wrana. "High-Throughput Screening of Protein Interaction Networks in the TGFβ Interactome: Understanding the Signaling Mechanisms Driving Tumor Progression". У Transforming Growth Factor-β in Cancer Therapy, Volume II, 265–84. Totowa, NJ: Humana Press, 2008. http://dx.doi.org/10.1007/978-1-59745-293-9_18.

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10

Zhang, Changzheng, Hong Ren, and Zhongzhou Zhang. "Study on the Effect of Factor Efficiency on Economic Restructuring Under Supply—Side Driving." In Management for Sustainable and Inclusive Development in a Transforming Asia, 237–54. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8195-3_14.

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Тези доповідей конференцій з теми "DRIVING FACTOR"

1

Sirois, William, Todd Dawson, Martin Moore-Ede, Acacia Aguirre, and Udo Trutschel. "Assessing Driver Fatigue as a Factor in Road Accidents." In Driving Assessment Conference. Iowa City, Iowa: University of Iowa, 2007. http://dx.doi.org/10.17077/drivingassessment.1287.

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2

"Driving Factor of Long Mach Launchers' Technical Progress." In 55th International Astronautical Congress of the International Astronautical Federation, the International Academy of Astronautics, and the International Institute of Space Law. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2004. http://dx.doi.org/10.2514/6.iac-04-v.2.04.

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3

Liu, Lin, Chunyuan Li, Xinze Hua, Yongfu Li, and Lin Liu. "Multi-factor integration based eco-driving optimization of vehicles with same driving characteristics." In 2017 Chinese Automation Congress (CAC). IEEE, 2017. http://dx.doi.org/10.1109/cac.2017.8244015.

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4

Silva, Mariana O., Gabriel P. Oliveira, Danilo B. Seufitelli, Anisio Lacerda, and Mirella M. Moro. "Collaboration as a Driving Factor for Hit Song Classification." In WebMedia '22: Brazilian Symposium on Multimedia and Web. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3539637.3556993.

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5

Stauber, Rudolf, and Markus Baur. "Advanced Material Technologies — A Key Factor for Ultimate Driving Performance." In SAE 2000 World Congress. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2000. http://dx.doi.org/10.4271/2000-01-0418.

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6

Lei, Hu, Xinping Yan, Chaozhong Wu, Ming Zhong, and Yuqian Qi. "Factor Analysis for Characterizing Angry Driving Behaviors of Chinese Drivers." In 14th COTA International Conference of Transportation Professionals. Reston, VA: American Society of Civil Engineers, 2014. http://dx.doi.org/10.1061/9780784413623.236.

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7

Ivanova, Malinka. "Self-assessment activities as factor for driving the learning performance." In THERMOPHYSICAL BASIS OF ENERGY TECHNOLOGIES (TBET 2020). AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0041755.

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8

LIU, Shaojie, Ning WANG, and Xiaoting WANG. "Multi-factor Influenced Integrated Driving Behavior Clustering Analysis Evaluation Model." In 2019 International Conference on Computer, Information and Telecommunication Systems (CITS). IEEE, 2019. http://dx.doi.org/10.1109/cits.2019.8862028.

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9

Athab, Hussain S., and Dylan Dah-Chuan Lu. "Quasi-active power factor correction using transformer-assisted driving voltage." In 2009 IEEE International Symposium on Circuits and Systems - ISCAS 2009. IEEE, 2009. http://dx.doi.org/10.1109/iscas.2009.5118179.

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Yu, Jianglin, and Yun Zhang. "A Driving Early Warning Method Based on Multi-Factor Fusion." In 2021 3rd International Conference on Applied Machine Learning (ICAML). IEEE, 2021. http://dx.doi.org/10.1109/icaml54311.2021.00074.

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Звіти організацій з теми "DRIVING FACTOR"

1

Biagio, Di. L52037 Ductile Fracture Propagation Resistance for Advanced Pipeline Designs. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), January 2008. http://dx.doi.org/10.55274/r0011001.

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The development of a method able to evaluate the ductile fracture behavior on pipelines has been documented. Therefore, methods for the determination of material fracture resistance and crack driving force have been accurately investigated. In particular, the techniques to determine the critical fracture characterizing parameter CTOA (crack tip opening angle) have been reviewed in-depth (back-slotted drop weight tear tests [DWTT], two specimen CTOA tests, etc.), and in view of a future pipe-mill application. For a more reliable CTOA estimate the needed following parameters have been investigated: 1) rotation factor in a DWTT and 2) the material flow stress to be used in dynamic tests. On the other hand, as far as the crack driving force is concerned, a finite element code developed by CSM (PICPRO) has been successfully used to evaluate the correlation between the CTOA inferred by DWT tests and that measured on pipe. In addition PICPRO has been used to determine the driving force acting on pipe in a wide range of operating conditions, finally supplying an appropriate formula for its calculation. Once the driving force and the fracture resistance have been determined their comparison allows crack arrest assessment.
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2

Chierichetti, Maria, Armin Chierichetti, and Fatemeh Davoudi. Design of an Evaluation Plan for Senate Bill 1046. Mineta Transportation Institute, July 2022. http://dx.doi.org/10.31979/mti.2021.2209.

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In an effort to understand and decrease alcohol-impaired driving as a primary collision factor In California, the research team designed an evaluation plan for California Senate Bill 1046 and its focus on ignition interlock devices as a sentence for Driving Under Influence offense. This plan will evaluate whether Senate Bill 1046 affected the Driving Under the Influence crash frequency and severity, and whether sociodemographic and geographic factors influence its effectiveness. This report lays the foundation for the evaluation that will be conducted in 2024. The research team conducted a meta-analysis of the last 12 years of literature and research on ignition interlock programs inside and outside the United States. Based on the findings of this analysis, the recommended evaluation plan of the law revolves around three research questions that focus on the changes in the frequency/severity of DUI-related crashes in California, the impact of the law on recidivism and on interlock installation rates. To respond to these questions, the research team recommends a list of data that should be collected, such as the number of injuries and deaths resulting from alcohol-related motor vehicle accidents, installation rates of ignition interlocks compared to the prior five-year period, the number of individuals who were required to have an ignition interlock device installed who were convicted of an alcohol-related violation, as well as number of lockouts while an interlock is installed. The research team proposed several statistical approaches for the analysis of this data, such as descriptive statistics, time series analysis, analysis of variance, and logistic regression.
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3

Chierichetti, Maria, Armin Chierichetti, and Fatemeh Davoudi. Design of an Evaluation Plan for Senate Bill 1046. Mineta Transportation Institute, July 2022. http://dx.doi.org/10.31979/mti.2022.2209.

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Анотація:
In an effort to understand and decrease alcohol-impaired driving as a primary collision factor In California, the research team designed an evaluation plan for California Senate Bill 1046 and its focus on ignition interlock devices as a sentence for Driving Under Influence offense. This plan will evaluate whether Senate Bill 1046 affected the Driving Under the Influence crash frequency and severity, and whether sociodemographic and geographic factors influence its effectiveness. This report lays the foundation for the evaluation that will be conducted in 2024. The research team conducted a meta-analysis of the last 12 years of literature and research on ignition interlock programs inside and outside the United States. Based on the findings of this analysis, the recommended evaluation plan of the law revolves around three research questions that focus on the changes in the frequency/severity of DUI-related crashes in California, the impact of the law on recidivism and on interlock installation rates. To respond to these questions, the research team recommends a list of data that should be collected, such as the number of injuries and deaths resulting from alcohol-related motor vehicle accidents, installation rates of ignition interlocks compared to the prior five-year period, the number of individuals who were required to have an ignition interlock device installed who were convicted of an alcohol-related violation, as well as number of lockouts while an interlock is installed. The research team proposed several statistical approaches for the analysis of this data, such as descriptive statistics, time series analysis, analysis of variance, and logistic regression.
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4

Shim, D. J., Gery Wilkowski, Mohammed Uddin, Sureshkumar Kalyanam, and P. Mincer. PR-276-094509-R01 Develop Fracture Initiation Criteria for High-Strength Steel Line Pipe Phase II. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), August 2013. http://dx.doi.org/10.55274/r0010072.

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This report summarizes the major findings from a PRCI Project on developing fracture initiation criteria for axial flaws (both through-wall and surface flaws) in high-strength line-pipe materials. This work was originally done on the basis to see if improvements were needed for higher-grade steels, but interestingly there were several outcomes that affect predictions for all piping steels. One of the outcomes of this work is a new correlation between Charpy USE and J-R curve for high-strength materials. Although it is based on limited data, it was demonstrated that there is significant difference compared to the existing correlation. Another interesting finding is the effect of the internal patch on burst pressure of axial through-wall-cracked pipe test. Careful experimental and detailed finite element analyses showed patching affects burst pressure by at least 10-percent which affects the leak-rupture boundary. For axial surface-cracked pipes, the effect of crack shape on the crack-driving force was investigated. Finally, it was demonstrated that the actual axial surface-cracked pipe bulging factor is considerably lower than bulging factor empirically derived at Battelle in the 1970s. If past bulging factor is used for subcritical crack growth (e.g., for SCC or fatigue analyses), the crack growth and start of ductile tearing can be significantly overpredicted. Overall, J-T analysis provided the most accurate results when proper crack-driving forces and J-R curves were used (both for axial through-wall-cracked pipe and axial surface-cracked pipe). This report also includes recommendations for future work.
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5

Gallaher, Michael, Tanzeed Alam, and Nadia Rouchdy. The Impact of Electricity and Water Subsidies in the United Arab Emirates. RTI Press, May 2017. http://dx.doi.org/10.3768/rtipress.2017.pb.0012.1705.

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The United Arab Emirates (UAE) has some of the highest electricity and water consumption rates in the world. A driving factor is the presence of electricity and water subsidies and their impact on the investment in efficiency, technology adoption, and implementation of best practices. Decades of subsidization have made Gulf Cooperation Council businesses some of the world’s most inefficient energy and water consumers, and there is a growing consensus in the UAE that a comprehensive conservation plan is needed. However, for any comprehensive conservation plan to be successful, it must include tariff reform as a cornerstone. The social and political issues associated with tariff reform are not trivial. A comprehensive approach needs to be developed and implemented while energy prices are low and the initial impact on customers can be minimized.
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6

Hauzenberger, Niko, Florian Huber, Gary Koop, and James Mitchell. Bayesian modeling of time-varying parameters using regression trees. Federal Reserve Bank of Cleveland, January 2023. http://dx.doi.org/10.26509/frbc-wp-202305.

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In light of widespread evidence of parameter instability in macroeconomic models, many time-varying parameter (TVP) models have been proposed. This paper proposes a nonparametric TVP-VAR model using Bayesian additive regression trees (BART). The novelty of this model stems from the fact that the law of motion driving the parameters is treated nonparametrically. This leads to great flexibility in the nature and extent of parameter change, both in the conditional mean and in the conditional variance. In contrast to other nonparametric and machine learning methods that are black box, inference using our model is straightforward because, in treating the parameters rather than the variables nonparametrically, the model remains conditionally linear in the mean. Parsimony is achieved through adopting nonparametric factor structures and use of shrinkage priors. In an application to US macroeconomic data, we illustrate the use of our model in tracking both the evolving nature of the Phillips curve and how the effects of business cycle shocks on inflationary measures vary nonlinearly with movements in uncertainty.
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7

Guyer, Gretchen. Factors Driving the Concentration of Ephemeral Flow. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.2955.

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8

Roth, Christian. Design of the In-vehicle Experience. SAE International, June 2022. http://dx.doi.org/10.4271/epr2022012.

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The in-vehicle experience, both physical and digital, is increasingly the differentiating factor between vehicles. Since touch displays, smart surfaces, and internet connectivity are present in most vehicle segments, the growing resemblance of in-vehicle experiences with mobile experiences leads to user expectations on par with smartphones. While manufacturers are faced with providing suitable service offerings that are safe to use, they must also identify services to exclude or limit, without encouraging drivers to resort back to their mobile devices. This increasingly complex in-vehicle experience design process is being shaped by new stakeholders, including operating system providers and application developers. Design of the In-vehicle Experience examines the challenging and changing relationships between manufacturers (that lack in software development and mobile experience design skills) and new stakeholders (that lack the decades of experience designing for the driving context). The report also discusses augmenting and expanding existing guidelines and best practices to address the challenges of modern in-vehicle experience design.
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9

Frydman, Roman, Søren Johansen, Anders Rahbek, and Morten Nyboe Tabor. Asset Prices Under Knightian Uncertainty. Institute for New Economic Thinking Working Paper Series, December 2021. http://dx.doi.org/10.36687/inetwp172.

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We extend Lucas’s classic asset-price model by opening the stochastic process driving dividends to Knightian uncertainty arising from unforeseeable change. Implementing Muth’s hypothesis, we represent participants’ expectations as being consistent with our model’s predictions and formalize their ambiguity-averse decisions with maximization of intertemporal multiple-priors utility. We characterize the asset-price function with a stochastic Euler equation and derive a novel prediction that the relationship between prices and dividends undergoes unforeseeable change. Our approach accords participants’ expectations, driven by both fundamental and psychological factors, an autonomous role in driving the asset price over time, without presuming that participants are irrational.
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10

Coyle, William, Mark Gehlhar, Thomas Hertel, Zhi Wang, and Wusheng Yu. Understanding the Determinants of structural Change in World Food Markets. GTAP Working Paper, September 2000. http://dx.doi.org/10.21642/gtap.wp02.

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This study assesses the interaction between climate change and agricultural trade policies. We distinguish between two dimensions of agricultural trade policy: market insulation and subsidy levels. Building on the previous work of Tsigas, Frisvold and Kuhn (1997) we find that, in the presence of current levels of agricultural subsidies, increased price transmission --as called for under the Uruguay Round Agreement on Agriculture-- reduces global welfare in the wake of climate change. This is due to the positive correlation between productivity changes and current levels of agricultural support. Increases in subsidized output under climate change tend to exacerbate inefficiencies in the global agricultural economy in the absence of market insulation. However, once agricultural subsidies have also been eliminated, price transmission via the global trading system contributes positively to economic adaptation under climate change. products. This may partially explain the relatively slow growth of world grain import demand in recent years. In addition, bilateral agreements with East Asia, NAFTA, and the evolution of the CAP, have all had important impacts on the structure of world food and agricultural trade. The objective of this paper is to assess the relative role of each of the major forces-- consumer demand, factor accumulation, transport costs, and policy change--in driving changes in the composition of world food trade in 1980-1995. To do so, we employ a modified version of the Global Trade Analysis Project (GTAP) model of world trade which permits us to isolate the contribution of each of these related factors to the changing composition of world food trade in a general equilibrium context. We evaluate the relative role of each of these factors by simulating the model backwards in time, from 1995 to 1980 under different assumptions. This general approach, termed “backcasting” (i.e. backwards forecasting), takes as exogenous the basic drivers of change and attempts to explain the resulting change in food trade composition. The model-produced changes in the composition of agricultural and food trade are compared with historical trade data, to determine the relative importance of each factor on the changing composition of food trade. Given limited space, our focus will be on explaining the changes in the global composition of food and agriculture trade. A natural follow-on effort would target specific markets in more detail. This type of backcasting approach was first employed by Gehlhar (1997) who sought to explain the shift in exports of primary commodities to manufactures in East Asia in the 1980's. He calibrated the GTAP model to 1992 data, then implemented shocks to factor endowments and economywide total factor productivity (TFP) in order to force each economy back to its 1982 levels of population, land, labor, human capital, physical capital and technology. By comparing actual and predicted changes in export shares in this period, he found human capital accumulation played a key role in explaining the change in the aggregate composition of East Asian exports. Gehlhar, Hertel and Martin (1994) built on this work in an effort to predict future changes in the pattern of agricultural trade from 1992-2002. They also emphasized the importance of supply-side determinants of agricultural trade. In this paper, we go beyond this earlier work in a number of ways. First, we focus on the composition of agricultural exports, rather than simply looking at the share of agriculture in total trade. Secondly, we incorporate the Cranfield et al. estimates of Rimmer and Powell’s recently developed, implicitly directly additive demand system (nicknamed AIDADS) into the GTAP model. This permits us to better capture the impact of demand-side changes on the pattern of global tr
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