8 resultados para bounded input
em AMS Tesi di Dottorato - Alm@DL - Università di Bologna
Resumo:
In the thesis I exploit an empirical analysis on firm's productivity. I relate the efficiency at plant level with the input market features and I suggest an estimation technique for production function that takes into account firm's liquidity constraints. The main results are three. When I consider services as inputs for manufacturing firm's production process, I find that more competition in service sector affects positively plants productivity and export decision. Secondly liquidity constraints are important for the calculation of firm's productivity because they are a second source of firm's heterogeneity. Third liquidity constraints are important for firm's internationalization
Resumo:
In the recent years, consumers became more aware and sensible in respect to environment and food safety matters. They are more and more interested in organic agriculture and markets and tend to prefer ‘organic’ products more than their traditional counterparts. To increase the quality and reduce the cost of production in organic and low-input agriculture, the 6FP-European “QLIF” project investigated the use of natural products such as bio-inoculants. They are mostly composed by arbuscular mycorrhizal fungi and other microorganisms, so-called “plant probiotic” microorganisms (PPM), because they help keeping an high yield, even under abiotic and biotic stressful conditions. Italian laws (DLgs 217, 2006) have recently included them as “special fertilizers”. This thesis focuses on the use of special fertilizers when growing tomatoes with organic methods in open field conditions, and the effects they induce on yield, quality and microbial rhizospheric communities. The primary objective was to achieve a better understanding of how plant-probiotic micro-flora management could buffer future reduction of external inputs, while keeping tomato fruit yield, quality and system sustainability. We studied microbial rhizospheric communities with statistical, molecular and histological methods. This work have demonstrated that long-lasting introduction of inoculum positively affected micorrhizal colonization and resistance against pathogens. Instead repeated introduction of compost negatively affected tomato quality, likely because it destabilized the ripening process, leading to over-ripening and increasing the amount of not-marketable product. Instead. After two years without any significant difference, the third year extreme combinations of inoculum and compost inputs (low inoculum with high amounts of compost, or vice versa) increased mycorrhizal colonization. As a result, in order to reduce production costs, we recommend using only inoculum rather than compost. Secondly, this thesis analyses how mycorrhizal colonization varies in respect to different tomato cultivars and experimental field locations. We found statistically significant differences between locations and between arbuscular colonization patterns per variety. To confirm these histological findings, we started a set of molecular experiments. The thesis discusses preliminary results and recommends their continuation and refinement to gather the complete results.
Resumo:
The present work is devoted to the assessment of the energy fluxes physics in the space of scales and physical space of wall-turbulent flows. The generalized Kolmogorov equation will be applied to DNS data of a turbulent channel flow in order to describe the energy fluxes paths from production to dissipation in the augmented space of wall-turbulent flows. This multidimensional description will be shown to be crucial to understand the formation and sustainment of the turbulent fluctuations fed by the energy fluxes coming from the near-wall production region. An unexpected behavior of the energy fluxes comes out from this analysis consisting of spiral-like paths in the combined physical/scale space where the controversial reverse energy cascade plays a central role. The observed behavior conflicts with the classical notion of the Richardson/Kolmogorov energy cascade and may have strong repercussions on both theoretical and modeling approaches to wall-turbulence. To this aim a new relation stating the leading physical processes governing the energy transfer in wall-turbulence is suggested and shown able to capture most of the rich dynamics of the shear dominated region of the flow. Two dynamical processes are identified as driving mechanisms for the fluxes, one in the near wall region and a second one further away from the wall. The former, stronger one is related to the dynamics involved in the near-wall turbulence regeneration cycle. The second suggests an outer self-sustaining mechanism which is asymptotically expected to take place in the log-layer and could explain the debated mixed inner/outer scaling of the near-wall statistics. The same approach is applied for the first time to a filtered velocity field. A generalized Kolmogorov equation specialized for filtered velocity field is derived and discussed. The results will show what effects the subgrid scales have on the resolved motion in both physical and scale space, singling out the prominent role of the filter length compared to the cross-over scale between production dominated scales and inertial range, lc, and the reverse energy cascade region lb. The systematic characterization of the resolved and subgrid physics as function of the filter scale and of the wall-distance will be shown instrumental for a correct use of LES models in the simulation of wall turbulent flows. Taking inspiration from the new relation for the energy transfer in wall turbulence, a new class of LES models will be also proposed. Finally, the generalized Kolmogorov equation specialized for filtered velocity fields will be shown to be an helpful statistical tool for the assessment of LES models and for the development of new ones. As example, some classical purely dissipative eddy viscosity models are analyzed via an a priori procedure.
Resumo:
Tracking activities during daily life and assessing movement parameters is essential for complementing the information gathered in confined environments such as clinical and physical activity laboratories for the assessment of mobility. Inertial measurement units (IMUs) are used as to monitor the motion of human movement for prolonged periods of time and without space limitations. The focus in this study was to provide a robust, low-cost and an unobtrusive solution for evaluating human motion using a single IMU. First part of the study focused on monitoring and classification of the daily life activities. A simple method that analyses the variations in signal was developed to distinguish two types of activity intervals: active and inactive. Neural classifier was used to classify active intervals; the angle with respect to gravity was used to classify inactive intervals. Second part of the study focused on extraction of gait parameters using a single inertial measurement unit (IMU) attached to the pelvis. Two complementary methods were proposed for gait parameters estimation. First method was a wavelet based method developed for the estimation of gait events. Second method was developed for estimating step and stride length during level walking using the estimations of the previous method. A special integration algorithm was extended to operate on each gait cycle using a specially designed Kalman filter. The developed methods were also applied on various scenarios. Activity monitoring method was used in a PRIN’07 project to assess the mobility levels of individuals living in a urban area. The same method was applied on volleyball players to analyze the fitness levels of them by monitoring their daily life activities. The methods proposed in these studies provided a simple, unobtrusive and low-cost solution for monitoring and assessing activities outside of controlled environments.
Resumo:
Recently, the increasing interest in organic food products and environmental friendly practices has emphasized the importance of selecting crop varieties suitable for the low-input systems. Additionally, in recent years the relationship between diet and human health has gained much attention among consumers, favoring the investigations on food nutraceutical properties. Among cereals, wheat plays an important role in human nutrition around the world and contributes to the daily intake of essential nutrients such as starch and protein. Moreover, whole grain contains several bioactive compounds that confer to wheat-derived products unique nutraceutical properties (dietary fibre, antioxidants). The present research provided interesting insights for the selection of wheat genotypes suitable for low-input systems and the development of specific breeding programs dedicated to organic farming. The investigation involved 5 old not dwarf genotypes (Andriolo, Frassineto, Gentil rosso, Inallettabile, Verna) and 1 modern dwarf variety (Palesio), grown under biodynamic management, over two consecutive growing seasons (2009/2010, 2010/2011). Results evidenced that under low-input farming some investigated old wheat genotypes (Frassineto, Inallettabile) were comparable to the modern cultivar in terms of whole agronomic performance. As regards the nutritional and nutraceutical properties, some old genotypes (Andriolo, Gentil rosso, Verna) emerged for their relevant content of several investigated phytochemicals (such as insoluble dietary fibre, polyphenols, flavonoids, in vitro antioxidant activity) and nutrients (protein, lipid, minerals). Despite of the low technological features, the six wheat varieties grown under low-input management may efficiently provide raw material for the preparation of traditionally processed bread with valuable sensory and nutritional properties. Results highlighted that old wheat varieties have peculiar phytochemical composition and may be a valuable source of nutraceutical compounds. Some of the genetic material involved in the present study may be used in breeding programs aimed at selecting varieties suitable for low-input farming and rich in health-promoting compounds.
Resumo:
The market’s challenges bring firms to collaborate with other organizations in order to create Joint Ventures, Alliances and Consortia that are defined as “Interorganizational Networks” (IONs) (Provan, Fish and Sydow; 2007). Some of these IONs are managed through a shared partecipant governance (Provan and Kenis, 2008): a team composed by entrepreneurs and/or directors of each firm of an ION. The research is focused on these kind of management teams and it is based on an input-process-output model: some input variables (work group’s diversity, intra-team's friendship network density) have a direct influence on the process (team identification, shared leadership, interorganizational trust, team trust and intra-team's communication network density), which influence some team outputs, individual innovation behaviors and team effectiveness (team performance, work group satisfaction and ION affective commitment). Data was collected on a sample of 101 entrepreneurs grouped in 28 ION’s government teams and the research hypotheses are tested trough the path analysis and the multilevel models. As expected trust in team and shared leadership are positively and directly related to team effectiveness while team identification and interorganizational trust are indirectly related to the team outputs. The friendship network density among the team’s members has got positive effects on the trust in team and on the communication network density, and also, through the communication network density it improves the level of the teammates ION affective commitment. The shared leadership and its effects on the team effectiveness are fostered from higher level of team identification and weakened from higher level of work group diversity, specifically gender diversity. Finally, the communication network density and shared leadership at the individual level are related to the frequency of individual innovative behaviors. The dissertation’s results give a wider and more precise indication about the management of interfirm network through “shared” form of governance.
Resumo:
In recent years, radars have been used in many applications such as precision agriculture and advanced driver assistant systems. Optimal techniques for the estimation of the number of targets and of their coordinates require solving multidimensional optimization problems entailing huge computational efforts. This has motivated the development of sub-optimal estimation techniques able to achieve good accuracy at a manageable computational cost. Another technical issue in advanced driver assistant systems is the tracking of multiple targets. Even if various filtering techniques have been developed, new efficient and robust algorithms for target tracking can be devised exploiting a probabilistic approach, based on the use of the factor graph and the sum-product algorithm. The two contributions provided by this dissertation are the investigation of the filtering and smoothing problems from a factor graph perspective and the development of efficient algorithms for two and three-dimensional radar imaging. Concerning the first contribution, a new factor graph for filtering is derived and the sum-product rule is applied to this graphical model; this allows to interpret known algorithms and to develop new filtering techniques. Then, a general method, based on graphical modelling, is proposed to derive filtering algorithms that involve a network of interconnected Bayesian filters. Finally, the proposed graphical approach is exploited to devise a new smoothing algorithm. Numerical results for dynamic systems evidence that our algorithms can achieve a better complexity-accuracy tradeoff and tracking capability than other techniques in the literature. Regarding radar imaging, various algorithms are developed for frequency modulated continuous wave radars; these algorithms rely on novel and efficient methods for the detection and estimation of multiple superimposed tones in noise. The accuracy achieved in the presence of multiple closely spaced targets is assessed on the basis of both synthetically generated data and of the measurements acquired through two commercial multiple-input multiple-output radars.
Resumo:
In rural and isolated areas without cellular coverage, Satellite Communication (SatCom) is the best candidate to complement terrestrial coverage. However, the main challenge for future generations of wireless networks will be to meet the growing demand for new services while dealing with the scarcity of frequency spectrum. As a result, it is critical to investigate more efficient methods of utilizing the limited bandwidth; and resource sharing is likely the only choice. The research community’s focus has recently shifted towards the interference management and exploitation paradigm to meet the increasing data traffic demands. In the Downlink (DL) and Feedspace (FS), LEO satellites with an on-board antenna array can offer service to numerous User Terminals (UTs) (VSAT or Handhelds) on-ground in FFR schemes by using cutting-edge digital beamforming techniques. Considering this setup, the adoption of an effective user scheduling approach is a critical aspect given the unusually high density of User terminals on the ground as compared to the on-board available satellite antennas. In this context, one possibility is that of exploiting clustering algorithms for scheduling in LEO MU-MIMO systems in which several users within the same group are simultaneously served by the satellite via Space Division Multiplexing (SDM), and then these different user groups are served in different time slots via Time Division Multiplexing (TDM). This thesis addresses this problem by defining a user scheduling problem as an optimization problem and discusses several algorithms to solve it. In particular, focusing on the FS and user service link (i.e., DL) of a single MB-LEO satellite operating below 6 GHz, the user scheduling problem in the Frequency Division Duplex (FDD) mode is addressed. The proposed State-of-the-Art scheduling approaches are based on graph theory. The proposed solution offers high performance in terms of per-user capacity, Sum-rate capacity, SINR, and Spectral Efficiency.