Automotive Radars:towards smarter vehicles

Radars are expected to become the main sensors in various civilian applications, especially for autonomous driving. Their success is mainly due to the availability of low cost integrated devices, equipped with compact antenna arrays, and computationally efficient signal processing techniques. This thesis focuses on the study and the development of different deterministic and learning based techniques for colocated multiple-input multiple-output (MIMO) radars. In particular, after providing an overview on the architecture of these devices, the problem of detecting and estimating multiple targets in stepped frequency continuous wave (SFCW) MIMO radar systems is investigated and different deterministic techniques solving it are illustrated. Moreover, novel solutions, based on an approximate maximum likelihood approach, are developed. The accuracy achieved by all the considered algorithms is assessed on the basis of the raw data acquired from low power wideband radar devices. The results demonstrate that the developed algorithms achieve reasonable accuracies, but at the price of different computational efforts. Another important technical problem investigated in this thesis concerns the exploitation of machine learning and deep learning techniques in the field of colocated MIMO radars. In this thesis, after providing a comprehensive overview of the machine learning and deep learning techniques currently being considered for use in MIMO radar systems, their performance in two different applications is assessed on the basis of synthetically generated and experimental datasets acquired through a commercial frequency modulated continuous wave (FMCW) MIMO radar. Finally, the application of colocated MIMO radars to autonomous driving in smart agriculture is illustrated.

Controlo unfalsified em sistemas MIMO

Com o crescente progresso tecnológico, surgem sistemas mais eficientes, mas também mais complexos e não-lineares. Isto torna-se mais evidente em sistemas Multi-Input Multi-Output (MIMO), devido a diferentes efeitos que uma entrada possa ter sobre diversas saídas. Para estes sistemas, a obtenção de modelos matemáticos que capturem, com precisão aceitável, a dinâmica do sistema, torna-se cada vez mais complexa e custosa. Sendo que muitos dos sistemas utilizados hoje em dia são MIMO, a diminuição na precisão dos modelos matemáticos é uma adversidade à eficiência dos sistemas de controlo. Isto deve-se a grande parte dos métodos de projeto de controladores terem como base o modelo do sistema. O trabalho realizado nesta dissertação pretende desenvolver uma estrutura de supervisão para sistemas MIMO, com base em controlo Unfalsified, ou Unfalsified Control (UC). Este consiste numa abordagem de controlo adaptativo, cujo processo de adaptação se traduz na seleção de um controlador, de entre um conjunto pré-determinado. Em cada momento é selecionado o controlador que mais se adequa ao objetivo de controlo pretendido. A utilização de UC representa uma possível solução para o problema apresentado, pois utiliza apenas dados experimentais recolhidos do funcionamento do processo. Assim, contorna a necessidade da existência de modelos do processo. Existem, no entanto, dificuldades associadas à comutação de controladores, pelo que este trabalho pretende também desenvolver uma estrutura de Bumpless Transfer (BT), de forma a reduzir estes efeitos. Finalmente, a utilização de dados experimentais implica que a aplicação de UC a um processo está apenas limitada ao ajuste dos parâmetros do sistema de supervisão, e à existência de um conjunto de controladores adequados.

Movement of Input and Output Prices of Rice in Kerala and its Impact on Area, Yield and Outp

Rice is the most extensively cultivated crop in the world, particularly concentrated in Asia and the Far East. Asian countries together make up for as much as 91.80 per cent of the world production of rice in 1986. The main objective of the present study is to analyse the rice economy of Kerala over time and space at the State, district and taluk level. The thesis analyses the trends in area, yield and total production of rice during the three seasons in the state, districts and taluks and studies the trends in input and output prices of rice and coconut in the state, districts and taluks. The researcher estimates the impact of input and output prices on area, yield and total output of rice in the state, districts and selected taluks and examines the conversion of paddy field into coconut garden and rubber plantation.

Vom Input zum Output

Infolge der durch die internationalen Schulvergleichstests eingeleiteten empirischen Wende in der Erziehungswissenschaft hat sich die Aufmerksamkeit vom Input schulischen Lehrens und Lernens zunehmend auf die Ergebnisse (Output) bzw. Wirkungen (Outcomes) verlagert. Die Kernfrage lautet nun: Was kommt am Ende in der Schule bzw. im Unterricht eigentlich heraus? Grundlegende Voraussetzung ergebnisorienterter Steuerung schulischen Unterrichts ist die Formulierung von Bildungsstandards. Wie Bildungsstandards mit Kompetenzmodellen und konkreten Aufgabenstellungen im Unterricht des Faches "Politik & Wirtschaft" verknüpft werden können, wird in diesem Beitrag einer genaueren Analyse unterzogen. Vor dem Hintergrund bildungstheoretischer Vorstellungen im Anschluss an Immanuel Kant kommen dabei das Literacy-Konzept der Pisa-Studie sowie die "Dokumentarische Methode" nach Karl Mannheim zur Anwendung.

Input usage, output mix and industry deregulation: an analysis of the Australian dairy manufacturing industry

In this paper we estimate a Translog output distance function for a balanced panel of state level data for the Australian dairy processing sector. We estimate a fixed effects specification employing Bayesian methods, with and without the imposition of monotonicity and curvature restrictions. Our results indicate that Tasmania and Victoria are the most technically efficient states with New South Wales being the least efficient. The imposition of theoretical restrictions marginally affects the results especially with respect to estimates of technical change and industry deregulation. Importantly, our bias estimates show changes in both input use and output mix that result from deregulation. Specifically, we find that deregulation has positively biased the production of butter, cheese and powders.

An extensible automated protein annotation tool: standardizing input and output using validated XML

Motivation: There is a frequent need to apply a large range of local or remote prediction and annotation tools to one or more sequences. We have created a tool able to dispatch one or more sequences to assorted services by defining a consistent XML format for data and annotations. Results: By analyzing annotation tools, we have determined that annotations can be described using one or more of the six forms of data: numeric or textual annotation of residues, domains (residue ranges) or whole sequences. With this in mind, XML DTDs have been designed to store the input and output of any server. Plug-in wrappers to a number of services have been written which are called from a master script. The resulting APATML is then formatted for display in HTML. Alternatively further tools may be written to perform post-analysis.

Input and output modality effects in immediate serial recall

In immediate recall tasks, visual recency is substantially enhanced when output interference is low (Cowan, Saults, Elliott, & Moreno, 2002; Craik, 1969) whereas auditory recency remains high even under conditions of high output interference. Ibis auditory advantage has been interpreted in terms of auditory resistance to output interference (e.g., Neath & Surprenant, 2003). In this study the auditory-visual difference at low output interference re-emerged when ceiling effects were accounted for, but only with spoken output. With written responding the auditory advantage remained significantly larger with high than with low output interference. These new data suggest that both superior auditory encoding and modality-specific output interference contribute to the classic auditory-visual modality effect.

Variable selection algorithm for the construction of MIMO operating point dependent neurofuzzy networks

An input variable selection procedure is introduced for the identification and construction of multi-input multi-output (MIMO) neurofuzzy operating point dependent models. The algorithm is an extension of a forward modified Gram-Schmidt orthogonal least squares procedure for a linear model structure which is modified to accommodate nonlinear system modeling by incorporating piecewise locally linear model fitting. The proposed input nodes selection procedure effectively tackles the problem of the curse of dimensionality associated with lattice-based modeling algorithms such as radial basis function neurofuzzy networks, enabling the resulting neurofuzzy operating point dependent model to be widely applied in control and estimation. Some numerical examples are given to demonstrate the effectiveness of the proposed construction algorithm.

Tri-state single-phase integrated inverters with input to output power decoupling control

Researches on control for power electronics have looked for original solutions in order to advance renewable resources feasibility, specially the photovoltaic (PV). In this context, for PV renewable energy source the usage of compact, high efficiency, low cost and reliable converters are very attractive. In this context, two improved simplified converters, namely Tri-state Boost and Tri-state Buck-Boost integrated single-phase inverters, are achieved with the presented Tri-state modulation and control schemes, which guarantees the input to output power decoupling control. This feature enhances the field of single-phase PV inverters once the energy storage is mainly inductive. The main features of the proposal are confirmed with some simulations and experimental results. © 2012 IEEE.

An Input-Process-Output Approach to Interorganizational Teams: The Influence of Work Group Diversity, Trust and Shared Leadership on Communication Network and Team Outputs.

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.

Comparing Input- and Output-Oriented Measures of Technical Efficiency to Determine Local Returns to Scale in DEA Models

This paper shows how one can infer the nature of local returns to scale at the input- or output-oriented efficient projection of a technically inefficient input-output bundle, when the input- and output-oriented measures of efficiency differ.