Search results for "Processo"
showing 10 items of 648 documents
Il valore della codificazione nell'evoluzione del processo amministrativo
2011
Analysis of Socio-Spatial Differences in Germany for the Definition of Online Milieus
2017
This research paper is part of a research project that analyses the influence of socioeconomic variables on the usage of online social networks to provide quality ensured social media supported business transactions. The research in this paper contains the analysing of the online milieu groups from the Responsibility-Driven Individuals and the Digital Vanguards, which were defined 2012 as milieu groups for online users in Germany. Both target groups are part of the in Germany well-established approach of lifeworlds and milieus for the differentiation of groups in the society. With such a distinguishing of customer groups, the communication with agents in social media communication will be m…
Exploring parallel capabilities of an innovative numerical method for recovering image velocity vectors field
2010
In this paper an efficient method devoted to estimate the velocity vectors field is investigated. The method is based on a quasi-interpolant operator and involves a large amount of computation. The operations characterizing the computational scheme are ideal for parallel processing because they are local, regular and repetitive. Therefore, the spatial parallelism of the process is studied to rapidly proceed in the computation on distributed multiprocessor systems. The process has shown to be synchronous, with good task balancing and requiring a small amount of data transfer.
Practical considerations for acoustic source localization in the IoT era: Platforms, energy efficiency, and performance
2019
The rapid development of the Internet of Things (IoT) has posed important changes in the way emerging acoustic signal processing applications are conceived. While traditional acoustic processing applications have been developed taking into account high-throughput computing platforms equipped with expensive multichannel audio interfaces, the IoT paradigm is demanding the use of more flexible and energy-efficient systems. In this context, algorithms for source localization and ranging in wireless acoustic sensor networks can be considered an enabling technology for many IoT-based environments, including security, industrial, and health-care applications. This paper is aimed at evaluating impo…
Asynchronous sensor fusion of GPS, IMU and CAN-based odometry for heavy-duty vehicles
2021
[EN] In heavy-duty vehicles, multiple signals are available to estimate the vehicle's kinematics, such as Inertial Measurement Unit (IMU), Global Positioning System (GPS) and linear and angular speed readings from wheel tachometers on the internal Controller Area Network (CAN). These signals have different noise variance, bandwidth and sampling rate (being the latter, possibly, irregular). In this paper we present a non-linear sensor fusion algorithm allowing asynchronous sampling and non-causal smoothing. It is applied to achieve accuracy improvements when incorporating odometry measurements from CAN bus to standard GPS+IMU kinematic estimation, as well as the robustness against missing da…
An Scalable matrix computing unit architecture for FPGA and SCUMO user design interface
2019
High dimensional matrix algebra is essential in numerous signal processing and machine learning algorithms. This work describes a scalable square matrix-computing unit designed on the basis of circulant matrices. It optimizes data flow for the computation of any sequence of matrix operations removing the need for data movement for intermediate results, together with the individual matrix operations’ performance in direct or transposed form (the transpose matrix operation only requires a data addressing modification). The allowed matrix operations are: matrix-by-matrix addition, subtraction, dot product and multiplication, matrix-by-vector multiplication, and matrix by scalar multiplication.…
Sequence Learning in a Single Trial: A Spiking Neurons Model Based on Hippocampal Circuitry.
2020
ABSTRACTIn contrast with our everyday experience using brain circuits, it can take a prohibitively long time to train a computational system to produce the correct sequence of outputs in the presence of a series of inputs. This suggests that something important is missing in the way in which models are trying to reproduce basic cognitive functions. In this work, we introduce a new neuronal network architecture that is able to learn, in a single trial, an arbitrary long sequence of any known objects. The key point of the model is the explicit use of mechanisms and circuitry observed in the hippocampus, which allow the model to reach a level of efficiency and accuracy that, to the best of our…
An optimized mass storage FFT for vector computers
1995
Abstract The performance of a segmented FFT algorithm which allows the out-of-core computation of the Fourier transform of a very large mass storage data array is presented. The code is particularly optimized for vector computers. Tests performed mainly on a CONVEX C210 vector computer showed that, for very long transforms, tuning of the main parameters involved leads to computation speed and global efficiency better than for FFTs performed in-core. The use of tunable parameters allows optimization of the algorithm on machines with different configurations.
Domain-Knowledge Optimized Simulated Annealing for Network-on-Chip Application Mapping
2013
Network-on-Chip architectures are scalable on-chip interconnection networks. They replace the inefficient shared buses and are suitable for multicore and manycore systems. This paper presents an Optimized Simulated Annealing (OSA) algorithm for the Network-on-Chip application mapping problem. With OSA, the cores are implicitly and dynamically clustered using knowledge about communication demands. We show that OSA is a more feasible Simulated Annealing approach to NoC application mapping by comparing it with a general Simulated Annealing algorithm and a Branch and Bound algorithm, too. Using real applications we show that OSA is significantly faster than a general Simulated Annealing, withou…
Performance improvements of real-time crowd simulations
2010
The current challenge for crowd simulations is the design and development of a scalable system that is capable of simulating the individual behavior of millions of complex agents populating large scale virtual worlds with a good frame rate. In order to overcome this challenge, this thesis proposes different improvements for crowd simulations. Concretely, we propose a distributed software architecture that can take advantage of the existing distributed and multi-core architectures. In turn, the use of these distributed architectures requires partitioning strategies and workload balancing techniques for distributed crowd simulations. Also, these architectures allow the use of GPUs not only fo…