Search results for "Embedded"

Reports of the AAAI 2019 Spring Symposium Series

2019

Applications of machine learning combined with AI algorithms have propelled unprecedented economic disruptions across diverse fields in industry, military, medicine, finance, and others. With the forecast for even larger impacts, the present economic impact of machine learning is estimated in the trillions of dollars. But as autonomous machines become ubiquitous, recent problems have surfaced. Early on, and again in 2018, Judea Pearl warned AI scientists they must "build machines that make sense of what goes on in their environment," a warning still unheeded that may impede future development. For example, self-driving vehicles often rely on sparse data; self-driving cars have already been …

ConformalALU: A Conformal Geometric Algebra Coprocessor for Medical Image Processing

2015

Medical imaging involves important computational geometric problems, such as image segmentation and analysis, shape approximation, three-dimensional (3D) modeling, and registration of volumetric data. In the last few years, Conformal Geometric Algebra (CGA), based on five-dimensional (5D) Clifford Algebra, is emerging as a new paradigm that offers simple and universal operators for the representation and solution of complex geometric problems. However, the widespread use of CGA has been so far hindered by its high dimensionality and computational complexity. This paper proposes a simplified formulation of the conformal geometric operations (reflections, rotations, translations, and uniform …

Design and implementation of an embedded coprocessor with native support for 5D, quadruple-based Clifford algebra

2013

Geometric or Clifford algebra (CA) is a powerful mathematical tool that offers a natural and intuitive way to model geometric facts in a number of research fields, such as robotics, machine vision, and computer graphics. Operating in higher dimensional spaces, its practical use is hindered, however, by a significant computational cost, only partially addressed by dedicated software libraries and hardware/software codesigns. For low-dimensional algebras, several dedicated hardware accelerators and coprocessing architectures have been already proposed in the literature. This paper introduces the architecture of CliffordALU5, an embedded coprocessing core conceived for native execution of up t…

A New Embedded Coprocessor for Clifford Algebra based Software Intensive Systems

2011

Computer graphics applications require efficient tools to model geometric objects and their transformations. Clifford algebra (also known as geometric algebra) is receiving a growing attention in many research fields, such as computer graphics, machine vision and robotics, as a new, interesting computational paradigm that offers a natural and intuitive way to perform geometric calculations. At the same time, compute-intensive graphics algorithms require the execution of million Clifford operations. Clifford algebra based software intensive systems need therefore the support of specialized hardware architectures capable of accelerating Clifford operations execution. In this paper the archite…

Testing wearable IoT applications through sensor virtualization

2020

The development of distributed IoT applications requires the integration of data provided by different sensors embedded in multiple devices. As an example, an application for health monitoring in an assisted living scenario may include several wearable and fixed nodes each carrying different sensors and running specific code. Verifying that the application is properly working according to the specifications requires assessing that the code of each node behaves consistently in all the possible use cases. Tests involving sensor data may be difficult or costly to replicate realistically and this could also slow down the development of the application in its early stages. In this paper we intro…

Embedded Biometric Sensor Devices: Design and Implementation on Field Programmable Gate Array

During the research activity in my Ph.D. course, I thoroughly studied the biometric systems and the relevant design and implementation techniques allowing the employment of such systems in embedded devices. I focused my attention on the fingerprint-based recognition and classification systems, and on their implementation on Field Programmable Gate Array (FPGA) devices. I was prompted to study biometric systems mainly because these systems may play a key role in the new emerging market of mobile devices (for example, they are recently available in the new generation of Apple and Samsung smart phones). Such market is rapidly growing and influencing the way people use network resources and fun…

An embedded iris recognizer for portable and mobile devices

2010

Software-intensive systems play an increasingly dominant role in our lives and daily activities. Several applications, in which a timely response to user and environment stimulus is essential, require real-time software intensive systems. Computation-intensive applications, such as video compression, control systems, security systems, result in significant growth for processor workload. To address the above issues, one possible solution is to design embedded specialized components. At the same time, the integration of new features in portable and mobile devices is rapidly increasing. Several services and applications require robust user authentication for access to services, data, and resou…

Modeling and Verification of Symbolic Distributed Applications Through an Intelligent Monitoring Agent

2022

Wireless Sensor Networks (WSNs) represent a key component in emerging distributed computing paradigms such as IoT, Ambient Intelligence, and Smart Cities. In these contexts, the difficulty of testing, verifying, and monitoring applications in their intended scenarios ranges from challenging to impractical. Current simulators can only be used to investigate correctness at source code level and with limited accuracy. This paper proposes a system and a methodology to model and verify symbolic distributed applications running on WSNs. The approach allows to complement the distributed application code at a high level of abstraction in order to test and reprogram it, directly, on deployed network…

A Family of Embedded Coprocessors with Native Geometric Algebra Support

2015

Clifford Algebra or Geometric Algebra (GA) is a simple and intuitive way to model geometric objects and their transformations. Operating in high-dimensional vector spaces with significant computational costs, the practical use of GA requires, however, dedicated software and/or hardware architectures to directly support Clifford data types and operators. In this paper, a family of embedded coprocessors for the native execution of GA operations is presented. The paper shows the evolution of the coprocessor family focusing on the latest two architectures that offer direct hardware support to up to five-dimensional Clifford operations. The proposed coprocessors exploit hardware-oriented represe…

An Embedded Processor for Metabolic Networks Optimization

2011

In recent years biological processes modelling and simulation have become two key issues in analyzing complex cellular systems. The computational requirements suggest to investigate alternative solutions to the common supercomputers and clusters in order to optimize and overcome computational bottleneck. The goal of this work is the design and the realization of an embedded processor for metabolic networks optimization in order to examine their behaviour and robustness under malfunctions of one or more nodes. The embedded processor has been prototyped on the Celoxica RC203E board, equipped with programmable FPGA technologies. A case studied outlining the E. Coli bacteria metabolic network i…