2,345 research outputs found
Topology optimization of multiple anisotropic materials, with application to self-assembling diblock copolymers
We propose a solution strategy for a multimaterial minimum compliance
topology optimization problem, which consists in finding the optimal allocation
of a finite number of candidate (possibly anisotropic) materials inside a
reference domain, with the aim of maximizing the stiffness of the body. As a
relevant and novel application we consider the optimization of self-assembled
structures obtained by means of diblock copolymers. Such polymers are a class
of self-assembling materials which spontaneously synthesize periodic
microstructures at the nanoscale, whose anisotropic features can be exploited
to build structures with optimal elastic response, resembling biological
tissues exhibiting microstructures, such as bones and wood. For this purpose we
present a new generalization of the classical Optimality Criteria algorithm to
encompass a wider class of problems, where multiple candidate materials are
considered, the orientation of the anisotropic materials is optimized, and the
elastic properties of the materials are assumed to depend on a scalar
parameter, which is optimized simultaneously to the material allocation and
orientation. Well-posedness of the optimization problem and well-definition of
the presented algorithm are narrowly treated and proved. The capabilities of
the proposed method are assessed through several numerical tests
Trojans in Early Design Steps—An Emerging Threat
Hardware Trojans inserted by malicious foundries
during integrated circuit manufacturing have received substantial
attention in recent years. In this paper, we focus on a different
type of hardware Trojan threats: attacks in the early steps of
design process. We show that third-party intellectual property
cores and CAD tools constitute realistic attack surfaces and that
even system specification can be targeted by adversaries. We
discuss the devastating damage potential of such attacks, the
applicable countermeasures against them and their deficiencies
The Evolution of First Person Vision Methods: A Survey
The emergence of new wearable technologies such as action cameras and
smart-glasses has increased the interest of computer vision scientists in the
First Person perspective. Nowadays, this field is attracting attention and
investments of companies aiming to develop commercial devices with First Person
Vision recording capabilities. Due to this interest, an increasing demand of
methods to process these videos, possibly in real-time, is expected. Current
approaches present a particular combinations of different image features and
quantitative methods to accomplish specific objectives like object detection,
activity recognition, user machine interaction and so on. This paper summarizes
the evolution of the state of the art in First Person Vision video analysis
between 1997 and 2014, highlighting, among others, most commonly used features,
methods, challenges and opportunities within the field.Comment: First Person Vision, Egocentric Vision, Wearable Devices, Smart
Glasses, Computer Vision, Video Analytics, Human-machine Interactio
Du loup. Force et loi
For elucidating the relation between violence and justice, that gives rise to the phrase «force of law», the figure of wolf, the lupus in fabula, occupies a strategic place in the western philosophical and political discourse. The double reading –or writing– of such a phrase in a text by Solon, because of a lapsus calami – indeed a masterly slip of the pen, as Derrida reminds us– allows us to see the –paradoxical– double face of the sovereign kratos: that of force without law and outside the law that establishes the law, and that of force incorporated into the law to accomplish justice. The figure of the wolf embodies this paradox of sovereignty.Para esclarecer la relaciĂłn entre violencia y justicia que cristaliza en el sintagma «fuerza de ley», la figura del lobo, el lupus in fabula, ocupa un lugar estratĂ©gico en el discurso filosĂłfico-polĂtico de occidente. La doble lectura –o escritura– de dicho sintagma en un texto de SolĂłn debida a un lapsus calami –lapsus magistral sin duda, como recuerda Derrida– nos permite ver la doble cara –paradĂłjica– del kratos soberano: la de la fuerza sin ley y fuera de la ley que establece la ley, y la de la fuerza incorporada a la ley para la realizaciĂłn de la justicia. En la figura del lobo se encarna esa paradoja de la soberanĂa.Para esclarecer la relaciĂłn entre violencia y justicia que cristaliza en el sintagma «fuerza de ley», la figura del lobo, el lupus in fabula, ocupa un lugar estratĂ©gico en el discurso filosĂłfico-polĂtico de occidente. La doble lectura –o escritura– de dicho sintagma en un texto de SolĂłn debida a un lapsus calami –lapsus magistral sin duda, como recuerda Derrida– nos permite ver la doble cara –paradĂłjica– del kratos soberano: la de la fuerza sin ley y fuera de la ley que establece la ley, y la de la fuerza incorporada a la ley para la realizaciĂłn de la justicia. En la figura del lobo se encarna esa paradoja de la soberanĂa
Left/Right Hand Segmentation in Egocentric Videos
Wearable cameras allow people to record their daily activities from a
user-centered (First Person Vision) perspective. Due to their favorable
location, wearable cameras frequently capture the hands of the user, and may
thus represent a promising user-machine interaction tool for different
applications. Existent First Person Vision methods handle hand segmentation as
a background-foreground problem, ignoring two important facts: i) hands are not
a single "skin-like" moving element, but a pair of interacting cooperative
entities, ii) close hand interactions may lead to hand-to-hand occlusions and,
as a consequence, create a single hand-like segment. These facts complicate a
proper understanding of hand movements and interactions. Our approach extends
traditional background-foreground strategies, by including a
hand-identification step (left-right) based on a Maxwell distribution of angle
and position. Hand-to-hand occlusions are addressed by exploiting temporal
superpixels. The experimental results show that, in addition to a reliable
left/right hand-segmentation, our approach considerably improves the
traditional background-foreground hand-segmentation
Practice-based methodology for effectively modeling and documenting search, protection and innovation
AbstractThis work relates to a methodology for effectively modeling an Action and Problem System and documenting a path built by means of patent databases. The aim of this work is to provide an improved method and operative tool for a quick and reliable patents investigation driven by Boolean algorithms. The method has been tested with several projects for companies of different industrial areas. Moreover in the last months the method has been used in case studies by students from the University of Bergamo with good results after a very few hours of training. Two specific case studies will be discussed in this paper in order to clarify the operative value of said method and to show the results obtained in terms of solutions found and of efforts requested
Unsupervised Understanding of Location and Illumination Changes in Egocentric Videos
Wearable cameras stand out as one of the most promising devices for the
upcoming years, and as a consequence, the demand of computer algorithms to
automatically understand the videos recorded with them is increasing quickly.
An automatic understanding of these videos is not an easy task, and its mobile
nature implies important challenges to be faced, such as the changing light
conditions and the unrestricted locations recorded. This paper proposes an
unsupervised strategy based on global features and manifold learning to endow
wearable cameras with contextual information regarding the light conditions and
the location captured. Results show that non-linear manifold methods can
capture contextual patterns from global features without compromising large
computational resources. The proposed strategy is used, as an application case,
as a switching mechanism to improve the hand-detection problem in egocentric
videos.Comment: Submitted for publicatio
Tracking Using Continuous Shape Model Learning in the Presence of Occlusion
This paper presents a Bayesian framework for a new model-based learning method, which is able to track nonrigid objects in the presence of occlusions, based on a dynamic shape description in terms of a set of corners. Tracking is done by estimating the new position of the target in a multimodal voting space. However, occlusion events and clutter may affect the model learning, leading to a distraction in the estimation of the new position of the target as well as incorrect updating of the shape model. This method takes advantage of automatic decisions regarding how to learn the model in different environments, by estimating the possible presence of distracters and regulating corner updating on the basis of these estimations. Moreover, by introducing the corner feature vector classification, the method is able to continue learning the model dynamically, even in such situations. Experimental results show a successful tracking along with a more precise estimation of shape and motion during occlusion events
Exploring Energy Efficiency of Lightweight Block Ciphers
Abstract. In the last few years, the field of lightweight cryptography has seen an influx in the number of block ciphers and hash functions being proposed. One of the metrics that define a good lightweight design is the energy consumed per unit operation of the algorithm. For block ciphers, this operation is the encryption of one plaintext. By studying the energy consumption model of a CMOS gate, we arrive at the conclusion that the total energy consumed during the encryption operation of an r-round unrolled architecture of any block cipher is a quadratic function in r. We then apply our model to 9 well known lightweight block ciphers, and thereby try to predict the optimal value of r at which an r-round unrolled architecture for a cipher is likely to be most energy efficient. We also try to relate our results to some physical design parameters like the signal delay across a round and algorithmic parameters like the number of rounds taken to achieve full diffusion of a difference in the plaintext/key
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