51,045 research outputs found
Efficient Proxies in Smalltalk
International audienceA proxy object is a surrogate or placeholder that controls access to another target object. Proxy objects are a widely used solution for different scenarios such as remote method invocation, future objects, behavioral reflection, object databases, inter-languages communications and bindings, access control, lazy or parallel evaluation, security, among others. Most proxy implementations support proxies for regular objects but they are unable to create proxies for classes or methods. Proxies can be complex to install, have a significant overhead, be limited to certain type of classes, etc. Moreover, most proxy implementations are not stratified at all and there is no separation between proxies and handlers. In this paper, we present Ghost, a uniform, light-weight and stratified general purpose proxy model and its Smalltalk implementation.Ghost supports proxies for classes or methods. When a proxy takes the place of a class it intercepts both, messages received by the class and lookup of methods for messages received by instances. Similarly, if a proxy takes the place of a method, then the method execution is intercepted too
Are Face and Object Recognition Independent? A Neurocomputational Modeling Exploration
Are face and object recognition abilities independent? Although it is
commonly believed that they are, Gauthier et al.(2014) recently showed that
these abilities become more correlated as experience with nonface categories
increases. They argued that there is a single underlying visual ability, v,
that is expressed in performance with both face and nonface categories as
experience grows. Using the Cambridge Face Memory Test and the Vanderbilt
Expertise Test, they showed that the shared variance between Cambridge Face
Memory Test and Vanderbilt Expertise Test performance increases monotonically
as experience increases. Here, we address why a shared resource across
different visual domains does not lead to competition and to an inverse
correlation in abilities? We explain this conundrum using our
neurocomputational model of face and object processing (The Model, TM). Our
results show that, as in the behavioral data, the correlation between
subordinate level face and object recognition accuracy increases as experience
grows. We suggest that different domains do not compete for resources because
the relevant features are shared between faces and objects. The essential power
of experience is to generate a "spreading transform" for faces that generalizes
to objects that must be individuated. Interestingly, when the task of the
network is basic level categorization, no increase in the correlation between
domains is observed. Hence, our model predicts that it is the type of
experience that matters and that the source of the correlation is in the
fusiform face area, rather than in cortical areas that subserve basic level
categorization. This result is consistent with our previous modeling
elucidating why the FFA is recruited for novel domains of expertise (Tong et
al., 2008)
The C Object System: Using C as a High-Level Object-Oriented Language
The C Object System (Cos) is a small C library which implements high-level
concepts available in Clos, Objc and other object-oriented programming
languages: uniform object model (class, meta-class and property-metaclass),
generic functions, multi-methods, delegation, properties, exceptions, contracts
and closures. Cos relies on the programmable capabilities of the C programming
language to extend its syntax and to implement the aforementioned concepts as
first-class objects. Cos aims at satisfying several general principles like
simplicity, extensibility, reusability, efficiency and portability which are
rarely met in a single programming language. Its design is tuned to provide
efficient and portable implementation of message multi-dispatch and message
multi-forwarding which are the heart of code extensibility and reusability.
With COS features in hand, software should become as flexible and extensible as
with scripting languages and as efficient and portable as expected with C
programming. Likewise, Cos concepts should significantly simplify adaptive and
aspect-oriented programming as well as distributed and service-oriented
computingComment: 18
Neural signatures of strategic types in a two-person bargaining game
The management and manipulation of our own social image in the minds of others requires difficult and poorly understood computations. One computation useful in social image management is strategic deception: our ability and willingness to manipulate other people's beliefs about ourselves for gain. We used an interpersonal bargaining game to probe the capacity of players to manage their partner's beliefs about them. This probe parsed the group of subjects into three behavioral types according to their revealed level of strategic deception; these types were also distinguished by neural data measured during the game. The most deceptive subjects emitted behavioral signals that mimicked a more benign behavioral type, and their brains showed differential activation in right dorsolateral prefrontal cortex and left Brodmann area 10 at the time of this deception. In addition, strategic types showed a significant correlation between activation in the right temporoparietal junction and expected payoff that was absent in the other groups. The neurobehavioral types identified by the game raise the possibility of identifying quantitative biomarkers for the capacity to manipulate and maintain a social image in another person's mind
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