117,556 research outputs found
Recent Advances in Transfer Learning for Cross-Dataset Visual Recognition: A Problem-Oriented Perspective
This paper takes a problem-oriented perspective and presents a comprehensive
review of transfer learning methods, both shallow and deep, for cross-dataset
visual recognition. Specifically, it categorises the cross-dataset recognition
into seventeen problems based on a set of carefully chosen data and label
attributes. Such a problem-oriented taxonomy has allowed us to examine how
different transfer learning approaches tackle each problem and how well each
problem has been researched to date. The comprehensive problem-oriented review
of the advances in transfer learning with respect to the problem has not only
revealed the challenges in transfer learning for visual recognition, but also
the problems (e.g. eight of the seventeen problems) that have been scarcely
studied. This survey not only presents an up-to-date technical review for
researchers, but also a systematic approach and a reference for a machine
learning practitioner to categorise a real problem and to look up for a
possible solution accordingly
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A systematic review of software development cost estimation studies
This paper aims to provide a basis for the improvement of software estimation research through a systematic review of previous work. The review identifies 304 software cost estimation papers in 76 journals and classifies the papers according to research topic, estimation approach, research approach, study context and data set. A web-based library of these cost estimation papers is provided to ease the identification of relevant estimation research results. The review results combined with other knowledge provide support for recommendations for future software cost estimation research, including: 1) Increase the breadth of the search for relevant studies, 2) Search manually for relevant papers within a carefully selected set of journals when completeness is essential, 3) Conduct more studies on estimation methods commonly used by the software industry, and, 4) Increase the awareness of how properties of the data sets impact the results when evaluating estimation methods
Dynamic Virtual Join Point Dispatch
Conceptually, join points are points in the execution of a program and advice is late-bound to them. We propose the notion of virtual join points that makes this concept explicit not only at a conceptual, but also at implementation level. In current implementations of aspect-oriented languages, binding is performed early, at deploy-time, and only a limited residual dispatch is executed. Current implementations fall in the categories of modifying the application code, modifying the meta-level of an application, or interacting with the application by means of eventsâthe latter two already realizing virtual join points to some degree. We provide an implementation of an aspect-oriented execution environment that supports truly virtual join points and discuss how this approach also favors optimizations in the execution environment
Global Search with Bernoulli Alternation Kernel for Task-oriented Grasping Informed by Simulation
We develop an approach that benefits from large simulated datasets and takes
full advantage of the limited online data that is most relevant. We propose a
variant of Bayesian optimization that alternates between using informed and
uninformed kernels. With this Bernoulli Alternation Kernel we ensure that
discrepancies between simulation and reality do not hinder adapting robot
control policies online. The proposed approach is applied to a challenging
real-world problem of task-oriented grasping with novel objects. Our further
contribution is a neural network architecture and training pipeline that use
experience from grasping objects in simulation to learn grasp stability scores.
We learn task scores from a labeled dataset with a convolutional network, which
is used to construct an informed kernel for our variant of Bayesian
optimization. Experiments on an ABB Yumi robot with real sensor data
demonstrate success of our approach, despite the challenge of fulfilling task
requirements and high uncertainty over physical properties of objects.Comment: To appear in 2nd Conference on Robot Learning (CoRL) 201
Distributed machining control and monitoring using smart sensors/actuators
The study of smart sensors and actuators led, during the past few years, to the development of facilities which improve traditional sensors and actuators in a necessary way to automate production systems. In an other context, many studies are carried out aiming at defining a decisional structure for production activity control and the increasing need of reactivity leads to the autonomization of decisional levels close to the operational system. We suggest in this paper to study the natural convergence between these two approaches and we propose an integration architecture dealing with machine tool and machining control that enables the exploitation of distributed smart sensors and actuators in the decisional system
Mental Structures
An ongoing philosophical discussion concerns how various types of mental states fall within broad representational generaâfor example, whether perceptual states are âiconicâ or âsentential,â âanalogâ or âdigital,â and so on. Here, I examine the grounds for making much more specific claims about how mental states are structured from constituent parts. For example, the state I am in when I perceive the shape of a mountain ridge may have as constituent parts my representations of the shapes of each peak and saddle of the ridge. More specific structural claims of this sort are a guide to how mental states fall within broader representational kinds. Moreover, these claims have significant implications of their own about semantic, functional, and epistemic features of our mental lives. But what are the conditions on a mental state's having one type of constituent structure rather than another? Drawing on explanatory strategies in vision science, I argue that, other things being equal, the constituent structure of a mental state determines what I call its distributional propertiesânamely, how mental states of that type can, cannot, or must coâoccur with other mental states in a given system. Distributional properties depend critically on and are informative about the underlying structures of mental states, they abstract in important ways from aspects of how mental states are processed, and they can yield significant insights into the variegation of psychological capacities
Model Based Development of Quality-Aware Software Services
Modelling languages and development frameworks give support for functional and structural description of software architectures. But quality-aware applications require languages which allow expressing QoS as a first-class concept during architecture design and service composition, and to extend existing tools and infrastructures adding support for modelling, evaluating, managing and monitoring QoS aspects. In addition to its functional behaviour and internal structure, the developer of each service must consider the fulfilment of its quality requirements. If the service is flexible, the output quality depends both on input quality and available resources (e.g., amounts of CPU execution time and memory). From the software engineering point of view, modelling of quality-aware requirements and architectures require modelling support for the description of quality concepts, support for the analysis of quality properties (e.g. model checking and consistencies of quality constraints, assembly of quality), tool support for the transition from quality requirements to quality-aware architectures, and from quality-aware architecture to service run-time infrastructures. Quality management in run-time service infrastructures must give support for handling quality concepts dynamically. QoS-aware modeling frameworks and QoS-aware runtime management infrastructures require a common evolution to get their integration
Real-time edge tracking using a tactile sensor
Object recognition through the use of input from multiple sensors is an important aspect of an autonomous manipulation system. In tactile object recognition, it is necessary to determine the location and orientation of object edges and surfaces. A controller is proposed that utilizes a tactile sensor in the feedback loop of a manipulator to track along edges. In the control system, the data from the tactile sensor is first processed to find edges. The parameters of these edges are then used to generate a control signal to a hybrid controller. Theory is presented for tactile edge detection and an edge tracking controller. In addition, experimental verification of the edge tracking controller is presented
Open Programming Language Interpreters
Context: This paper presents the concept of open programming language
interpreters and the implementation of a framework-level metaobject protocol
(MOP) to support them. Inquiry: We address the problem of dynamic interpreter
adaptation to tailor the interpreter's behavior on the task to be solved and to
introduce new features to fulfill unforeseen requirements. Many languages
provide a MOP that to some degree supports reflection. However, MOPs are
typically language-specific, their reflective functionality is often
restricted, and the adaptation and application logic are often mixed which
hardens the understanding and maintenance of the source code. Our system
overcomes these limitations. Approach: We designed and implemented a system to
support open programming language interpreters. The prototype implementation is
integrated in the Neverlang framework. The system exposes the structure,
behavior and the runtime state of any Neverlang-based interpreter with the
ability to modify it. Knowledge: Our system provides a complete control over
interpreter's structure, behavior and its runtime state. The approach is
applicable to every Neverlang-based interpreter. Adaptation code can
potentially be reused across different language implementations. Grounding:
Having a prototype implementation we focused on feasibility evaluation. The
paper shows that our approach well addresses problems commonly found in the
research literature. We have a demonstrative video and examples that illustrate
our approach on dynamic software adaptation, aspect-oriented programming,
debugging and context-aware interpreters. Importance: To our knowledge, our
paper presents the first reflective approach targeting a general framework for
language development. Our system provides full reflective support for free to
any Neverlang-based interpreter. We are not aware of any prior application of
open implementations to programming language interpreters in the sense defined
in this paper. Rather than substituting other approaches, we believe our system
can be used as a complementary technique in situations where other approaches
present serious limitations
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