A flexible open source web platform to facilitate Learning Object evaluation

Systematic evaluation of Learning Objects is essential to make high quality Web-based education possible. For this reason, several educational repositories and e-Learning systems have developed their own evaluation models and tools. However, the differences of the context in which Learning Objects are produced and consumed suggest that no single evaluation model is sufficient for all scenarios. Besides, no much effort has been put in developing open tools to facilitate Learning Object evaluation and use the quality information for the benefit of end users. This paper presents LOEP, an open source web platform that aims to facilitate Learning Object evaluation in different scenarios and educational settings by supporting and integrating several evaluation models and quality metrics. The work exposed in this paper shows that LOEP is capable of providing Learning Object evaluation to e-Learning systems in an open, low cost, reliable and effective way. Possible scenarios where LOEP could be used to implement quality control policies and to enhance search engines are also described. Finally, we report the results of a survey conducted among reviewers that used LOEP, showing that they perceived LOEP as a powerful and easy to use tool for evaluating Learning Objects.

Cooperative Learning Model based on Multi-Agent Architecture for Embedded Intelligent Systems

Cooperative systems are suitable for many types of applications and nowadays these system are vastly used to improve a previously defined system or to coordinate multiple devices working together. This paper provides an alternative to improve the reliability of a previous intelligent identification system. The proposed approach implements a cooperative model based on multi-agent architecture. This new system is composed of several radar-based systems which identify a detected object and transmit its own partial result by implementing several agents and by using a wireless network to transfer data. The proposed topology is a centralized architecture where the coordinator device is in charge of providing the final identification result depending on the group behavior. In order to find the final outcome, three different mechanisms are introduced. The simplest one is based on majority voting whereas the others use two different weighting voting procedures, both providing the system with learning capabilities. Using an appropriate network configuration, the success rate can be improved from the initial 80% up to more than 90%.

RESSIST: a research object-based recommender system

The scientific method is a methodological approach to the process of inquiry { in which empirically grounded theory of nature is constructed and verified [14]. It is a hard, exhaustive and dedicated multi-stage procedure that a researcher must perform to achieve valuable knowledge. Trying to help researchers during this process, a recommender system, intended as a researcher assistant, is designed to provide them useful tools and information for each stage of the procedure. A new similarity measure between research objects and a representational model, based on domain spaces, to handle them in dif ferent levels are created as well as a system to build them from OAI-PMH (and RSS) resources. It tries to represents a sound balance between scientific insight into individual scientific creative processes and technical implementation using innovative technologies in information extraction, document summarization and semantic analysis at a large scale.

Engineering Computational Emotion - A Reference Model for Emotion in Artificial Systems

Emotion is generally argued to be an influence on the behavior of life systems, largely concerning flexibility and adaptivity. The way in which life systems acts in response to a particular situations of the environment, has revealed the decisive and crucial importance of this feature in the success of behaviors. And this source of inspiration has influenced the way of thinking artificial systems. During the last decades, artificial systems have undergone such an evolution that each day more are integrated in our daily life. They have become greater in complexity, and the subsequent effects are related to an increased demand of systems that ensure resilience, robustness, availability, security or safety among others. All of them questions that raise quite a fundamental challenges in control design. This thesis has been developed under the framework of the Autonomous System project, a.k.a the ASys-Project. Short-term objectives of immediate application are focused on to design improved systems, and the approaching of intelligence in control strategies. Besides this, long-term objectives underlying ASys-Project concentrate on high order capabilities such as cognition, awareness and autonomy. This thesis is placed within the general fields of Engineery and Emotion science, and provides a theoretical foundation for engineering and designing computational emotion for artificial systems. The starting question that has grounded this thesis aims the problem of emotion--based autonomy. And how to feedback systems with valuable meaning has conformed the general objective. Both the starting question and the general objective, have underlaid the study of emotion, the influence on systems behavior, the key foundations that justify this feature in life systems, how emotion is integrated within the normal operation, and how this entire problem of emotion can be explained in artificial systems. By assuming essential differences concerning structure, purpose and operation between life and artificial systems, the essential motivation has been the exploration of what emotion solves in nature to afterwards analyze analogies for man--made systems. This work provides a reference model in which a collection of entities, relationships, models, functions and informational artifacts, are all interacting to provide the system with non-explicit knowledge under the form of emotion-like relevances. This solution aims to provide a reference model under which to design solutions for emotional operation, but related to the real needs of artificial systems. The proposal consists of a multi-purpose architecture that implement two broad modules in order to attend: (a) the range of processes related to the environment affectation, and (b) the range or processes related to the emotion perception-like and the higher levels of reasoning. This has required an intense and critical analysis beyond the state of the art around the most relevant theories of emotion and technical systems, in order to obtain the required support for those foundations that sustain each model. The problem has been interpreted and is described on the basis of AGSys, an agent assumed with the minimum rationality as to provide the capability to perform emotional assessment. AGSys is a conceptualization of a Model-based Cognitive agent that embodies an inner agent ESys, the responsible of performing the emotional operation inside of AGSys. The solution consists of multiple computational modules working federated, and aimed at conforming a mutual feedback loop between AGSys and ESys. Throughout this solution, the environment and the effects that might influence over the system are described as different problems. While AGSys operates as a common system within the external environment, ESys is designed to operate within a conceptualized inner environment. And this inner environment is built on the basis of those relevances that might occur inside of AGSys in the interaction with the external environment. This allows for a high-quality separate reasoning concerning mission goals defined in AGSys, and emotional goals defined in ESys. This way, it is provided a possible path for high-level reasoning under the influence of goals congruence. High-level reasoning model uses knowledge about emotional goals stability, letting this way new directions in which mission goals might be assessed under the situational state of this stability. This high-level reasoning is grounded by the work of MEP, a model of emotion perception that is thought as an analogy of a well-known theory in emotion science. The work of this model is described under the operation of a recursive-like process labeled as R-Loop, together with a system of emotional goals that are assumed as individual agents. This way, AGSys integrates knowledge that concerns the relation between a perceived object, and the effect which this perception induces on the situational state of the emotional goals. This knowledge enables a high-order system of information that provides the sustain for a high-level reasoning. The extent to which this reasoning might be approached is just delineated and assumed as future work. This thesis has been studied beyond a long range of fields of knowledge. This knowledge can be structured into two main objectives: (a) the fields of psychology, cognitive science, neurology and biological sciences in order to obtain understanding concerning the problem of the emotional phenomena, and (b) a large amount of computer science branches such as Autonomic Computing (AC), Self-adaptive software, Self-X systems, Model Integrated Computing (MIC) or the paradigm of models@runtime among others, in order to obtain knowledge about tools for designing each part of the solution. The final approach has been mainly performed on the basis of the entire acquired knowledge, and described under the fields of Artificial Intelligence, Model-Based Systems (MBS), and additional mathematical formalizations to provide punctual understanding in those cases that it has been required. This approach describes a reference model to feedback systems with valuable meaning, allowing for reasoning with regard to (a) the relationship between the environment and the relevance of the effects on the system, and (b) dynamical evaluations concerning the inner situational state of the system as a result of those effects. And this reasoning provides a framework of distinguishable states of AGSys derived from its own circumstances, that can be assumed as artificial emotion.

A model of multiplicative neural responses in parietal cortex.

Visual responses of neurons in parietal area 7a are modulated by a combined eye and head position signal in a multiplicative manner. Neurons with multiplicative responses can act as powerful computational elements in neural networks. In the case of parietal cortex, multiplicative gain modulation appears to play a crucial role in the transformation of object locations from retinal to body-centered coordinates. It has proven difficult to uncover single-neuron mechanisms that account for neuronal multiplication. Here we show that multiplicative responses can arise in a network model through population effects. Specifically, neurons in a recurrently connected network with excitatory connections between similarly tuned neurons and inhibitory connections between differently tuned neurons can perform a product operation on additive synaptic inputs. The results suggest that parietal responses may be based on this architecture.

A new boundary-based morphological model

Mathematical morphology addresses the problem of describing shapes in an n-dimensional space using the concepts of set theory. A series of standardized morphological operations are defined, and they are applied to the shapes to transform them using another shape called the structuring element. In an industrial environment, the process of manufacturing a piece is based on the manipulation of a primitive object via contact with a tool that transforms the object progressively to obtain the desired design. The analogy with the morphological operation of erosion is obvious. Nevertheless, few references about the relation between the morphological operations and the process of design and manufacturing can be found. The non-deterministic nature of classic mathematical morphology makes it very difficult to adapt their basic operations to the dynamics of concepts such as the ordered trajectory. A new geometric model is presented, inspired by the classic morphological paradigm, which can define objects and apply morphological operations that transform these objects. The model specializes in classic morphological operations, providing them with the determinism inherent in dynamic processes that require an order of application, as is the case for designing and manufacturing objects in professional computer-aided design and manufacturing (CAD/CAM) environments. The operators are boundary-based so that only the points in the frontier are handled. As a consequence, the process is more efficient and more suitable for use in CAD/CAM systems.

Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC

Plane model extraction from three-dimensional point clouds is a necessary step in many different applications such as planar object reconstruction, indoor mapping and indoor localization. Different RANdom SAmple Consensus (RANSAC)-based methods have been proposed for this purpose in recent years. In this study, we propose a novel method-based on RANSAC called Multiplane Model Estimation, which can estimate multiple plane models simultaneously from a noisy point cloud using the knowledge extracted from a scene (or an object) in order to reconstruct it accurately. This method comprises two steps: first, it clusters the data into planar faces that preserve some constraints defined by knowledge related to the object (e.g., the angles between faces); and second, the models of the planes are estimated based on these data using a novel multi-constraint RANSAC. We performed experiments in the clustering and RANSAC stages, which showed that the proposed method performed better than state-of-the-art methods.

Digital surface model, hillshade and orthophoto of the world's largest fossil oyster reef, links to GeoTIFFs

The world's largest fossil oyster reef, formed by the giant oyster Crassostrea gryphoides and located in Stetten (north of Vienna, Austria) is studied by Harzhauser et al., 2015, 2016; Djuricic et al., 2016. Digital documentation of the unique geological site is provided by terrestrial laser scanning (TLS) at the millimeter scale. Obtaining meaningful results is not merely a matter of data acquisition with a suitable device; it requires proper planning, data management, and postprocessing. Terrestrial laser scanning technology has a high potential for providing precise 3D mapping that serves as the basis for automatic object detection in different scenarios; however, it faces challenges in the presence of large amounts of data and the irregular geometry of an oyster reef. We provide a detailed description of the techniques and strategy used for data collection and processing in Djuricic et al., 2016. The use of laser scanning provided the ability to measure surface points of 46,840 (estimated) shells. They are up to 60-cm-long oyster specimens, and their surfaces are modeled with a high accuracy of 1 mm. In addition to laser scanning measurements, more than 300 photographs were captured, and an orthophoto mosaic was generated with a ground sampling distance (GSD) of 0.5 mm. This high-resolution 3D information and the photographic texture serve as the basis for ongoing and future geological and paleontological analyses. Moreover, they provide unprecedented documentation for conservation issues at a unique natural heritage site.

Electromagnetic modeling of conformal wideband and multi-band patch antennas by bridging a solid-object modeler with MoM software

The advantages of antennas that can resemble the shape of the body to which they are attached are obvious. However, electromagnetic modeling of such unusually shaped antennas can be difficult. In this paper, the commercially available software SolidWorks(TM) is used for accurately drawing complex shapes in conjunction with the electromagnetic software FEKO(TM) to model the EM behavior of conformal antennas. The application of SolidWorks and custom-written software allows all the required information that forms the analyzed structure to be automatically inserted into FEKO, and gives the user complete control over the antenna being modeled. This approach is illustrated by a number of simulation examples of single, wideband, multi-band planar and curved patch antennas.

An object-oriented designed finite-difference time-domain simulator for electromagnetic analysis and design in MRI - application to high field analyses

This paper presents a finite-difference time-domain (FDTD) simulator for electromagnetic analysis and design applications in MRI. It is intended to be a complete FDTD model of an MRI system including all RF and low-frequency field generating units and electrical models of the patient. The pro-ram has been constructed in an object-oriented framework. The design procedure is detailed and the numerical solver has been verified against analytical solutions for simple cases and also applied to various field calculation problems. In particular, the simulator is demonstrated for inverse RF coil design, optimized source profile generation, and parallel imaging in high-frequency situations. The examples show new developments enabled by the simulator and demonstrate that the proposed FDTD framework can be used to analyze large-scale computational electromagnetic problems in modern MRI engineering. (C) 2004 Elsevier Inc. All rights reserved.

Multigradient field-active contour model for multilayer boundary detection of ultrasound rectal wall image

Extraction and reconstruction of rectal wall structures from an ultrasound image is helpful for surgeons in rectal clinical diagnosis and 3-D reconstruction of rectal structures from ultrasound images. The primary task is to extract the boundary of the muscular layers on the rectal wall. However, due to the low SNR from ultrasound imaging and the thin muscular layer structure of the rectum, this boundary detection task remains a challenge. An active contour model is an effective high-level model, which has been used successfully to aid the tasks of object representation and recognition in many image-processing applications. We present a novel multigradient field active contour algorithm with an extended ability for multiple-object detection, which overcomes some limitations of ordinary active contour models—"snakes." The core part in the algorithm is the proposal of multigradient vector fields, which are used to replace image forces in kinetic function for alternative constraints on the deformation of active contour, thereby partially solving the initialization limitation of active contour for rectal wall boundary detection. An adaptive expanding force is also added to the model to help the active contour go through the homogenous region in the image. The efficacy of the model is explained and tested on the boundary detection of a ring-shaped image, a synthetic image, and an ultrasound image. The experimental results show that the proposed multigradient field-active contour is feasible for multilayer boundary detection of rectal wall

A formal object-oriented approach to defining consistency constraints for UML models

We discuss how integrity consistency constraints between different UML models can be precisely defined at a language level. In doing so, we introduce a formal object-oriented metamodeling approach. In the approach, integrity consistency constraints between UML models are defined in terms of invariants of the UML model elements used to define the models at the language-level. Adopting a formal approach, constraints are formally defined using Object-Z. We demonstrate how integrity consistency constraints for UML models can be precisely defined at the language-level and once completed, the formal description of the consistency constraints will be a precise reference of checking consistency of UML models as well as for tool development.

Using integrated metamodeling to define OO design patterns with object-z and UML

Three important goals in describing software design patterns are: generality, precision, and understandability. To address these goals, this paper presents an integrated approach to specifying patterns using Object-Z and UML. To achieve the generality goal, we adopt a role-based metamodeling approach to define patterns. With this approach, each pattern is defined as a pattern role model. To achieve precision, we formalize role concepts using Object-Z (a role metamodel) and use these concepts to define patterns (pattern role models). To achieve understandability, we represent the role metamodel and pattern role models visually using UML. Our pattern role models provide a precise basis for pattern-based model transformations or refactoring approaches.

Architectural design in object-z

We present a process for introducing an object-oriented architecture into an abstract functional specification written in Object-Z. Since the design is derived from the specification, correctness concerns are addressed as pan of the design process. We base our approach on refactoring rules that apply to class structure, and use the rules to implement design patterns. As a motivating example, we introduce a user-interface design that follows the model-view-controller paradigm into an existing specification.

An object-orient designed FDTD simulator: Applications to high field systems

An object-oriented finite-difference time-domain (FDTD) simulator has been developed for electromagnetic study and design applications in Magnetic Resonance Imaging. It is aimed to be a complete FDTD model of an MRI system including all high and low-frequency field generating units and electrical models of the patient. The design method is described and MRI-based numerical examples are presented to illustrate the function of the numerical solver, particular emphasis is placed on high field studies.