Context Aware e-Learning Objects and their Types from the Perspective of the Object-Oriented Paradigm

The contribution of this article demonstrates how to identify context-aware types of e-Learning objects (eLOs) derived from the subject domains. This perspective is taken from an engineering point of view and is applied during requirements elicitation and analysis relating to present work in constructing an object-oriented (OO), dynamic, and adaptive model to build and deliver packaged e-Learning courses. Consequently, three preliminary subject domains are presented and, as a result, three primitive types of eLOs are posited. These types educed from the subject domains are of structural, conceptual, and granular nature. Structural objects are responsible for the course itself, conceptual objects incorporate adaptive and logical interoperability, while granular objects congregate granular assets. Their differences, interrelationships, and responsibilities are discussed. A major design challenge relates to adaptive behaviour. Future research addresses refinement on the subject domains and adaptive hypermedia systems.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.

A Mathematical Model for Simplifying Representations of Objects in a Geographic Information System

The study of operations on representations of objects is well documented in the realm of spatial engineering. However, the mathematical structure and formal proof of these operational phenomena are not thoroughly explored. Other works have often focused on query-based models that seek to order classes and instances of objects in the form of semantic hierarchies or graphs. In some models, nodes of graphs represent objects and are connected by edges that represent different types of coarsening operators. This work, however, studies how the coarsening operator "simplification" can manipulate partitions of finite sets, independent from objects and their attributes. Partitions that are "simplified first have a collection of elements filtered (removed), and then the remaining partition is amalgamated (some sub-collections are unified). Simplification has many interesting mathematical properties. A finite composition of simplifications can also be accomplished with some single simplification. Also, if one partition is a simplification of the other, the simplified partition is defined to be less than the other partition according to the simp relation. This relation is shown to be a partial-order relation based on simplification. Collections of partitions can not only be proven to have a partial- order structure, but also have a lattice structure and are complete. In regard to a geographic information system (GIs), partitions related to subsets of attribute domains for objects are called views. Objects belong to different views based whether or not their attribute values lie in the underlying view domain. Given a particular view, objects with their attribute n-tuple codings contained in the view are part of the actualization set on views, and objects are labeled according to the particular subset of the view in which their coding lies. Though the scope of the work does not mainly focus on queries related directly to geographic objects, it provides verification for the existence of particular views in a system with this underlying structure. Given a finite attribute domain, one can say with mathematical certainty that different views of objects are partially ordered by simplification, and every collection of views has a greatest lower bound and least upper bound, which provides the validity for exploring queries in this regard.

Alexander’s Dictum and the Reality of Familiar Objects

Alexander's Dictum--"to be is to have causal powers"--appears to furnish an argument against the reality of familiar medium-sized objects. For every time a familiar object appears to cause a familiar macro-event, it sets up a rival claim by its component microparticles to have caused the complex swarm of microphysical events that composes into that macro-event. But this argument, argues this paper, wrongly assumes that even after familiar objects are removed from the picture, there is a phenomenon of joint causation which unites all and only the microparticles within each familiar object.

Glassy objects from DSDP Hole 5-32 in the northeastern Pacific Ocean

Small glassy spheres, ellipsoids, teardrops, cylinders and dumbbells occur in large numbers in Tertiary deep sea clays cored in the northeastern Pacific by the Deep Sea Drilling Project. These objects morphologically resemble microtektites, but have the composition of an oceanic tholeiite. On the basis of their composition and stratigraphic relationship it is considered that they are of volcanic origin and most likely have been formed in deep water by submarine volcanic processes.

Colored dissolved organic matter (cDOM) absorption measurements in terrestrial water objects of Yamal, Yavai and Gydan Peninsula

The datasets present measurements of cDOM absorption in lakes, rivers and streams of Yamal and Gydan Peninsula area during the summer periods from 2012-2014 and 2016. In summer seasons of 2012 - 2013 water samples was collected during "Yamal-Arctic" Expedition. All of the research areas were located near the coastline of Yamal, Yavay, and Gydan Peninsula and Bely Island. In 2012 water samples from rivers, lakes and streams were taken near New Port, Cape Kamenny and Tambey settlements and in basins (water catchments) of the Sabetta, Seyakha, Yuribey (Baydaratskaya Bay, Gydan Peninsula) and Mongocheyakha rivers. In 2013 water samples from rivers, lakes and streams were taken in the Yavai Peninsula, Yayne Vong bay and in the basins (water catchments) of the Sabetta, Mongocheyakha and Yuribey (Gydan Peninsula) rivers. In 2014 lakes were sampled in the Erkuta River basin, south of Yamal Peninsula. In 2016 lakes and rivers were sampled it the Erkuta River basin and Polar Ural area. cDOM is operationally defined by the chosen filter pore size. Samples have been consistently filtrated through 0.7 µm pore size glas fibre filters. cDOM filtrates have been stored in darkness and have been measured after the expedition using the dual-beam Specord200 laboratory spectrometer (Jena Analytik) at the Otto Schmidt Laboratory OSL, Arctic and Antarctic Research Institute, St. Petersburg, Russia. The OSL cDOM protocol (Heim and Roessler, 2016) prescribes 3 Absorbance (A) measurements per sample from UV to 750 nm against ultra-pure water. The absorption coefficient, a, is calculated by a = 2.303A/L, where L is the pathlength of the cuvette [m], and the factor 2.303 converts log10 to loge. The output of the calculation is a continuous spectrum of a. The cDOM a spectra are used to determine the exponential slope value for specific wavelength ranges, S by fitting the data between min and max wavelength to an exponential function. We provide cDOM absorption coefficients for the wavelengths 254, 260, 350, 375, 400, 412, 440, 443 nm [1/m] and Slope values for three different UV, VIS, wavelength ranges: 275 to 295 nm, 350 to 400 nm, 300 to 500 nm [1/m]. All data were carried out by scientists from Arctic and Antarctic Research Institute and Saint Petersburg State University of Russia during "Yamal-Arctic" expeditions in 2012-2013, RFBR project No 14-04-10065 in 2014, No 14-05-00787 in 2016.

Unimanual and Bimanual Weight Perception of Virtual Objects with a new Multi-finger Haptic Interface

Accurate weight perception is important particularly in tasks where the user has to apply vertical forces to ensure safe landing of a fragile object or precise penetration of a surface with a probe. Moreover, depending on physical properties of objects such as weight and size we may switch between unimanual and bimanual manipulation during a task. Research has shown that bimanual manipulation of real objects results in a misperception of their weight: they tend to feel lighter than similarly heavy objects which are handled with one hand only [8]. Effective simulation of bimanual manipulation with desktop haptic interfaces should be able to replicate this effect of bimanual manipulation on weight perception. Here, we present the MasterFinger-2, a new multi-finger haptic interface allowing bimanual manipulation of virtual objects with precision grip and we conduct weight discrimination experiments to evaluate its capacity to simulate unimanual and bimanual weight. We found that the bimanual ‘lighter’ bias is also observed with the MasterFinger-2 but the sensitivity to changes of virtual weights deteriorated.

Enhancing Interaction With Smart Objects Throught Mobile Devices

Interaction with smart objects can be accomplished with different technologies, such as tangible interfaces or touch computing, among others. Some of them require the object to be especially designed to be 'smart', and some other are limited in the variety and complexity of the possible actions. This paper describes a user-smart object interaction model and prototype based on the well known event-condition-action (ECA) reasoning, which can work, to a degree, independently of the intelligence embedded into the smart object. It has been designed for mobile devices to act as mediators between users and smart objects and provides an intuitive means for personalization of object's behavior. When the user is close to an object, this one publishes its 'event & action' capabilities to the user's device. The user may accept the object's module offering, which will enable him to configure and control that object, but also its actions with respect to other elements of the environment or the virtual world. The modular ECA interaction model facilitates the integration of different types of objects in a smart space, giving the user full control of their capabilities and facilitating creative mash-uping to build customized functionalities that combine physical and virtual actions

A simple approach to distributed objects in prolog

We present the design of a distributed object system for Prolog, based on adding remote execution and distribution capabilities to a previously existing object system. Remote execution brings RPC into a Prolog system, and its semantics is easy to express in terms of well-known Prolog builtins. The final distributed object design features state mobility and user-transparent network behavior. We sketch an implementation which provides distributed garbage collection and some degree of tolerance to network failures. We provide a preliminary study of the overhead of the communication mechanism for some test cases.

Objects-based Image Analysis for Mapping Natura 2000 Habitats to Improve Forest Management.

Clasificación de una imagen de alta resolución "Quickbird" con la técnica de análisis de imágenes en base a objetos

An attitude-based reasoning strategy to enhance interaction with augmented objects

This paper describes a mobile-based system to interact with objects in smart spaces, where the offer of resources may be extensive. The underlying idea is to use the augmentation capabilities of the mobile device to enable it as user-object mediator. In particular, the paper details how to build an attitude-based reasoning strategy that facilitates user-object interaction and resource filtering. The strategy prioritizes the available resources depending on the spatial history of the user, his real-time location and orientation and, finally, his active touch and focus interactions with the virtual overlay. The proposed reasoning method has been partially validated through a prototype that handles 2D and 3D visualization interfaces. This framework makes possible to develop in practice the IoT paradigm, augmenting the objects without physically modifying them.

Towards a lightweight mobile semantic-based approach for enhancing interaction with smart objects

This work describes a semantic extension for a user-smart object interaction model based on the ECA paradigm (Event-Condition-Action). In this approach, smart objects publish their sensing (event) and action capabilities in the cloud and mobile devices are prepared to retrieve them and act as mediators to configure personalized behaviours for the objects. In this paper, the information handled by this interaction system has been shaped according several semantic models that, together with the integration of an embedded ontological and rule-based reasoner, are exploited in order to (i) automatically detect incompatible ECA rules configurations and to (ii) support complex ECA rules definitions and execution. This semantic extension may significantly improve the management of smart spaces populated with numerous smart objects from mobile personal devices, as it facilitates the configuration of coherent ECA rules.