Ubiquitous interaction with positioning and navigation using a novel light sensor-based information transmission system

This paper describes a novel light sensor-based information transmission system for indoor positioning and navigation with particular benefits for mobile and wearable computers. It can seamlessly extend outdoor GPS tracking to the indoor environment. In a novel manner, fluorescent light is used as the medium to transmit information, which is encoded by using a pulse-frequency modulation technique. The user receives the encoded light information through a photo-receiver. The information is passed into the wearable or mobile computer after the data is decoded. This information allows positioning information to be given to indoor mobile and wearable computers. We design an economical transmitter circuit by adding few components to a commercial electronic ballast circuit for fluorescent lamps with price of less than US $10. The propose system can be used in indoor guidance and navigation applications. Exemplary applications are included in the paper, with experimented results detailed.     

Hazard pointers: safe memory reclamation for lock-free objects

Lock-free objects offer significant performance and reliability advantages over conventional lock-based objects. However, the lack of an efficient portable lock-free method for the reclamation of the memory occupied by dynamic nodes removed from such objects is a major obstacle to their wide use in practice. We present hazard pointers, a memory management methodology that allows memory reclamation for arbitrary reuse. It is very efficient, as demonstrated by our experimental results. It is suitable for user-level applications - as well as system programs - without dependence on special kernel or scheduler support. It is wait-free. It requires only single-word reads and writes for memory access in its core operations. It allows reclaimed memory to be returned to the operating system. In addition, it offers a lock-free solution for the ABA problem using only practical single-word instructions. Our experimental results on a multiprocessor system show that the new methodology offers equal and, more often, significantly better performance than other memory management methods, in addition to its qualitative advantages regarding memory reclamation and independence of special hardware support. We also show that lock-free implementations of important object types, using hazard pointers, offer comparable performance to that of efficient lock-based implementations under no contention and no multiprogramming, and outperform them by significant margins under moderate multiprogramming and/or contention, in addition to guaranteeing continuous progress and availability, even in the presence of thread failures and arbitrary delays.     

Feature extraction of three-dimensional objects and visual processing in a hand-eye system using laser tracker

Visual processing is one of the important aspects in researches on an intelligent robot. This paper describes the principle and the construction of a laser tracker as a visual device with an active faculty. This robot's eye can acquire three-dimensional coordinates of a laser spot on an object based on triangulation and then extract features of the object corresponding to the purpose of the intelligent rogot. As its applications, classification of several three-dimensional objects and visual processing in a hand-eye system are performed.     

Reconstruction of three-dimensional objects using a knowledge-based environment

This paper presents a knowledge-based technique forunderstanding and reconstructing a class of three-dimensional objects from their two-dimensional orthographic views commonly found in machine drawings and blueprints. The reconstruction procedure uses a volume-oriented approach and views a complex part as composed of a number of primitive subobjects. These subobjects are recognized using a model-guided recognition scheme, utilizing characteristic patterns of the primitives in different views. Features such as protrusions and cavities are recognized and the composite part is transferred to a CAD data base.     

Introducing solid objects into a constraint modelling system

A constraint modelling system called RASOR allows the constraints between design parameters to be investigated by a designer. Some simple geometric entities are provided. The ACIS solid modeller provides procedures for handling solid objects. An integrated system in which ACIS solids are defined and manipulated by RASOR commands has been achieved. The use of constraints is illustrated with reference to the assembly of the links of a mechanical system.     

Distributed environment: A conceptual framework using objects

We present a conceptual framework for a distributed office system using concepts inherent to object-oriented formalism. The functions of the active object and the procedure servers are described. So are the attributes of the objects stored in these two servers. In order to endow the individual workstations with as much autonomy as possible, we develop a coarse-grained algorithm for active and procedural object distribution. An office model should have a high level of evolvability. To accommodate this phenomenon we devise a mechanism to enable the model to transit one state to another with a minimum level of perturbation.     

Personal technologies: memory and intimacy through physical computing

In this paper, I present an overview of personal and intimate technologies within a pedagogical context. I describe two courses that I have developed for Computation Arts at Concordia University: “Tangible Media and Physical Computing” and “Second Skin and Soft Wear.” Each course deals with different aspects of physical computing and tangible media in a Fine Arts context. In both courses, I introduce concepts of soft computation and intimate reactive artifacts as artworks. I emphasize the concept of memory (contrasting computer memory and personal, interpretive memory), and explore how responsive or interactive objects can create a new medium for annotating architectural space and objects, for leaving traces of presence, and for recording personal histories. At the core of this pedagogical practice is a strong emphasis on engaging a vulnerable, personal approach to working with electronics and physical computation. To contextualize the teaching practice, I begin by presenting some of my own research projects developed at Extra Soft Labs (also known as XS Labs), then segue into a detailed discussion of these two classes, and conclude with a discussion of some student work.

Efficient tracking of moving objects using a relational database

Tracking uncooperative moving objects by means of radar is a complex task due to clutter and association problems in multi-target scenarios. An approach to solve this problem is probabilistic multiple hypothesis tracking (PMHT). This method combines classical track filtering with a likelihood ratio test for the estimation of the plot-to-track association. The basics of PMHT and similar algorithms have gained much attention recently. However, the efficient implementation of real world applications of this technique still represents a challenging task. Since a common requirement in this context is the reliable storage of track data in a database, an implementation of the tracker's calculation inside a database management system (DBMS) using SQL views is desirable. A naive implementation of PMHT using a commercial DBMS, however, usually leads to performance problems because of the high frequency of measurement updates. In this paper, we propose possible optimizations for solving these performance problems. Their usage leads to a dramatic run-time improvement in our sample case and makes the implementation of PMHT in a database context feasible.     

Lidar detection of underwater objects using a neuro-SVM-based architecture

This paper presents a neural network architecture using a support vector machine (SVM) as an inference engine (IE) for classification of light detection and ranging (Lidar) data. Lidar data gives a sequence of laser backscatter intensities obtained from laser shots generated from an airborne object at various altitudes above the earth surface. Lidar data is pre-filtered to remove high frequency noise. As the Lidar shots are taken from above the earth surface, it has some air backscatter information, which is of no importance for detecting underwater objects. Because of these, the air backscatter information is eliminated from the data and a segment of this data is subsequently selected to extract features for classification. This is then encoded using linear predictive coding (LPC) and polynomial approximation. The coefficients thus generated are used as inputs to the two branches of a parallel neural architecture. The decisions obtained from the two branches are vector multiplied and the result is fed to an SVM-based IE that presents the final inference. Two parallel neural architectures using multilayer perception (MLP) and hybrid radial basis function (HRBF) are considered in this paper. The proposed structure fits the Lidar data classification task well due to the inherent classification efficiency of neural networks and accurate decision-making capability of SVM. A Bayesian classifier and a quadratic classifier were considered for the Lidar data classification task but they failed to offer high prediction accuracy. Furthermore, a single-layered artificial neural network (ANN) classifier was also considered and it failed to offer good accuracy. The parallel ANN architecture proposed in this paper offers high prediction accuracy (98.9%) and is found to be the most suitable architecture for the proposed task of Lidar data classification.     

Drawing pictures of solid objects using a graph plotter

This paper describes a method of producing shaded pictures of three-dimensional polyhedral objects in which the computer time depends only on the complexity of the objects and not on the resolution required. Objectives of the paper are to describe how hidden lines are detected and how the visible lines are assembled to form closed polygonal areas which may be shaded. The detection of hidden lines is carried out efficiently using a sorting technique. Visible lines are assembled to form closed polygons for shading, using programming devices such as the tree, the two-way list, the two-way circular list, and the stack.     

Mobile cloud-based physical activity advisory system using biofeedback sensors

Physical inactivity has gained a wide attention due to its negative influence on human wellness. Physical activity advisory systems consider a promising solution for this phenomenon. In this paper, we propose a mobile cloud-based physical activity advisory system utilizing biofeedback sensors and environmental context data based on calories expenditure from performing various activities by tracking user’s physical movements. To evaluate the proposed system, we conducted in total a three-month experiment on six users. For each user, we tracked the amount of burnt calories from the physical movements for a two-week period. During the first week, the system did not send any advice, while during the second week, the system was advising the user on activities to perform. The compared results of the two weeks collected data (without and with advice) reflect the positive effect of the proposed system on participants’ physical activity level. The system motivates them to reach or exceed the recommended number of calories to be burned daily.     

Handling inheritance in a system integrating logic in objects

The inheritance mechanism of SILO, a system integrating a many-sorted logic within an object-based framework, is presented. In order to be adequate for knowledge representation, it comprises two components, a hardwired and a user-definable. Due to use of typed (sorted) terms, a variety of specialisation types between logical formulas (axioms) are introduced and defined. Thus, the hardwired component is able to represent a variety of inheritance/specialisation relations between objects. The notion of a conflict is defined and conflict detection theorems are introduced. Also, consequence retraction is introduced and used alongside attribute/predicate overriding to resolve conflicts. The user-definable component consists of a number of user definable functions, called meta-functions, which are able to implement both global and local inheritance control. It is based on a partial reflection meta-level architecture.     

Resegmentation using generic shape: Locating general cultural objects

As a step toward automating the ability to locate generic objects in an image, we propose an approach based on model-driven correction of an initial low-level scene partition. To accomplish this, we define generic data structures for geometric shapes, along with robust rules for parsing the image geometry and performing a shape-motivated resegmentation. We successfully apply the system to the task of locating and outlining complex rectilinear cultural objects in aerial imagery.     

Interface methods for using intranet portal organizational memory information system

In this paper, an intranet portal is considered as an information infrastructure (organizational memory information system, OMIS) supporting organizational learning. The properties and the hierarchical structure of information and knowledge in an intranet portal OMIS was identified as a problem for navigation tools of an intranet portal interface. The problem relates to navigation and retrieval functions of intranet portal OMIS and is expected to adversely affect user performance, satisfaction, and usefulness. To solve the problem, a conceptual model for navigation tools of an intranet portal interface was proposed and an experiment using a crossover design was conducted with 10 participants. In the experiment, a separate access method (tabbed tree tool) was compared to an unified access method (single tree tool). The results indicate that each information/knowledge repository for which a user has a different structural knowledge should be handled separately with a separate access to increase user satisfaction and the usefulness of the OMIS and to improve user performance in navigation.     

Interface methods for using intranet portal organizational memory information system

In this paper, an intranet portal is considered as an information infrastructure (organizational memory information system, OMIS) supporting organizational learning. The properties and the hierarchical structure of information and knowledge in an intranet portal OMIS was identified as a problem for navigation tools of an intranet portal interface. The problem relates to navigation and retrieval functions of intranet portal OMIS and is expected to adversely affect user performance, satisfaction, and usefulness. To solve the problem, a conceptual model for navigation tools of an intranet portal interface was proposed and an experiment using a crossover design was conducted with 10 participants. In the experiment, a separate access method (tabbed tree tool) was compared to an unified access method (single tree tool). The results indicate that each information/knowledge repository for which a user has a different structural knowledge should be handled separately with a separate access to increase user satisfaction and the usefulness of the OMIS and to improve user performance in navigation.     

ARCHI: An expert system for biological objects recognition

From the biological sample to the final decision, a computer vision system splits its process in many levels: image acquisition, preprocessing, segmentation, postprocessing, measurement, decision. Most often, the human operator acts upon one or more of these levels, either to drive or to confirm the processing, either to do it himself.ARCHI system acts in two ways: first to drive the acquisition, preprocessing and segmentation steps (driving part), second, to filter contours issued by segmentation according to morphological or color parameters, learned during previous steps (recognition part).At every level, decisions are taken according to (i) the biological knowledge of the field, (ii) the objects which are looked for, (iii) and the associated artefacts. That can possibly imply a modification of previous steps (control and feedback). Moreover, the knowledge of the objects can adapt itself to the sample.     

Pattern classification using a linear associative memory

Pattern classification is a very important image processing task. A typical pattern classification algorithm can be broken into two parts; first, the pattern features are extracted and, second, these features are compared with a stored set of reference features until a match is found. In the second part, usually one of the several clustering algorithms or similarity measures is applied. In this paper, a new application of linear associative memory (LAM) to pattern classification problems is introduced. Here, the clustering algorithms or similarity measures are replaced by a LAM matrix multiplication. With a LAM, the reference features need not be separately stored. Since the second part of most classification algorithms is similar, a LAM standardizes the many clustering algorithms and also allows for a standard digital hardware implementation. Computer simulations on regular textures using a feature extraction algorithm achieved a high percentage of successful classification. In addition, this classification is independent of topological transformations.