XMobile: A MB-UID environment for semi-automatic generation of adaptive applications for mobile devices

Ubiquitous Computing promises seamless access to information anytime, anywhere with different and heterogeneous devices. This kind of environment imposes new challenges to software development. For example, information and user interface should be adapted according to contextual characteristics such as user, environment, and access device. In case of device adaptation, the development challenge is related to the heterogeneity of the devices, which requires software engineers to create different versions for each type of device and every platform. This paper proposes a MB-UID (model-based user interface development) approach for semi-automatic generation of adaptive applications for mobile devices. An environment, called XMobile, offers a device-independent user interface framework and a code generation tool for providing fast development of multi-platform and adaptive applications according to device and platform features. A case study is also presented to illustrate how the environment can be used for constructing an application for heterogeneous devices with different network connectivity modes.     

Modelling the three-dimensional elastic constants of parallel-fibred and lamellar bone

The complex hierarchical structure of lamellar bone makes understanding structure–mechanical function relations, very difficult. We approach the problem by first using the relatively simple structure of parallel-fibred bone to construct a mathematical model for calculating Young's moduli in three-dimensions. Parallel-fibred bone is composed essentially of arrays of mineralized collagen fibrils, which are also the basic structural motif of the individual lamellae of lamellar bone. Parallel-fibred bone structure has orthotropic symmetry. As the sizes and shapes of crystals in bone are not well known, the model is also used to compare the cases of platelet-, ribbon- and sheet-reinforced composites. The far more complicated rotated plywood structure of lamellar bone results in the loss of the orthotropic symmetry of individual lamellae. The mathematical model used circumvents this problem by sub-dividing the lamellar unit into a thin lamella, thick lamella, transition zone between them, and the recently observed back-flip lamella. Each of these is regarded as having orthotropic symmetry. After the calculation of their Young's moduli they are rotated in space in accordance with the rotated plywood model, and then the segments are combined to present the overall modulus values in three-dimensions. The calculated trends compare well with the trends in microhardness values measured for circumferential lamellar bone. Microhardness values are, as yet, the only measurements available for direct comparison. Although the model is not directly applicable to osteonal bone, which is composed of many hollow cylinders of lamellar bone, the range of calculated modulus values and the trends observed for off-axis calculations, compare well with measured values. © 1998 Chapman & Hall     

Photorefractive processing for large adaptive phased arrays

An adaptive null-steering phased-array optical processor that utilizes a photorefractive crystal to time integrate the adaptive weights and null out correlated jammers is described. This is a beam-steering processor in which the temporal waveform of the desired signal is known but the look direction is not. The processor computes the angle(s) of arrival of the desired signal and steers the array to look in that direction while rotating the nulls of the antenna pattern toward any narrow-band jammers that may be present. We have experimentally demonstrated a simplified version of this adaptive phased-array-radar processor that nulls out the narrow-band jammers by using feedback-correlation detection. In this processor it is assumed that we know a priori only that the signal is broadband and the jammers are narrow band. These are examples of a class of optical processors that use the angular selectivity of volume holograms to form the nulls and look directions in an adaptive phased-array-radar pattern and thereby to harness the computational abilities of three-dimensional parallelism in the volume of photorefractive crystals. The development of this processing in volume holographic system has led to a new algorithm for phased-array-radar processing that uses fewer tapped-delay lines than does the classic time-domain beam former. The optical implementation of the new algorithm has the further advantage of utilization of a single photorefractive crystal to implement as many as a million adaptive weights, allowing the radar system to scale to large size with no increase in processing hardware.     

A Bayesian network approach to assess and predict software quality using activity-based quality models

ContextSoftware quality is a complex concept. Therefore, assessing and predicting it is still challenging in practice as well as in research. Activity-based quality models break down this complex concept into concrete definitions, more precisely facts about the system, process, and environment as well as their impact on activities performed on and with the system. However, these models lack an operationalisation that would allow them to be used in assessment and prediction of quality. Bayesian networks have been shown to be a viable means for this task incorporating variables with uncertainty.ObjectiveThe qualitative knowledge contained in activity-based quality models are an abundant basis for building Bayesian networks for quality assessment. This paper describes a four-step approach for deriving systematically a Bayesian network from an assessment goal and a quality model.MethodThe four steps of the approach are explained in detail and with running examples. Furthermore, an initial evaluation is performed, in which data from NASA projects and an open source system is obtained. The approach is applied to this data and its applicability is analysed.ResultsThe approach is applicable to the data from the NASA projects and the open source system. However, the predictive results vary depending on the availability and quality of the data, especially the underlying general distributions.ConclusionThe approach is viable in a realistic context but needs further investigation in case studies in order to analyse its predictive validity.     

Constant-phase-mode operation of the light-addressable potentiometric sensor

The constant-phase-mode operation of the light-addressable potentiometric sensor (LAPS) is proposed and demonstrated. In this new operation mode, the temporal change and the spatial distribution of the analyte concentration are recorded in the form of the bias voltage applied to the LAPS sensor plate, which is servo-controlled to maintain the phase of the photocurrent at a constant value with respect to the light modulation. The constant-phase-mode LAPS is advantageous for its wider measurement range and reduction of artifacts.     

Prediction of part orientation error tolerance of a robotic gripper

This paper presents a model which predicts the part orientation error tolerance of a three-fingered robotic gripper. The concept of “self-alignment” is introduced, where the gripper uses the grasping process to bring the workpiece into its final state of orientation. The gripper and part are represented mathematically, and initial contact locations upon grasp closure determined. This information is used to solve for the contact forces present, and criteria are developed to determine if beneficial part motion resulting in self-alignment is expected. The results are visualized via a boundary projected on a reference plane below the part. The model is validated experimentally with a number of part configurations with favorable results. This method presents a useful tool by which the mechanical designer can quantitatively predict the performance of an intuitively designed gripping system.     

Foot motions in manual material handling transfer tasks: a taxonomy and data from an automotive assembly plant

Ergonomic job analysis commonly applies static postural and biomechanical analysis tools to particular postures observed during manual material handling (MMH) tasks, usually focusing on the most extreme postures or those involving the highest loads. When these analyses are conducted prospectively using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses. In automotive assembly jobs, workers frequently take several steps between task elements, for example, picking up a part at one location and moving to another location to place it on the vehicle. A detailed understanding of the influence of task type and task sequence on the stepping pattern is necessary to accurately predict the foot placements associated with MMH tasks. The current study examined the patterns of foot motions observed during automotive assembly tasks. Video data for 529 pickup and delivery tasks from 32 automotive assembly jobs were analysed. A minimum of five cycles was analysed for each task. The approach angle, departure angle, hand(s) used, manipulation height and patterns of footsteps were coded from the video. Object mass was identified from the job information sheet provided by the assembly plant. Three independent raters coded each video and demonstrated an intraclass correlation coefficient of 0.54 for identification of the configuration of the lower extremities during terminal stance. Based on an analysis of the distribution of stepping behaviours during object transitions (pickups or deliveries), a transition classification system (TRACS) was developed. TRACS uses a compact notation to quantify the sequence of steps associated with a MMH transition. Five TRACS behaviour groups accounted for over 90% of the transition stepping behaviours observed in the assembly plant. Approximately two-thirds (68.4%) of the object transfers observed were performed with only one foot in contact with the ground during the terminal posture. The results from this paper suggest that a predictive model for choosing a transition stepping behaviour, coupled with a model to scale the selected foot behaviours, is needed to facilitate accurate prospective ergonomic analyses. This study proposes a method for categorising the stepping patterns associated with MMH tasks. The influence of task type and task sequence on the stepping patterns observed during several automotive assembly tasks is discussed. For prospective postural analyses conducted using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses.