On resource allocation in multistage interconnection network-based systems

A resource allocation problem in a reconfigurable multicomputer architecture based on rectangular banyan multistage interconnection network with arbitrary fanout and arbitrary number of levels is studied. Four commonly used problem structures such as ring, pipeline, broadcast, and macropipeline are introduced and the mapping problem of these structures on the system model, which is equivalent to the resource allocation problem, is discussed. Analytic solutions to several mapping questions are given and generalization of the results to other networks is presented.     

Neural clustering networks based on global optimisation of prototypes in metric spaces

The utilisation of clustering algorithms based on the optimisation of prototypes in neural networks is demonstrated for unsupervised learning. Stimulated by common clustering methods of this type (learning vector quantisation [LVQ, GLVQ] and K-means) a globally operating algorithm was developed to cope with known shortcomings of existing tools. This algorithm and K-means (for the common methods) were applied to the problem of clustering EEG patterns being pre-processed. It can be shown that the algorithm based on global random optimisation may find an optimal solution repeatedly, whereas K-means provides different sub-optimal solutions with respect to the quality measure defined as objective function. The results are presented. The performance of the algorithms is discussed.     

Electrical and thermophysical properties of mechanochemically obtained lanthanide hafnates

This contribution presents the synthesis and thermophysical characterization of seven lanthanide hafnates Ln₂Hf₂O₇ (Ln=Sm³⁺, Eu³⁺, Gd³⁺, Dy³⁺, Y³⁺, Ho³⁺, Yb³⁺); the title samples were prepared at room temperature by mechanically milling stoichiometric mixtures of the corresponding elemental oxides. Irrespective of the lanthanide ion involved, milling promotes the formation of highly disordered fluoritelike materials. Postmilling thermal treatments facilitate the formation of the fluorite ordered derivative, the pyrochlore structure, but only for the larger lanthanides (Sm³⁺, Eu³⁺, Gd³⁺). Impedance spectroscopy measurements revealed that these materials show a moderate‐to‐good oxygen ion conductivity at high temperatures; furthermore, those adopting the pyrochlore structure give higher σ_dc and lower E_dc than their fluorite analogues (σ_dc at 750°C>10^?3 S·cm^?1 vs <5·10^?4 S·cm^?1, respectively). The same trend also holds for the thermal resistivity at high temperatures; the highest thermal resistivity and thus, lowest κ was obtained for Eu₂Hf₂O₇ (κ~1.3·W·m^?1·K^?1 at 800°C). Therefore, Ln₂Hf₂O₇ phases might be attractive component materials for electrochemical devices and thermal insulating coatings.     

Virtual lifeline: Multimodal sensor data fusion for robust navigation in unknown environments

We present a novel, multimodal indoor navigation technique that combines pedestrian dead reckoning (PDR) with relative position information from wireless sensor nodes. It is motivated by emergency response scenarios where no fixed or pre-deployed global positioning infrastructure is available and where typical motion patterns defeat standard PDR systems. We use RF and ultrasound beacons to periodically re-align the PDR system and reduce the impact of incremental error accumulation. Unlike previous work on multimodal positioning, we allow the beacons to be dynamically deployed (dropped by the user) at previously unknown locations. A key contribution of this paper is to show that despite the fact that the beacon locations are not known (in terms of absolute coordinates), they significantly improve the performance of the system. This effect is especially relevant when a user re-traces (parts of) the path he or she had previously travelled or lingers and moves around in an irregular pattern at single locations for extended periods of time. Both situations are common and relevant for emergency response scenarios. We describe the system architecture, the fusion algorithms and provide an in depth evaluation in a large scale, realistic experiment.     

Mobile phones as medical devices in mental disorder treatment: an overview

Mental disorders can have a significant, negative impact on sufferers’ lives, as well as on their friends and family, healthcare systems and other parts of society. Approximately 25 % of all people in Europe and the USA experience a mental disorder at least once in their lifetime. Currently, monitoring mental disorders relies on subjective clinical self-reporting rating scales, which were developed more than 50 years ago. In this paper, we discuss how mobile phones can support the treatment of mental disorders by (1) implementing human–computer interfaces to support therapy and (2) collecting relevant data from patients’ daily lives to monitor the current state and development of their mental disorders. Concerning the first point, we review various systems that utilize mobile phones for the treatment of mental disorders. We also evaluate how their core design features and dimensions can be applied in other, similar systems. Concerning the second point, we highlight the feasibility of using mobile phones to collect comprehensive data including voice data, motion and location information. Data mining methods are also reviewed and discussed. Based on the presented studies, we summarize advantages and drawbacks of the most promising mobile phone technologies for detecting mood disorders like depression or bipolar disorder. Finally, we discuss practical implementation details, legal issues and business models for the introduction of mobile phones as medical devices.     

Assessing the impact of meta-model evolution: a measure and its automotive application

Software and Systems Modeling - Domain-specific meta-models play an important role in the design of large software systems by defining language for the architectural models. Such common modeling...     

Multi-CMP system with data communication on the fly

The paper concerns new communication solutions for hierarchical Chip Multiprocessor (CMP) systems composed of many CMP modules interconnected by a global data exchange network. New architectural solutions for internal module data communication are presented in the presence of hierarchical data caches in CMP modules. Inside CMP modules, dynamic shared memory core clusters are organized around L1–L2 data cache busses. Such clusters enable a group-oriented data communication based on reads on the fly to L1 banks of data present on the busses by many cores at a time. Dynamic switching of cores between such L1–L2 busses is done with porting data in core’s L1 caches. Together with data reads on the fly, it provides a very efficient intercluster “communication on the fly,” especially useful for transfers of strongly shared data. It provides fast cache to cache group data transmissions and eliminates standard transactions based on shared memory in the system. Comparative experimental results based on automatic scheduling of program data flow graphs and execution in a simulator of the proposed architecture evaluate the assumed architectural solutions. The multi-CMP system structure is assessed while taking into account technological limitations of the size of the single CMP module.     

Evaluating code complexity triggers,use of complexity measures and the influence of code complexity on maintenance time

Code complexity has been studied intensively over the past decades because it is a quintessential characterizer of code’s internal quality. Previously, much emphasis has been put on creating code complexity measures and applying these measures in practical contexts. To date, most measures are created based on theoretical frameworks, which determine the expected properties that a code complexity measure should fulfil. Fulfilling the necessary properties, however, does not guarantee that the measure characterizes the code complexity that is experienced by software engineers. Subsequently, code complexity measures often turn out to provide rather superficial insights into code complexity. This paper supports the discipline of code complexity measurement by providing empirical insights into the code characteristics that trigger complexity, the use of code complexity measures in industry, and the influence of code complexity on maintenance time. Results of an online survey, conducted in seven companies and two universities with a total of 100 respondents, show that among several code characteristics, two substantially increase code complexity, which subsequently have a major influence on the maintenance time of code. Notably, existing code complexity measures are poorly used in industry.     

From Backpacks to Smartphones: Past, Present, and Future of Wearable Computers

Do smart phones render wearable computers obsolete? Where does the rise of the smart phone leave wearable computing research? We answer these questions by examining past, present, and future of wearable platform research.     

Gesture spotting with body-worn inertial sensors to detect user activities

We present a method for spotting sporadically occurring gestures in a continuous data stream from body-worn inertial sensors. Our method is based on a natural partitioning of continuous sensor signals and uses a two-stage approach for the spotting task. In a first stage, signal sections likely to contain specific motion events are preselected using a simple similarity search. Those preselected sections are then further classified in a second stage, exploiting the recognition capabilities of hidden Markov models. Based on two case studies, we discuss implementation details of our approach and show that it is a feasible strategy for the spotting of various types of motion events.