A family of similarity measures between two strings

We present a class of similarity measures for quantitatively comparing two strings, that is, two linearly ordered sets of elements. The strings can be of different lengths, the elements come from a single alphabet, and an element may appear any number of times. The limiting values of each measure are 0, when two completely different strings are compared, and 1, when the two strings are identical. Applications of similarity measures are numerous in nonnumerical computations, such as in heuristic search processes in associative networks, in pattern recognition and classification, in game playing programs, and in music and text analysis. We offer a number of feasible measures from among which some are discarded on plausibility grounds. One can select the measure most adequate for one's needs on the basis of a few characteristic examples of strings compared and by considering the specific requirements of the application at hand.     

Split-sum correlator simplifies range computations in GPS receiver

A novel correlator architecture for handling the satellite-to-receiver time skew in a Global Positioning System (GPS) receiver is presented. The correlator's signal integration and numerically-controlled oscillator updates are referenced to receiver time epochs rather than satellite epochs as in traditional architectures. To avoid straddling navigation data bits, the correlation is split into two parts. The technique was successfully implemented and integrated into a field programmable gate array-based multichannel software GPS receiver     

Measuring the sensitivity of microwave components to bias variations

This paper presents a method to measure the sensitivity of microwave components to memory effects caused by the dc biasing circuit. This allows us to determine the required (impedance) properties of the dc biasing circuit to reduce slow dynamics under a certain level. The proposed measurement technique is based on the nonlinear vectorial network analyzer, which allows us to measure not only the absolute magnitude but also the absolute phase relations between the waves. Superimposing a multisine excitation signal on the dc bias allows us to measure the slow dynamics caused by the dc biasing circuit as a function of frequency and input power. Furthermore, it is verified whether or not the measured phenomena depend on the type of excitation signal.     

Differential automatic zero-adjusting amplifier

A method is described for building a low-voltage-drift differential dc amplifier featuring automatic zero adjustment, a high input impedance, and a bandwidth of 10 kHz. This is achieved by an asymmetric two-step process between the input signal and ground. Bandwidth can be extended by the use of a second amplifier during the ground-sampling time. The amplifier can be made with standard electronic components. A major advantage of this method is that an existing amplifier can easily be converted into a low-voltage-drift amplifier by adding the essential elements of the described automatic zero-adjusting amplifier to its input stage. To illustrate the method a practical example is constructed featuring a drift of 0.2 microV/ degrees C.     

Nonparallel training for voice conversion based on a parameter adaptation approach

The objective of voice conversion algorithms is to modify the speech by a particular source speaker so that it sounds as if spoken by a different target speaker. Current conversion algorithms employ a training procedure, during which the same utterances spoken by both the source and target speakers are needed for deriving the desired conversion parameters. Such a (parallel) corpus, is often difficult or impossible to collect. Here, we propose an algorithm that relaxes this constraint, i.e., the training corpus does not necessarily contain the same utterances from both speakers. The proposed algorithm is based on speaker adaptation techniques, adapting the conversion parameters derived for a particular pair of speakers to a different pair, for which only a nonparallel corpus is available. We show that adaptation reduces the error obtained when simply applying the conversion parameters of one pair of speakers to another by a factor that can reach 30%. A speaker identification measure is also employed that more insightfully portrays the importance of adaptation, while listening tests confirm the success of our method. Both the objective and subjective tests employed, demonstrate that the proposed algorithm achieves comparable results with the ideal case when a parallel corpus is available.     

Use of topographic correction in Landsat TM-based forest interpretation in Nepal

The land use of two districts in western Nepal was classified into forest and non-forest by satellite imagery with different topographical corrections. The accuracy of the forest biomass and timber volume estimates was also tested. The forest areas were interpretated correctly, with an accuracy of 82-88%. The best result was derived when the Minnaert constants of forest were separated from those of other land uses which were combined. The timber volume and biomass estimates were computed using the weighted nearest neighbour method. The coefficients of determination were 0.06 for timber volume and 0.09 for biomass. The use of the existing land use data seems to have potential for improving the results of topographic normalization. Because the reflectance in mountainous areas depends on many vegetative and terrain features, the simple non-Lambertian correction over broad categories did not significantly improve the results.     

An emergent approach to systems of physical agents

For the past ten years the author has been involved in industrial research on applications of agent architectures to manufacturing, and is presently technical advisor to an industrial consortium that is fielding pilot tests of shop-floor agents. The specific problem addressed by most of their work is the management of material flow and resource utilization on the factory floor. Classically, these problems have been considered under the rubrics of ‘scheduling’ and ‘shop-floor control’, and have been addressed with top-down control that does not offer the robustness and agility required in modern competitive environments. The approach has been to reify parts and equipment as agents, and seek architectures that permit the overall shop schedule to emerge dynamically from their interaction, rather than being imposed top-down.     

On operator effectiveness: the role of expertise and familiarity of environment on the detection of deviant behaviour

This paper examines factors contributing to the effectiveness of camera operators in urban camera surveillance. The use of camera surveillance has taken an enormous flight in the past decades. Despite this increase, its effectiveness is strongly debated. One reason for the disputed effectiveness may be that an understanding of how to use camera surveillance, including elements contributing to the effectiveness of camera operators, has not kept track with technological developments. This paper focuses on the role of expertise and familiarity with the environment on the effectiveness of camera operators to detect offenders in video footage from Rotterdam City Surveillance in the Netherlands. Results show no effect of expertise, but do show that familiarity with the location contributes to operator effectiveness and that camera operators seem to use different criteria for detecting and selecting suspects depending on the familiarity with the location. These results contribute to our understanding of operator effectiveness and offer guidelines for the training of camera operators. Implications are discussed.     

Ubiquitous emotion-aware computing

Emotions are a crucial element for personal and ubiquitous computing. What to sense and how to sense it, however, remain a challenge. This study explores the rare combination of speech, electrocardiogram, and a revised Self-Assessment Mannequin to assess people’s emotions. 40 people watched 30 International Affective Picture System pictures in either an office or a living-room environment. Additionally, their personality traits neuroticism and extroversion and demographic information (i.e., gender, nationality, and level of education) were recorded. The resulting data were analyzed using both basic emotion categories and the valence--arousal model, which enabled a comparison between both representations. The combination of heart rate variability and three speech measures (i.e., variability of the fundamental frequency of pitch (F0), intensity, and energy) explained 90% (p < .001) of the participants’ experienced valence--arousal, with 88% for valence and 99% for arousal (ps < .001). The six basic emotions could also be discriminated (p < .001), although the explained variance was much lower: 18–20%. Environment (or context), the personality trait neuroticism, and gender proved to be useful when a nuanced assessment of people’s emotions was needed. Taken together, this study provides a significant leap toward robust, generic, and ubiquitous emotion-aware computing.