inTrack: High Precision Tracking of Mobile Sensor Nodes

Radio-interferometric ranging is a novel technique that allows for fine-grained node localization in networks of inexpensive COTS nodes. In this paper, we show that the approach can also be applied to precision tracking of mobile sensor nodes. We introduce inTrack, a cooperative tracking system based on radio-interferometry that features high accuracy, long range and low-power operation. The system utilizes a set of nodes placed at known locations to track a mobile sensor. We analyze how target speed and measurement errors affect the accuracy of the computed locations. To demonstrate the feasibility of our approach, we describe our prototype implementation using Berkeley motes. We evaluate the system using data from both simulations and field tests

Whirl measurements on leakage flows in turbomachine models

The beneficial effects claimed for whirl control devices demonstrate that the dynamic behavior of rotors is influenced by the fluid whirl in shaft and balance drum seals. The present paper reports results from two series of experiments, the first on the factors affecting the whirl at the seal inlet, and the second on the variation of whirl velocity along the seal. In both cases the LDA measurement technique required the clearance between the fixed and rotating parts of the models to be substantially greater than occurs in real machines, but the results are indicative nevertheless. Experimental and theoretical results are given for the radial distribution of whirl velocity in the gap between impeller shroud and pump casing. Results of tests with modified stator surfaces are also shown. This work leads naturally into the second series of experiments where some preliminary measurements of velocity distribution in the clearance between a fixed stator and a rotating shaft are reported for a range of inlet whirl conditions

Supporting Device Discovery and Spontaneous Interaction with Spatial References

The RELATE interaction model is designed to support spontaneous interaction of mobile users with devices and services in their environment. The model is based on spatial references that capture the spatial relationship of a user’s device with other co-located devices. Spatial references are obtained by relative position sensing and integrated in the mobile user interface to spatially visualize the arrangement of discovered devices, and to provide direct access for interaction across devices. In this paper we discuss two prototype systems demonstrating the utility of the model in collaborative and mobile settings, and present a study on usability of spatial list and map representations for device selection

You have interrupted me again!: making voice assistants more dementia-friendly with incremental clarification

In spontaneous conversation, speakers seldom have a full plan of what they are going to say in advance: they need to conceptualise and plan incrementally as they articulate each word in turn. This often leads to long pauses mid-utterance. Listeners either wait out the pause, offer a possible completion, or respond with an incremental clarification request (iCR), intended to recover the rest of the truncated turn. The ability to generate iCRs in response to pauses is therefore important in building natural and robust everyday voice assistants (EVA) such as Amazon Alexa. This becomes crucial with people with dementia (PwDs) as a target user group since they are known to pause longer and more frequently, with current state-of-the-art EVAs interrupting them prematurely, leading to frustration and breakdown of the interaction. In this article, we first use two existing corpora of truncated utterances to establish the generation of clarification requests as an effective strategy for recovering from interruptions. We then proceed to report on, analyse, and release SLUICE-CR: a new corpus of 3,000 crowdsourced, human-produced iCRs, the first of its kind. We use this corpus to probe the incremental processing capability of a number of state-of-the-art large language models (LLMs) by evaluating (1) the quality of the model's generated iCRs in response to incomplete questions and (2) the ability of the said LLMs to respond correctly after the users response to the generated iCR. For (1), our experiments show that the ability to generate contextually appropriate iCRs only emerges at larger LLM sizes and only when prompted with example iCRs from our corpus. For (2), our results are in line with (1), that is, that larger LLMs interpret incremental clarificational exchanges more effectively. Overall, our results indicate that autoregressive language models (LMs) are, in principle, able to both understand and generate language incrementally and that LLMs can be configured to handle speech phenomena more commonly produced by PwDs, mitigating frustration with today's EVAs by improving their accessibility

Analysis of Doppler Effect on the Pulse Compression of Different Codes Emitted by an Ultrasonic LPS

This work analyses the effect of the receiver movement on the detection by pulse compression of different families of codes characterizing the emissions of an Ultrasonic Local Positioning System. Three families of codes have been compared: Kasami, Complementary Sets of Sequences and Loosely Synchronous, considering in all cases three different lengths close to 64, 256 and 1,024 bits. This comparison is first carried out by using a system model in order to obtain a set of results that are then experimentally validated with the help of an electric slider that provides radial speeds up to 2 m/s. The performance of the codes under analysis has been characterized by means of the auto-correlation and cross-correlation bounds. The results derived from this study should be of interest to anyone performing matched filtering of ultrasonic signals with a moving emitter/receiver

User Identification Using Gait Patterns on UbiFloorII

This paper presents a system of identifying individuals by their gait patterns. We take into account various distinguishable features that can be extracted from a user’s gait and then divide them into two classes: walking pattern and stepping pattern. The conditions we assume are that our target environments are domestic areas, the number of users is smaller than 10, and all users ambulate with bare feet considering the everyday lifestyle of the Korean home. Under these conditions, we have developed a system that identifies individuals’ gait patterns using our biometric sensor, UbiFloorII. We have created UbiFloorII to collect walking samples and created software modules to extract the user’s gait pattern. To identify the users based on the gait patterns extracted from walking samples over UbiFloorII, we have deployed multilayer perceptron network, a feedforward artificial neural network model. The results show that both walking pattern and stepping pattern extracted from users’ gait over the UbiFloorII are distinguishable enough to identify the users and that fusing two classifiers at the matching score level improves the recognition accuracy. Therefore, our proposed system may provide unobtrusive and automatic user identification methods in ubiquitous computing environments, particularly in domestic areas

A paralog of a bacteriochlorophyll biosynthesis enzyme catalyzes the formation of 1,2-dihydro-carotenoids in green sulfur bacteria

Chlorobaculum tepidum, a green sulfur bacterium, utilizes chlorobactene as its major carotenoid, and this organism also accumulates a reduced form of this monocyclic pigment, 1',2'-dihydrochlorobactene. The protein catalyzing this reduction is the last unidentified enzyme in the biosynthetic pathways for all of the green sulfur bacterial pigments used for photosynthesis. The genome of Chlorobaculum tepidum contains two paralogous genes encoding members of the FixC family of flavoproteins: bchP, that has been shown to encode an enzyme of bacteriochlorophyll biosynthesis; and bchO, for which a function has not been assigned. Here we demonstrate that a bchO mutant is unable to synthesize 1',2'-dihydrochlorobactene, and when bchO is heterologously expressed in a neurosporene-producing mutant of the purple bacterium, Rhodobactersphaeroides, the encoded protein is able to catalyze the formation of 1,2-dihydroneurosporene, the major carotenoid of the only other organism reported to synthesize 1,2-dihydrocarotenoids, Blastochloris viridis Identification of this enzyme completes the pathways for the synthesis of photosynthetic pigments in Chlorobiaceae, and accordingly and consistent with its role in carotenoid biosynthesis, we propose to rename the gene, cruI Notably, the absence of cruI in Blastochloris viridis indicates that a second 1,2-carotenoid reductase, which is structurally unrelated to CruI (BchO), must exist in nature. The evolution of this carotenoid reductase in green sulfur bacteria is discussed herein

Local Positioning Systems in (Game) Sports

Position data of players and athletes are widely used in sports performance analysis for measuring the amounts of physical activities as well as for tactical assessments in game sports. However, positioning sensing systems are applied in sports as tools to gain objective information of sports behavior rather than as components of intelligent spaces (IS). The paper outlines the idea of IS for the sports context with special focus to game sports and how intelligent sports feedback systems can benefit from IS. Henceforth, the most common location sensing techniques used in sports and their practical application are reviewed, as location is among the most important enabling techniques for IS. Furthermore, the article exemplifies the idea of IS in sports on two applications