328 research outputs found

    Working out a common task: design and evaluation of user-intelligent system collaboration

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    This paper describes the design and user evaluation of an intelligent user interface intended to mediate between users and an Adaptive Information Extraction (AIE) system. The design goal was to support a synergistic and cooperative work. Laboratory tests showed the approach was efficient and effective; focus groups were run to assess its ease of use. Logs, user satisfaction questionnaires, and interviews were exploited to investigate the interaction experience. We found that user’ attitude is mainly hierarchical with the user wishing to control and check the system’s initiatives. However when confidence in the system capabilities rises, a more cooperative interaction is adopted

    Designing for the experiential body

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    The goal of this panel is to reflect on the past and discuss the present and future of designing for an experiencing body in HCI. The motivation is to discuss the full range of rich body/movement-based experiences and how the CHI community can embrace and extend these perspectives on designing for the body. The panelists and audience will be asked to share their perspectives on what has most influenced thought in designing for the body, how new sensing technologies are crafting the HCI perspective, and where they see this line of research and design heading in the next ten years

    Improving QPF by blending techniques at the Meteorological Service of Catalonia

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    The current operational very short-term and short-term quantitative precipitation forecast (QPF) at the Meteorological Service of Catalonia (SMC) is made by three different methodologies: Advection of the radar reflectivity field (ADV), Identification, tracking and forecasting of convective structures (CST) and numerical weather prediction (NWP) models using observational data assimilation (radar, satellite, etc.). These precipitation forecasts have different characteristics, lead time and spatial resolutions. The objective of this study is to combine these methods in order to obtain a single and optimized QPF at each lead time. This combination (blending) of the radar forecast (ADV and CST) and precipitation forecast from NWP model is carried out by means of different methodologies according to the prediction horizon. Firstly, in order to take advantage of the rainfall location and intensity from radar observations, a phase correction technique is applied to the NWP output to derive an additional corrected forecast (MCO). To select the best precipitation estimation in the first and second hour (t+1 h and t+2 h), the information from radar advection (ADV) and the corrected outputs from the model (MCO) are mixed by using different weights, which vary dynamically, according to indexes that quantify the quality of these predictions. This procedure has the ability to integrate the skill of rainfall location and patterns that are given by the advection of radar reflectivity field with the capacity of generating new precipitation areas from the NWP models. From the third hour (t+3 h), as radar-based forecasting has generally low skills, only the quantitative precipitation forecast from model is used. This blending of different sources of prediction is verified for different types of episodes (convective, moderately convective and stratiform) to obtain a robust methodology for implementing it in an operational and dynamic wa

    Maturation Schedules of Walleye Populations in the Great Lakes Region: Comparison of Maturation Indices and Evaluation of SamplingĂą Induced Biases

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    Maturation schedules, key determinants of fish stocks’ harvest potential and population dynamics, are influenced by both plastic and adaptive processes. Various indices are used to describe maturation schedules, and these have differential advantages for discriminating between plastic and adaptive processes. However, potential samplingñ related biases associated with different maturation indices have not been fully evaluated. We analyzed three maturation indices for walleyes Sander vitreus in Lake Erie; Saginaw Bay, Lake Huron; and Oneida Lake, New York: age and length at 50% maturity, midpoint of ageñ specific maturity ogives (ageñ specific length at which probability of maturity = 0.50), and midpoints of probabilistic maturation reaction norms (PMRNs; ageñ specific length at which probability of maturing in the following year = 0.50). We then compared estimated maturation indices to evaluate sensitivity of different maturation indices to samplingñ induced biases and to assess the relative importance of plastic versus adaptive processes in structuring interstock and temporal variation in maturation schedules. Our findings suggest that although small changes in sampling month, gear, and agencyñ related effects can bias estimates of age and length at 50% maturity and midpoints of maturity ogives, PMRN estimates appear to be robust to these biases. Furthermore, PMRN estimates are suggestive of potential adaptive variation in maturation schedules among walleye stocks and over time. For instance, Oneida Lake walleyes (which had relatively slow growth and low mortality rates) matured at a smaller size for a given age (smaller midpoints of PMRNs) than the other stocks. Temporally, walleyes in the western basin of Lake Erie matured at a larger size in recent years, as evidenced by increasing midpoints of PMRNs (1978ñ 1989 versus 1990ñ 2006 for Ohio Department of Natural Resources data and 1990ñ 1996 versus 1997ñ 2006 for Ontario Ministry of Natural Resources data). Our study highlights the necessity of monitoring maturation schedules via multiple maturation indices and the need to account for samplingñ induced biases when comparing maturation schedules.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141201/1/nafm1540.pd

    Nanomaterial interactions with biomembranes: Bridging the gap between soft matter models and biological context

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    Synthetic polymers, nanoparticles, and carbon-based materials have great potential in applications including drug delivery, gene transfection, in vitro and in vivo imaging, and the alteration of biological function. Nature and humans use different design strategies to create nanomaterials: biological objects have emerged from billions of years of evolution and from adaptation to their environment resulting in high levels of structural complexity; in contrast, synthetic nanomaterials result from minimalistic but controlled design options limited by the authors' current understanding of the biological world. This conceptual mismatch makes it challenging to create synthetic nanomaterials that possess desired functions in biological media. In many biologically relevant applications, nanomaterials must enter the cell interior to perform their functions. An essential transport barrier is the cell-protecting plasma membrane and hence the understanding of its interaction with nanomaterials is a fundamental task in biotechnology. The authors present open questions in the field of nanomaterial interactions with biological membranes, including: how physical mechanisms and molecular forces acting at the nanoscale restrict or inspire design options; which levels of complexity to include next in computational and experimental models to describe how nanomaterials cross barriers via passive or active processes; and how the biological media and protein corona interfere with nanomaterial functionality. In this Perspective, the authors address these questions with the aim of offering guidelines for the development of next-generation nanomaterials that function in biological media

    Modelling India’s coal production with a negatively skewed curve-fitting model

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    India’s coal demand is forecast to increase at a rapid pace in the future due to the country’s economic and population growth. Analyzing the scope for future production of India’s domestic coal resources, therefore, plays a vital role in the country’s development of sound energy policies. This paper presents a quantitative scenario analysis of India’s potential future coal production by using a negatively skewed curve-fitting model and a range of estimates of the country’s ultimately recoverable resources (URR) of coal. The results show that the resource base is sufficient for India’s coal production to keep increasing over the next few decades, to reach between 2400 and 3200 Mt/y at 2050, depending on the assumed value of URR. A further analysis shows that the high end of this range, which corresponds to our ‘GSI’ scenario, can be considered as the probable upper-bound to India’s domestic coal production. Comparison of production based on the ‘GSI’ scenario with India’s predicted demand shows that the domestic production of coal will be insufficient to meet the country’s rising coal demand, with the gap between demand and production increasing from its current value of about 268 Mt/y to reach 300 Mt/y in 2035, and 700 Mt/y by 2050. This increasing gap will be challenging for the energy security of India

    Tune in to your emotions: a robust personalized affective music player

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    The emotional power of music is exploited in a personalized affective music player (AMP) that selects music for mood enhancement. A biosignal approach is used to measure listeners’ personal emotional reactions to their own music as input for affective user models. Regression and kernel density estimation are applied to model the physiological changes the music elicits. Using these models, personalized music selections based on an affective goal state can be made. The AMP was validated in real-world trials over the course of several weeks. Results show that our models can cope with noisy situations and handle large inter-individual differences in the music domain. The AMP augments music listening where its techniques enable automated affect guidance. Our approach provides valuable insights for affective computing and user modeling, for which the AMP is a suitable carrier application
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