Transforming mobile personal life log into autobiographical multimedia eChronicles

Mobile devices are becoming indispensable personal assistants in people's daily life as these devices support work, study, play and socializing activities. The multi-modal sensors and rich features of smartphones can capture abundant information about users' life experience, such as taking photos or videos on what they see and hear, and organizing their tasks and activities using calendar, to-do lists, and notes. Such vast information can become useful to help users recalling episodic memories and reminisce about meaningful experiences. In this paper, we propose to apply autobiographical memory framework to provide an effective mechanism to structure mobile life-log data. The proposed model is an attempt towards a more complete personal life-log indexing model, which will support long term capture, organization, and retrieval. To demonstrate the benefits of the proposed model, we propose some design solutions for enabling users-driven capture, annotation, and retrieval of autobiographical multimedia chronicles tools.

Log delta analysis: Interpretable differencing of Business process event logs

This paper addresses the problem of identifying and explaining behavioral differences between two business process event logs. The paper presents a method that, given two event logs, returns a set of statements in natural language capturing behavior that is present or frequent in one log, while absent or infrequent in the other. This log delta analysis method allows users to diagnose differences between normal and deviant executions of a process or between two versions or variants of a process. The method relies on a novel approach to losslessly encode an event log as an event structure, combined with a frequency-enhanced technique for differencing pairs of event structures. A validation of the proposed method shows that it accurately diagnoses typical change patterns and can explain differences between normal and deviant cases in a real-life log, more compactly and precisely than previously proposed methods.

Maximum likelihood analysis of multi-stress accelerated life test data of series systems with competing log-normal causes of failure

This article presents frequentist inference of accelerated life test data of series systems with independent log-normal component lifetimes. The means of the component log-lifetimes are assumed to depend on the stress variables through a linear stress translation function that can accommodate the standard stress translation functions in the literature. An expectation-maximization algorithm is developed to obtain the maximum likelihood estimates of model parameters. The maximum likelihood estimates are then further refined by bootstrap, which is also used to infer about the component and system reliability metrics at usage stresses. The developed methodology is illustrated by analyzing a real as well as a simulated dataset. A simulation study is also carried out to judge the effectiveness of the bootstrap. It is found that in this model, application of bootstrap results in significant improvement over the simple maximum likelihood estimates.

A day in the life of PubMed: analysis of a typical day's query log.

OBJECTIVE: To characterize PubMed usage over a typical day and compare it to previous studies of user behavior on Web search engines. DESIGN: We performed a lexical and semantic analysis of 2,689,166 queries issued on PubMed over 24 consecutive hours on a typical day. MEASUREMENTS: We measured the number of queries, number of distinct users, queries per user, terms per query, common terms, Boolean operator use, common phrases, result set size, MeSH categories, used semantic measurements to group queries into sessions, and studied the addition and removal of terms from consecutive queries to gauge search strategies. RESULTS: The size of the result sets from a sample of queries showed a bimodal distribution, with peaks at approximately 3 and 100 results, suggesting that a large group of queries was tightly focused and another was broad. Like Web search engine sessions, most PubMed sessions consisted of a single query. However, PubMed queries contained more terms. CONCLUSION: PubMed's usage profile should be considered when educating users, building user interfaces, and developing future biomedical information retrieval systems.

The old log school house : furnitured with incidents of school life, notes of travel, poetry, hints to teachers and pupils, and miscellaneous sketches /

Mode of access: Internet.

The log of an ancient mariner : being the life and adventures of Captain Edgar Wakeman /

Mode of access: Internet.

The role of information avoidance in everyday-life information behaviors

This paper presents the results from a study of information behaviors in the context of people's everyday lives as part of a larger study of information behaviors (IB). 34 participants from across 6 countries maintained a daily information journal or diary – mainly through a secure web log – for two weeks, to an aggregate of 468 participant days over five months. The text-rich diary data was analyzed using Grounded Theory analysis. The findings indicate that information avoidance is a common phenomenon in everyday life and consisted of both passive avoidance and active avoidance. This has implications for several aspects of peoples' lives including health, finance, and personal relationships.

Bayesian Accelerated Life Testing under Competing Weibull Causes of Failure

Consider a J-component series system which is put on Accelerated Life Test (ALT) involving K stress variables. First, a general formulation of ALT is provided for log-location-scale family of distributions. A general stress translation function of location parameter of the component log-lifetime distribution is proposed which can accommodate standard ones like Arrhenius, power-rule, log-linear model, etc., as special cases. Later, the component lives are assumed to be independent Weibull random variables with a common shape parameter. A full Bayesian methodology is then developed by letting only the scale parameters of the Weibull component lives depend on the stress variables through the general stress translation function. Priors on all the parameters, namely the stress coefficients and the Weibull shape parameter, are assumed to be log-concave and independent of each other. This assumption is to facilitate Gibbs sampling from the joint posterior. The samples thus generated from the joint posterior is then used to obtain the Bayesian point and interval estimates of the system reliability at usage condition.

Bayesian Accelerated Life Testing under Competing Weibull Causes of Failure

Consider a J-component series system which is put on Accelerated Life Test (ALT) involving K stress variables. First, a general formulation of ALT is provided for log-location-scale family of distributions. A general stress translation function of location parameter of the component log-lifetime distribution is proposed which can accommodate standard ones like Arrhenius, power-rule, log-linear model, etc., as special cases. Later, the component lives are assumed to be independent Weibull random variables with a common shape parameter. A full Bayesian methodology is then developed by letting only the scale parameters of the Weibull component lives depend on the stress variables through the general stress translation function. Priors on all the parameters, namely the stress coefficients and the Weibull shape parameter, are assumed to be log-concave and independent of each other. This assumption is to facilitate Gibbs sampling from the joint posterior. The samples thus generated from the joint posterior is then used to obtain the Bayesian point and interval estimates of the system reliability at usage condition.

Use of oxygen sensors for the non destructive measurement of oxygen in packaged food and beverage products and its impact on product quality and shelf life

The principal objective of this thesis was to investigate the ability of reversible optical O2 sensors to be incorporated into food/beverage packaging systems to continuously monitor O2 levels in a non-destructive manner immediately postpackaging and over time. Residual levels of O2 present in packs can negatively affect product quality and subsequently, product shelf-life, especially for O2-sensitive foods/beverages. Therefore, the ability of O2 sensors to continuously monitor O2 levels present within food/beverage packages was considered commercially relevant in terms of identifying the consequences of residual O2 on product safety and quality over time. Research commenced with the development of a novel range of O2 sensors based on phosphorescent platinum and palladium octaethylporphyrin-ketones (OEPk) in nano-porous high density polyethylene (HDPE), polypropylene (PP) polytetrafluoroethylene (PTFE) polymer supports. Sensors were calibrated over a temperature range of -10°C to +40°C and deemed suitable for food and beverage packaging applications. This sensor technology was used and demonstrated itself effective in determining failures in packaging containment. This was clearly demonstrated in the packaging of cheese string products. The sensor technology was also assessed across a wide range of packaged products; beer, ready-to-eat salad products, bread and convenience-style, muscle-based processed food products. The O2 sensor technology performed extremely well within all packaging systems. The sensor technology adequately detected O2 levels in; beer bottles prior to and following pasteurisation, modified atmosphere (MA) packs of ready-to-eat salad packs as respiration progressed during product storage and MA packs of bread and convenience-style muscle-based products as mycological growth occurred in food packs over time in the presence and absence of ethanol emitters. The use of the technology, in conjunction with standard food quality assessment techniques, showed remarkable usefulness in determining the impact of actual levels of O2 on specific quality attributes. The O2 sensing probe was modified, miniaturised and automated to screen for the determination of total aerobic viable counts (TVC) in several fish species samples. The test showed good correlation with conventional TVC test (ISO:4833:2003), analytical performance and ruggedness with respect to variation of key assay parameters (probe concentration and pipetting volume). Overall, the respirometric fish TVC test was simple to use, possessed a dynamic microbial range (104-107 cfu/g sample), had an accuracy of +/- one log(cfu/g sample) and was rapid. Its ability to assess highly perishable products such as fish for total microbial growth in <12 hr demonstrates commercial potential.

Effects of priming duration on retention over the first 1 1/2 years of life.

Exposing individuals to an isolated component (a prime) of a prior event alleviates its forgetting. Two experiments with 120 human infants between 3 and 18 months of age determined the minimum duration of a prime that can reactivate a forgotten memory and how long the reactivated memory persists. Infants learned an operant task, forgot it, were exposed to the prime, and later were tested for renewed retention. In Experiment 1, the minimum duration of an effective prime decreased logarithmically with age, but was always longer than the duration of a mere glance. In Experiment 2, the reactivated memory was forgotten twice as fast after a minimum-duration prime as after a full-length one, irrespective of priming delay and infant age. These data reveal that the minimum effective prime duration psychophysically equates the accessibility of forgotten memories. We conclude that priming is perceptually based with effects that are organized on a ratio (log) scale.

How optimal life history changes with the community size-spectrum

This paper derives optimal life histories for fishes or other animals in relation to the size spectrum of the ecological community in which they are both predators and prey. Assuming log-linear size-spectra and well known scaling laws for feeding and mortality, we first construct the energetics of the individual. From these we find, using dynamic programming, the optimal allocation of energy between growth and reproduction as well as the trade-off between offspring size and numbers. Optimal strategies were found to be strongly dependent on size spectrum slope. For steep size spectra (numbers declining rapidly with size), determinate growth was optimal and allocation to somatic growth increased rapidly with increasing slope. However, restricting reproduction to a fixed mating season changed optimal allocations to give indeterminate growth approximating a von Bertalanffy trajectory. The optimal offspring size was as small as possible given other restrictions such as newborn starvation mortality. For shallow size spectra, finite optimal maturity size required a decline in fitness for large size or age. All the results are compared with observed size spectra of fish communities to show their consistency and relevance.

Coherent forecasting of multiple-decrement life tables: a test using Japanese cause of death data

Planners in public and private institutions would like coherent forecasts of the components of age-specic mortality, such as causes of death. This has been di cult to achieve because the relative values of the forecast components often fail to behave in a way that is coherent with historical experience. In addition, when the group forecasts are combined the result is often incompatible with an all-groups forecast. It has been shown that cause-specic mortality forecasts are pessimistic when compared with all-cause forecasts (Wilmoth, 1995). This paper abandons the conventional approach of using log mortality rates and forecasts the density of deaths in the life table. Since these values obey a unit sum constraint for both conventional single-decrement life tables (only one absorbing state) and multiple-decrement tables (more than one absorbing state), they are intrinsically relative rather than absolute values across decrements as well as ages. Using the methods of Compositional Data Analysis pioneered by Aitchison (1986), death densities are transformed into the real space so that the full range of multivariate statistics can be applied, then back-transformed to positive values so that the unit sum constraint is honoured. The structure of the best-known, single-decrement mortality-rate forecasting model, devised by Lee and Carter (1992), is expressed in compositional form and the results from the two models are compared. The compositional model is extended to a multiple-decrement form and used to forecast mortality by cause of death for Japan

Microbiological Shelf Life of Pasteurized Milk in Bottle and Pouch

Shelf life of pasteurized milk in Brazil ranges from 3 to 8 d, mainly due to poor cold chain conditions that prevail throughout the country and subject the product to repeated and/or severe temperature abuse. This study evaluated the influence of storage temperature on the microbiological stability of homogenized whole pasteurized milk (75 degrees C/15 s) packaged in high-density polyethylene (HDPE) bottle and low-density polyethylene (LDPE) pouch, both monolayer materials pigmented with titanium dioxide (TiO(2)). The storage temperatures investigated were 2, 4, 9, 14, and 16 degrees C. Microbiological evaluation was based on mesophilic and psychrotrophic counts with 7 log CFU/mL and 6 log CFU/mL, respectively, set as upper limits of acceptability for maintaining the quality of milk. The microbiological stability for pasteurized milk packaged in HDPE bottle and stored at 2, 4, 9, 14, and 16 degrees C was estimated at 43, 36, 8, 5, and 3 d, respectively. For milk samples packaged in LDPE pouch, shelf life was estimated at 37, 35, 7, 3, and 2 d, respectively. The determination of Q(10) and z values demonstrated that storage temperature has a greater influence on microbiological shelf life of pasteurized milk packaged in LDPE pouch compared to HDPE bottle. Based on the results of this study, HDPE bottle was better for storing pasteurized milk as compared to LDPE pouch.

On estimation and influence diagnostics for log-Birnbaum-Saunders Student-t regression models: Full Bayesian analysis

The purpose of this paper is to develop a Bayesian approach for log-Birnbaum-Saunders Student-t regression models under right-censored survival data. Markov chain Monte Carlo (MCMC) methods are used to develop a Bayesian procedure for the considered model. In order to attenuate the influence of the outlying observations on the parameter estimates, we present in this paper Birnbaum-Saunders models in which a Student-t distribution is assumed to explain the cumulative damage. Also, some discussions on the model selection to compare the fitted models are given and case deletion influence diagnostics are developed for the joint posterior distribution based on the Kullback-Leibler divergence. The developed procedures are illustrated with a real data set. (C) 2010 Elsevier B.V. All rights reserved.