Revisitation Patterns Research Articles

Hogs sleep like logs: Wild boars reduce the risk of anthropic disturbance by adjusting where they rest.

Many animals living in anthropized landscapes try to avoid encountering people by being active at night. By doing so, however, they risk being disturbed while at rest during the day. To mitigate this risk, diurnally resting species may be highly selective about where they rest. Here, we used GPS and activity sensors to study how wild boars (Sus scrofa) might adjust their resting site selection and revisitation patterns to the risk of disturbance by people. We evaluated the probability of daytime relocation to assess the efficacy of wild boars' resting strategy in reducing the risk of human encounter while at rest. We attempted to identify the cause of some relocations using audio recordings. Generally, we found that wild boars did not specifically avoid resting near villages or roads, that is, where the risk of encountering people is higher, if they could find sites with suitable vegetation cover. The risk of disturbance by people was low, even near villages. Resting sites located close to villages were visited more repeatedly than those located further away, suggesting that focusing on a few familiar and quiet resting sites was a successful strategy for resting undisturbed in an anthropized landscape.

Detecting Item Preknowledge Using Revisits With Speed and Accuracy

Examinees with item preknowledge tend to obtain inflated test scores that undermine test score validity. With the availability of process data collected in computer-based assessments, the research on detecting item preknowledge has progressed on using both item scores and response times. Item revisit patterns of examinees can also be utilized as an additional source of information. This study proposes a new statistic for detecting item preknowledge when compromised items are known by utilizing the hierarchical speed–accuracy revisits model. By simultaneously evaluating abnormal changes in the latent abilities, speeds, and revisit propensities of examinees, the procedure was found to provide greater statistical power and stronger substantive evidence that an examinee had indeed benefited from item preknowledge.

A Comparison of Emergency Department Revisit Rates of Pediatric Patients between Pre-COVID-19 and COVID-19 Periods.

Unscheduled revisits to emergency departments (EDs) are important because they indicate the quality of emergency care. However, the characteristics of pediatric patients visiting EDs changed during the coronavirus disease (COVID-19) pandemic, and these changes may have affected their revisit patterns. Therefore, we aimed to compare the ED revisit patterns of pediatric patients between the pre-COVID-19 and COVID-19 periods. This retrospective multicenter study included patients aged below 18 years who visited the ED in the pre-COVID-19 and COVID-19 periods. ED revisit rates were analyzed using five age groups and three visit-revisit intervals. In the pre-COVID-19 period, the revisit rates decreased with increasing age. In the COVID-19 period, the revisit rates were the lowest for the group aged 4–6 years, and the rates increased for those aged ≥7 years. In conclusion, there were changes in the patterns of revisit rates of pediatric patients according to age between the pre-COVID-19 and COVID-19 periods. Therefore, it is necessary to identify the reasons for revisits according to age and establish strategies to reduce the revisit rates of pediatric patients.

Ecological correlates of space use patterns in wild western lowland gorillas.

The distribution of resources is a crucial determinant of animals' space use (e.g., daily travel distance, monthly home range size, and revisitation patterns). We examined how variation in ecological parameters affected variability in space use patterns of western lowland gorillas, Gorilla gorilla gorilla. They are an interesting species for investigating this topic because key components of their diet are nonfruit items (herbaceous vegetation and tree leaves) that occur at low density and are sparsely distributed, and fruits, which show high spatiotemporal variation in availability. We estimated how availability of nonfruit foods and fruit, frugivory (proportion of feeding time consuming fruit), and swamps in areas used by the gorillas influenced daily travel distance, monthly home range size, and revisit frequency to grid cells in the home range of one habituated gorilla group in Loango National Park, Gabon. Using location data from 2015 to 2018, we found that the gorillas decreased their daily travel distance as both the density of nonfruit foods and the proportion of swamps in areas used increased. Daily travel distances were shorter when both frugivory and availability of fruit were higher, yet, daily travel distances were longer when availability of fruit was low but frugivory was still high. Furthermore, monthly home range size increased as frugivory increased and monthly revisit frequencies to an area increased as fruit availability of an area increased. In conclusion, the availability of both nonfruit and fruit influenced the gorillas' space use patterns. Gorillas decreased foraging effort when food availability was high but were willing to incur increasing foraging costs to feed on fruit when availability was low. This study highlights how animals have to adjust their space use with changing resource availability and it emphasizes the value of examining multiple parameters of space use.

State-space analysis of power to detect regional brook trout population trends over time

Threats to aquatic biodiversity are expressed at broad spatial scales, but identifying regional trends in abundance is challenging owing to variable sampling designs and temporal and spatial variation in abundance. We compiled a regional data set of brook trout (Salvelinus fontinalis) counts across their southern range representing 326 sites from eight states between 1982 and 2014 and conducted a statistical power analysis using Bayesian state-space models to evaluate the ability to detect temporal trends by characterizing posterior distributions with three approaches. A combination of monitoring periods, number of sites and electrofishing passes, decline magnitude, and different revisit patterns were tested. Power increased with monitoring periods and decline magnitude. Trends in adults were better detected than young-of-the-year fish, which showed greater interannual variation in abundance. The addition of weather covariates to account for the temporal variation increased power only slightly. Single- and three-pass electrofishing methods were similar in power. Finally, power was higher for sampling designs with more frequent revisits over the duration of the monitoring program. Our results provide guidance for broad-scale monitoring designs for temporal trend detection.

Revisitation in Urban Space vs. Online

We present the first large-scale analysis of POI revisitation patterns, which aims to model the periodic behavior in human mobility. We apply the revisitation analysis technique, which has previously been used to understand website revisitation, and smartphone app revisitations. We analyze a 1.5-year-long Foursquare check-in dataset with 266,909 users in 415 cities around the globe, as well as a Chinese social networking dataset on continuous localization of 15,000 users in Beijing. Our analysis identifies four major POI revisitation patterns and four user revisitation patterns of distinct characteristics, and demonstrates the role of POI functions and geographic constraints in shaping these patterns. We compare our results to previous analysis on website and app revisitation, and highlight the similarities and differences between physical and cyber revisitation activities. These point to fundamental characteristics of human behavior.

Applying sequential pattern mining to investigate cerebrovascular health outpatients' re-visit patterns.

Background and ObjectiveIncreases in outpatients seeking medical check-ups are expanding the number of health examination data records, which can be utilized for medical strategic planning and other purposes. However, because hospital visits by outpatients seeking medical check-ups are unpredictable, those patients often cannot receive optimal service due to limited facilities of hospitals. To resolve this problem, this study attempted to predict re-visit patterns of outpatients.MethodTwo-phase sequential pattern mining (SPM) and an association mining method were chosen to predict patient returns using sequential data. The data were grouped according to the outpatients’ personal information and evaluated by a discriminant analysis to check the significance of the grouping. Furthermore, SPM was employed to generate frequency patterns from each group and extract a general association pattern of return.ResultsResults of sequence patterns and association mining in this study provided valuable insights in terms of outpatients’ re-visit behaviors for regular medical check-ups. Cosine and Jaccard are two symmetric measures which were used in this study to indicate the degree of association between two variables. For instance, Jaccard values of variable abnormal blood pressure associated with an abnormal body-mass index (BMI) and/or abnormal blood sugar were respectively 47.5% and 100%, for the two-visit and three-visit behavior patterns. These results indicated that the corresponding pair of variables was more reliable when covering the three-visit behavior pattern than the two-visit behavior. Thus, appropriate preventive measures or suggestions for other medical treatments can be prepared for outpatients that have this pattern on their third visit. The higher degree of association implies that the corresponding behavior pattern might influence outpatients’ intentions to regularly seek medical check-ups concerning the risk of stroke. Furthermore, a radiology diagnosis (i.e., magnetic resonance imaging or neck vascular ultrasound) plays an important role in the association with a re-visit behavior pattern with respective 50% and 70% Cosine and Jaccard values in general behavior {f11}∧{f01}. These findings can serve as valuable information to increase the quality of medical services and marketing, by suggesting appropriate treatment for the subsequent visit after learning the behavior patterns.ConclusionsThe proposed method can provide valuable information related to outpatients’ re-visit behavior patterns based on hidden knowledge generated from sequential patterns and association mining results. For marketing purposes, medical practitioners can take behavior patterns studied in this paper into account to raise patients’ awareness of several possible medical conditions that might arise on subsequent visits and encourage them to take preventive measures or suggest other medical treatments.

MODELLING FREE-RANGE CATTLE MOVEMENTS IN FORESTS USING MULTISTATE RANDOM WALKS

In this study multi-state random walk models were tested as general approach to analyse movement states in animal relocation data. For this purpose, GPS collars were fit to free-range cattle inhabiting Andean forests in Patagonia, Argentina. The results indicate that animal trajectories have re-visitation patterns in restricted areas of few kilometres and that a large part of behaviors occur at a time scale lower than six hours. Simple multi-state random walk models proved to be practical in modelling characteristics such as step and turning angles distribution in addition to emergent properties of animal trajectories such as temporal autocorrelation. Re-visitation patterns and the emergence of home-range, among other memory processes could be marked as possible limitations of these models. This work is the first description of free-range cattle movement inhabiting the andean-Patagonian forests in semi-feral conditions.

Analysis of revisitations in online games

This paper analyzes revisitations in online games focusing on two types of revisitations: game revisitations and area revisitations. A player revisits a game and areas therein with purposes. For game revisitations, we conduct a large-scale analysis using Shen Zhou Online access log collected for nearly 6 years consisting of 50,000 characters and have succeeded in using in the information on game revisitations, together with the login time and login frequency information, for predicting the players who will be absent from the game. For area revisitations, we conduct yet another large-scale analysis using World of Warcraft access log collected for 2 years consisting of more than 60,000 characters and have discovered four main groups of area revisitation patterns. We also discuss in the paper how our findings can be utilized to support both game developers and players.

Evaluating the power of monitoring plot designs for detecting long‐term trends in the numbers of common guillemots

Summary In recent years concerns have been raised regarding the status of the common guillemot Uria aalge in the UK. Numbers have declined in several regions, highlighting the need for continued monitoring of this internationally important population. However, the extent to which the current monitoring scheme is capable of detecting declines and options for improving efficiency has received little attention. We investigated the power of different monitoring design options for detecting long‐term trends in abundance at a colony of guillemots. The ability to detect trends in abundance was reduced by the large temporal and spatial variability in colony attendance. Taking a linear mixed model approach, we obtained details on the sources and sizes of the variance components using count data collected from monitoring plots on the Isle of May, Scotland, and assessed how best to allocate sampling effort in the light of the count variability structure. Our results indicated that trend detection will be improved by counting birds in more plots rather than by increasing the number of counts at existing plots. The revisit pattern of counts at the monitoring plots during the seasonal counting period had little effect on trend detection power. However, given the practical issues associated with counting guillemots, alternative revisit patterns to the current approach are preferred. For a fixed number of visits per plot, power is strongly influenced by the choice of revisit design if the day‐to‐day variation in colony attendance is increased. Synthesis and applications. Aspects of the UK seabird monitoring scheme can be improved. Changes to the allocation of sampling effort and the plot‐revisit pattern will improve both the statistical power to detect long‐term trends and the efficiency of conducting the survey. We stress the importance of considering the structure and magnitude of the count variation in a power analysis because judicious design decisions depend on the relative magnitude of these variance components.

Temporal disaggregation of satellite-derived monthly precipitation estimates and the resulting propagation of error in partitioning of water at the land surface

Abstract. Global estimates of precipitation can now be made using data from a combination of geosynchronous and low earth-orbit satellites. However, revisit patterns of polar-orbiting satellites and the need to sample mixed-clouds scenes from geosynchronous satellites leads to the coarsening of the temporal resolution to the monthly scale. There are prohibitive limitations to the applicability of monthly-scale aggregated precipitation estimates in many hydrological applications. The nonlinear and threshold dependencies of surface hydrological processes on precipitation may cause the hydrological response of the surface to vary considerably based on the intermittent temporal structure of the forcing. Therefore, to make the monthly satellite data useful for hydrological applications (i.e. water balance studies, rainfall-runoff modelling, etc.), it is necessary to disaggregate the monthly precipitation estimates into shorter time intervals so that they may be used in surface hydrology models. In this study, two simple statistical disaggregation schemes are developed for use with monthly precipitation estimates provided by satellites. The two techniques are shown to perform relatively well in introducing a reasonable temporal structure into the disaggregated time series. An ensemble of disaggregated realisations was routed through two land surface models of varying complexity so that the error propagation that takes place over the course of the month could be characterised. Results suggest that one of the proposed disaggregation schemes can be used in hydrological applications without introducing significant error. Keywords: precipitation, temporal disaggregation, hydrological modelling, error propagation

PowerBookmarks

Users of the Web are overloaded with information. This medium is “polluted” with redundant, erroneous and low quality information. A WWW survey of 11,700 users conducted from April 10 to May 10, 1996[1] indicates that 30.31% of the users report “finding known info” is their problem and 27.80% of the users report organizing collected information as their problem. An empirical study[2] on users’ revisitation patterns to WWW pages found that 58% of an individual’s pages are revisits. With these study results, we believe the Web users would like to build and organize a larger collection of bookmarks for future references than they can reasonably maintain now.

How people revisit web pages: empirical findings and implications for the design of history systems

We report on users' revisitation patterns to World Wide Web (web) pages, and use the results to lay an empirical foundation for the design of history mechanisms in web browsers. Through history, a user can return quickly to a previously visited page, possibly reducing the cognitive and physical overhead required to navigate to it from scratch. We analysed 6 weeks of detailed usage data collected from 23 users of a well-known web browser. We found that 58% of an individual's pages are revisits, and that users continually add new web pages into their repertoire of visited pages. People tend to revisit pages just visited, access only a few pages frequently, browse in very small clusters of related pages and generate only short sequences of repeated URL paths. We compared different history mechanisms, and found that the stack-based prediction method prevalent in commercial browsers is inferior to the simpler approach of showing the last few recently visited URLs with duplicates removed. Other predictive approaches fare even better. Based on empirical evidence, eight design guidelines for web browser history mechanisms were then formulated. When used to evaluate the existing hypertext-based history mechanisms, they explain why some aspects of today's browsers seem to work well, and other's poorly. The guidelines also indicate how history mechanisms in the web can be made even more effective.f1f1This article is a major expansion of a conference paper (Tauscher & Greenberg, 1997). This research reported in this article was performed as part of an M.Sc. project (Tauscher, 1996).