Merge Event Research Articles

Community Evolution Analysis Driven by Tag Events: The Special Perspective of New Tags

The type, quantity, and scale of social-tagging systems have grown constantly in recent years as users’ interest increases. Tags have important reference value in the study of networked communities since they typically represent user preference. This paper aims to examine how a tagging community evolves and to check the impact of new tags on evolution. Therefore, we proposed an improved evolution model for tag communities where tags constantly accumulate without withdrawal. Based on the model, we conducted an evolution analysis on three different tag communities with the datasets generated from the Delicious bookmarking system, CiteULike, and Douban. The results from Delicious emphasized that new individuals have an enormous influence on the community evolution, for they dominate the Form event, lead the early Split event, indirectly have a hand in the Merge event, and affect existing tags’ transfer when they flood into the system. Moreover, new tags are proved to be more influential in tagging relation data of CiteULike and Douban, where new tags dominate the Split event. The in-depth and detailed depiction of community evolution helps us understand the evolution process of tag communities and the crucial role of new tags.

Fascicles split or merge every ∼560 microns within the human cervical vagus nerve

Objective. Vagus nerve stimulation (VNS) is Food and Drug Administration-approved for epilepsy, depression, and obesity, and stroke rehabilitation; however, the morphological anatomy of the vagus nerve targeted by stimulatation is poorly understood. Here, we used microCT to quantify the fascicular structure and neuroanatomy of human cervical vagus nerves (cVNs). Approach. We collected eight mid-cVN specimens from five fixed cadavers (three left nerves, five right nerves). Analysis focused on the ‘surgical window’: 5 cm of length, centered around the VNS implant location. Tissue was stained with osmium tetroxide, embedded in paraffin, and imaged on a microCT scanner. We visualized and quantified the merging and splitting of fascicles, and report a morphometric analysis of fascicles: count, diameter, and area. Main results. In our sample of human cVNs, a fascicle split or merge event was observed every ∼560 µm (17.8 ± 6.1 events cm−1). Mean morphological outcomes included: fascicle count (6.6 ± 2.8 fascicles; range 1–15), fascicle diameter (514 ± 142 µm; range 147–1360 µm), and total cross-sectional fascicular area (1.32 ± 0.41 mm2; range 0.58–2.27 mm). Significance. The high degree of fascicular splitting and merging, along with wide range in key fascicular morphological parameters across humans may help to explain the clinical heterogeneity in patient responses to VNS. These data will enable modeling and experimental efforts to determine the clinical effect size of such variation. These data will also enable efforts to design improved VNS electrodes.

ON THE LIMITATIONS OF THE EARNED VALUE MANAGEMENT TECHNIQUE TO ANTICIPATE PROJECT DELAYS

A significant proportion of projects across the construction industry fail to meet their planned completion dates, being this a recurrent topic in the project management literature. Multiples causes of project delays have been proposed, however, hardly any attention has been paid to the fact that the most celebrated project monitoring and control technique – the Earned Value Management (EVM) – may not be as fit for purpose as it seems. It is proposed that because EVM ignores activity duration variability it always results in optimistic completion dates which may be very difficult to meet in the real projects. This research offers a fresh and long overdue critique of EVM in its most common implementation (assuming deterministic activity durations and costs), while highlighting its shortcomings. Particularly, Monte Carlo simulations are implemented to exemplify how the merge event bias phenomenon is inadvertently impacting the schedule in both time and cost dimensions. A fictitious case study is used to demonstrate the connection between these shortcomings and what is then conceived as a delay in project completion.

Modelling the boundaries of project fast-tracking

Abstract Fast-tracking a project involves carrying out sequential activities in parallel, partially overriding their original order of precedence, to reduce the overall project duration. The current predominant mathematical models of fast-tracking are based on the concepts of activity sensitivity, evolution, dependency and, sometimes, information exchange uncertainty, and aim to determine optimum activity overlaps. However, these models require some subjective inputs from the scheduler and most of them neglect the merge event bias. In this paper, a stochastic model for schedule fast-tracking is proposed. Relevant findings highlight the existence of a pseudo-physical barrier that suggests that the possibility of shortening a schedule by more than a quarter of its original duration is highly unlikely. The explicit non-linear relationship between cost and overlap has also been quantified for the first time. Finally, manual calculations using the new model are compared with results from a Genetic Algorithm through a case study.

Modeling Mandatory Lane Changing Using Bayes Classifier and Decision Trees

A lane changing assistance system that advises drivers of safe gaps for making mandatory lane changes at lane drops is developed. Bayes classifier and decision-tree methods were applied to model lane changes. Detailed vehicle trajectory data from the Next Generation Simulation (NGSIM) data set were used for model development (U.S. Highway 101) and testing (Interstate 80). The model predicts driver decisions on whether to merge or not as a function of certain input variables. The best results were obtained when both Bayes and decision-tree classifiers were combined into a single classifier using a majority voting principle. The prediction accuracy was 94.3% for nonmerge events and 79.3% for merge events. In a lane change assistance system, the accuracy of nonmerge events is more critical than merge events. Misclassifying a nonmerge event as a merge event could result in a traffic crash, whereas misclassifying a merge event as a nonmerge event would only result in a lost opportunity to merge. Sensitivity analysis performed by assigning higher misclassification cost for nonmerge events resulted in even higher accuracy for nonmerge events but lower accuracy for merge events.

Morphology and evolution of umbral dots and their substructures

Substructures - dark lanes and tails - of umbral dots (UDs) were predicted by numerical simulations of magnetoconvection. We analyse a 6 h 23 min time series of broadband images of a large umbra in the active region NOAA 10634, acquired with the 1-m Swedish Solar Telescope, in the wavelength band around 602 nm. A 43 min part of this series was reconstructed with the MFBD method, reaching a spatial resolution of 0.14". We measure brightness, size, lifetime, and horizontal velocities of various umbral structures. Most (90 %) of UDs and bright point-like features in faint LBs split and merge, and their median lifetimes are 3.5 or 5.7 min, depending on whether the split or merge event is considered as the end of their life. Both UDs and features in faint LBs that do not split or merge are clearly smaller (0.15") than the average size (0.17") of all features. Horizontal motions of umbral bright small-scale features are directed either into the umbra or along faint LBs with mean horizontal velocities of 0.34 km/s. Features faster than 0.4 km/s appear mostly at the periphery of the umbra. The intensity of dark lanes, measured in four bright central UDs (CUDs), is by a factor 0.8 lower than the peak intensity of CUDs. The width of dark lanes is probably less than the resolution limit 0.14". The characteristic time of substructure changes of UDs is ~4 min. We observe narrow (0.14") bright and dark filaments connected with PUDs. Usually one dark and two bright filaments form a 0.4" wide tail attached to one PUD, resembling a short dark-cored penumbral filament. Our results indicate the similarity between PUDs and PGs located at the tips of bright penumbral filaments. The features seen in numerical MHD simulations are consistent with our observations of dark lanes in CUDs and tails attached to PUDs.

Time Planning for Construction Projects: Conceptual Developments

Time planning passes through four conceptual development stages. These are Bar Chart, Network Diagram, Resources Constrained Project Scheduling (RCPS) and Time Planning under Uncertainty. Recent developments acknowledged uncertainties in time planning and categorized them in four major factors. They are Uncertainties of Detailing of Activities, Estimating Activity Durations, Resources Dependencies, and Task Dependencies specifically Merge Event Biases (MEB). As a result, CPM, PERT, Mathematical and Heuristic models, Monte Carlo Simulation, Successive Principles and Theory of Constraints (TOC) are developed for Time planning approaches. This paper tries to review these conceptual developments for use in Practical applications and for R&D. Keywords : Time planning, CPM, PERT, MCS, Successive Principle, Theory of Constraints African Research Review Vol. 2 (4) 2008: pp. 88-112

Enhancing Project Evaluation and Review Technique Simulation through Artificial Neural Network-based Input Modeling

Although a stochastic simulation study can eliminate the merge event bias in the project evaluation and review technique (PERT), the errors due to calculating the statistical descriptors of beta distributions with the three-point time estimates of PERT may still make the simulation results suspect. In order to enhance PERT simulation in terms of input modeling, this paper presents an artificial neural network (ANN)-based approach to estimate the true properties of the beta distributions from statistical sampling of actual data combined with subjective information. The minimum and maximum values along with the lower and upper quartiles are four time estimates used to uniquely define a beta distribution. The effects of shape parameters of beta distributions are closely examined, and the working range of shape parameters is defined. To construct an ANN model, data are prepared using random sampling techniques and Excel functions. Through exploring the training data provided, the ANN model has found the patterns between the inputs and the outputs, namely the interactions and nonlinear relationships among the lower and upper quartiles and the shape parameters of the beta distributions. The ANN model was tested, validated, and compared with other packages for fitting beta distributions such as BetaFit, VIBES, and BestFit. The developed ANN-based input modeling method attempts to embed artificial intelligence into simulation and finds a new way to fit statistical distributions for activity duration in construction simulation, as demonstrated in a sample application.

Calculation of safe float use in risk-analysis-oriented network scheduling

One of the criticisms of the pert/cpm technique is that it ignores the uncertainty influence of noncritical activities on project-duration estimation. As a result of this problem, the pert/cpm technique gives an optimistic estimation of project duration and float use. The paper introduces a new concept of time-disturbance analysis for a project network. Time-disturbance analysis is a process of simulating the change of the expected time of a given merge event or total project duration with the changes in float use of noncritical activities. The computations of the late start and finish times of the noncritical activities on the basis of the rational use of the float are introduced by using the back-forward uncertainty estimation ( bfue) procedure, an analytical risk-analysis model. Time-disturbance analysis can assist in project scheduling to reduce project risks rationally.