Resource-constrained project scheduling for timely project completion with stochastic activity durations.

We investigate resource-constrained project scheduling with stochastic activity durations. Various objective functions related to timely project completion are examined, as well as the correlation between these objectives. We develop a GRASP-heuristic to produce high-quality solutions, using so-called descriptive sampling. The algorithm outperforms other existing algorithms for expected-makespan minimization. The distribution of the possible makespan realizations for a given scheduling policy is studied, and problem difficulty is explored as a function of problem parameters.GRASP; Project scheduling; Uncertainty;

Meta-heuristics for stable scheduling on a single machine.

This paper presents a model for single-machine scheduling with stability objective and a common deadline. Job durations are uncertain, and our goal is to ensure that there is little deviation between planned and actual job starting times. We propose two meta-heuristics for solving an approximate formulation of the model that assumes that exactly one job is disrupted during schedule execution, and we also present a meta-heuristic for the global problem with independent job durationsMeta-heuristics; Robustness; Single-machine scheduling; Uncertainty;

Heuristic procedures for reactive project scheduling.

This paper describes new heuristic reactive project scheduling procedures that may be used to repair resource-constrained roject baseline schedules that suer from multiple activity duration disruptions during project execution.The objective is to minimize the deviations between the baseline schedule and the schedule that is actually realized.We discuss computational results obtained with priority-rule based schedule generation schemes, a sampling approach and a weighted-earliness tardiness heuristic on a set of randomly generated project instances.Project scheduling; Scheduling; Reactive scheduling; Research; Uncertainty; Stability;

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Four-Legs D-STATCOM for Current Balancing in Low-Voltage Distribution Grids

The fast deployment of distributed energy resources (DERs) is creating a series of challenges that should be addressed in the coming years. In particular, distribution grids are playing an increasingly important role in the electricity system. Moreover, the three-phase four-wire structure of this network contribute to the appearance of imbalances and a series of problems derived from them. In this context, distribution system operators (DSOs), as the main responsible for the distribution grid, must ensure the quality of supply to consumers. This paper takes advantage of a four-legs D-STATCOM to remove current imbalances in low-voltage power lines. A 35-kVA prototype has been developed and installed in an urban distribution grid. The effect of the D-STATCOM has been analyzed during its first month of operation, studying and measuring the advantages of providing DERs the ability to perform active balancing to the utility grid. The results show a reduction in current imbalances from 21 % to 0 % and neutral current from 10.3 A to 0.4 A. In addition, a 13 % decrease in cable losses has been estimated and a slight improvement in voltage unbalance factor can be noted

Meta-heuristics for stable scheduling on a single machine

This paper presents a model for single-machine scheduling with stability objective and a common deadline. Job durations are uncertain, and our goal is to ensure that there is little deviation between planned and actual job starting times. We propose two meta-heuristics for solving an approximate formulation of the model that assumes that exactly one job is disrupted during schedule execution, and we also present a meta-heuristic for the global problem with independent job durationsstatus: publishe

Perception and Action in Peripersonal Space: A Comparison between Video and Optical See-Through Augmented Reality Devices

In this paper, we analyze how we perceive the peripersonal space when involved in a reaching task in an Augmented Reality (AR) environment. In particular, we aim to quantify whether distortions in perception of the spatial layout of the scene occur, by taking into consideration two different AR wearable devices, in particular head-mounted displays (HMD). We performed two tests, and compared the results between the subjects who used an Optical See-Through (OST) HMD (Metavision Meta 2) and those who used a Video See-Through (VST) HMD (a smartphone in conjunction with a headset like the Google Cardboard). The data has been collected from a total of 45 volunteer participants. In the experiment, the subjects had to perform a precision reaching task by overlapping the hand on the perceived target position. Then, we observed how the presence or absence of an internal feedback influenced the homing performance. Our results revealed a better depth estimation, thus a more precise interaction, when using the OST device, which also revealed a lower impact on eye strain and fatigue

A Registration Framework for the Comparison of Video and Optical See-Through Devices in Interactive Augmented Reality

In this paper, we designed a registration framework that can be used to develop augmented reality environments, where all the real (including the users) and virtual elements are co-localized and registered in a common reference frame. The software is provided together with this paper, to contribute to the research community. The developed framework allows us to perform a quantitative assessment of interaction and egocentric perception in Augmented Reality (AR) environments. We assess perception and interaction in the peripersonal space through a 3D blind reaching task in a simple scenario and an interaction task in a kitchen scenario using both video (VST) and optical see-through (OST) head-worn technologies. Moreover, we carry out the same 3D blind reaching task in real condition (without head-mounted display and reaching real targets). This provides a baseline performance with which to compare the two augmented reality technologies. The blind reaching task results show an underestimation of distances with OST devices and smaller estimation errors in frontal spatial positions when the depth does not change. This happens with both OST and VST devices, compared with the real-world baseline. Such errors are compensated in the interaction kitchen scenario task. Thanks to the egocentric viewing geometry and the specific required task, which constrain the position perception on a table, both VST and OST have comparable and effective performance. Thus, our results show that such technologies have issues, though they can be effectively used in specific real tasks. This does not allow us to choose between VST and OST devices. Still, it provides a baseline and a registration framework for further studies and emphasizes the specificity of perception in interactive AR

Experimental Validation of Photogrammetry based 3D Reconstruction Software

3D reconstruction is of interest to several fields. However, obtaining the 3D model is usually a time-consuming task that involves manual measurements and reproduction of the object using CAD software, which is not always feasible (e.g. for organic shapes). The necessity of quickly obtaining a dimensionally accurate 3D model of an object has led to the development of several reconstruction techniques, either vision based (with photogrammetry), using laser scanners, or a combination of the two. The contribution of this study is in the analysis of the performances of currently available 3D reconstruction frameworks with the aim of providing a guideline to novice users who may be unfamiliar with 3D reconstruction technologies. We evaluate various software packages on a synthetic dataset representing objects of various shapes and sizes. For comparison, we consider various metrics such as mean errors in the reconstructed cloud point and meshes and reconstruction time. Our results indicate that Colmap produces the best reconstruction

A VR game-based system for multimodal emotion data collection

The rising popularity of learning techniques in data analysis has recently led to an increased need of large-scale datasets. In this study, we propose a system consisting of a VR game and a software platform designed to collect the player’s multimodal data, synchronized with the VR content, with the aim of creating a dataset for emotion detection and recognition. The game was implemented ad-hoc in order to elicit joy and frustration, following the emotion elicitation process described by Roseman’s appraisal theory. In this preliminary study, 5 participants played our VR game along with pre-existing ones and self-reported experienced emotions