Processing continuous range queries with spatiotemporal tolerance

Continuous queries are often employed to monitor the locations of mobile objects (MOs), which are determined by sensing devices like GPS receivers. In this paper, we tackle two challenges in processing continuous range queries (CRQs): coping with data uncertainty inherently associated with location data, and reducing the energy consumption of battery-powered MOs. We propose the concept of spatiotemporal tolerance for CRQ to relax a query's accuracy requirements in terms of a maximal acceptable error. Unlike previous works, our definition considers tolerance in both the spatial and temporal dimensions, which offers applications more flexibility in specifying their individual accuracy requirements. As we will show, these tolerance bounds can provide well-defined query semantics in spite of different sources of data uncertainty. In addition, we present efficient algorithms that carefully control when an MO should sense or report a location, while satisfying these tolerances. Thereby, we particularly reduce the number of position sensing operations substantially, which constitute a considerable source of energy consumption. Extensive simulations confirm that the proposed algorithms result in large energy savings compared to nontolerant query processing. © 2006 IEEE.published_or_final_versio

Semantically Informed Multiview Surface Refinement

We present a method to jointly refine the geometry and semantic segmentation of 3D surface meshes. Our method alternates between updating the shape and the semantic labels. In the geometry refinement step, the mesh is deformed with variational energy minimization, such that it simultaneously maximizes photo-consistency and the compatibility of the semantic segmentations across a set of calibrated images. Label-specific shape priors account for interactions between the geometry and the semantic labels in 3D. In the semantic segmentation step, the labels on the mesh are updated with MRF inference, such that they are compatible with the semantic segmentations in the input images. Also, this step includes prior assumptions about the surface shape of different semantic classes. The priors induce a tight coupling, where semantic information influences the shape update and vice versa. Specifically, we introduce priors that favor (i) adaptive smoothing, depending on the class label; (ii) straightness of class boundaries; and (iii) semantic labels that are consistent with the surface orientation. The novel mesh-based reconstruction is evaluated in a series of experiments with real and synthetic data. We compare both to state-of-the-art, voxel-based semantic 3D reconstruction, and to purely geometric mesh refinement, and demonstrate that the proposed scheme yields improved 3D geometry as well as an improved semantic segmentation

A comparison of the magnetic properties of Proton- and Iron-implanted graphite

In this work we have investigated the changes of the magnetic properties of highly oriented pyrolytic graphite samples after irradiation either with $\sim 3 \times 10^{14}$ protons or $3.5 \times 10^{13} ... 3.5 \times 10^{14}$ iron ions with energies in the MeV range. Our results show that iron and proton irradiations can produce similar paramagnetic contributions depending on the implantation temperature. However, only protons induce a ferromagnetic effect.Comment: 4 pages with three figures. To be published in EPJ

Uma “Mesquita” (lugar de culto) no Alentejo – invisibilidades na cidade

Este artigo visa refletir sobre as novas práticas culturais que se estabeleceram numa cidade do Baixo Alentejo, como resultado da chegada de estudantes estrangeiros, refugiados e migrantes económicos do Médio Oriente, China e de diferentes países africanos, bem como da Europa de Leste. Há mudanças óbvias e imediatamente visíveis no rosto da cidade, mas outras estão como que “cercadas” por um secretismo de que só os mais atentos parecem dar-se conta. Referimo-nos à existência de um local de culto, vulgarmente designado por “Mesquita” instalado em Beja, há cerca de dois anos. Nada a identifica – é uma casa de um único andar, com uma porta e uma janela – situada numa rua estreita, em pleno centro histórico da cidade. Muitos dos habitantes de Beja desconhecem a sua existência. Porém, nesta cidade, templos católicos e protestantes são visíveis e identificados sem qualquer problema. Portanto, o facto de a “Mesquita” emergir como um edifício de alguma forma “oculto” levanta questões sobre identidade social e processos sociais de exclusão e incorporação subjacentes àqueles que a frequentam. A cidade reivindica um forte passado islâmico, pelo que seria expectável que a presença de comunidades muçulmanas enviasse os habitantes deste território para um tempo e espaço comuns de pertença; um tempo que lhes permita aceitar a religião muçulmana de forma pacífica e inclusiva. Sendo a existência da “Mesquita” desconhecida para tantos habitantes, impõe-se a necessidade de conhecer as razões pelas quais isso acontece

Dungeons and Data: A Large-Scale NetHack Dataset

Recent breakthroughs in the development of agents to solve challenging sequential decision making problems such as Go [50], StarCraft [58], or DOTA [3], have relied on both simulated environments and large-scale datasets. However, progress on this research has been hindered by the scarcity of open-sourced datasets and the prohibitive computational cost to work with them. Here we present the NetHack Learning Dataset (NLD), a large and highly-scalable dataset of trajectories from the popular game of NetHack, which is both extremely challenging for current methods and very fast to run [23]. NLD consists of three parts: 10 billion state transitions from 1.5 million human trajectories collected on the NAO public NetHack server from 2009 to 2020; 3 billion state-action-score transitions from 100,000 trajectories collected from the symbolic bot winner of the NetHack Challenge 2021; and, accompanying code for users to record, load and stream any collection of such trajectories in a highly compressed form. We evaluate a wide range of existing algorithms including online and offline RL, as well as learning from demonstrations, showing that significant research advances are needed to fully leverage large-scale datasets for challenging sequential decision making tasks

Reconnaissance of the Bedrock Aquifers and Groundwater Chemistry of Crawford, Franklin, and Sebastian Counties, Arkansas

A ground water reconnaissance of Crawford, Franklin, and Sebastian counties was performed utilizing 122 wells having drillers\u27 logs from bedrock aquifers. North of the Arkansas River, essentially all bedrock wells produce from the Atoka Formation. There are many low producing aquifers within the Atoka with a range in yield of 0.1 to 55 gpm, but having a median yield of only 2 gpm. Well depths range from 18 to 248 feet with a median of 122 feet. More water is generally obtained from the shale/siltstone aquifers than the sandstones due to more bedding-plane partings and more closely spaced fractures. Greater yields are also found in valleys. South of the Arkansas River, three additional bedrock aquifers are utilized. The aquifers and median yield are as follows: (1)Savannah Sandstone (11.7 gpm), (2) Hartshorne Sandstone (10 gpm), and (3) McAlester Shale (5.2 gpm). Well depths range from 40 to 300 feet. Seventeen wells in the Atoka were sampled and analyzed. The median iron concentration was 0.15, but four wells had over the 0.3 ppm health limit. Sulfate values ranged from31 to 125 ppm with a median of 45 ppm. Chloride concentrations ranged from 16 to 58 ppm with a median of 33 ppm. These relatively high values commonly give the water a bitter and strigent taste with some H₃S odor. The source of these ions may be from pyrite weathering or to contamination from the many gas fields in the area

An empirical study of fault localization for end-user programmers

End users develop more software than any other group of programmers, using software authoring devices such as e-mail filtering editors, by-demonstration macro builders, and spreadsheet environments. Despite this, there has been little research on finding ways to help these programmers with the dependability of their software. We have been addressing this problem in several ways, one of which includes supporting end-user debugging activities through fault localization techniques. This paper presents the results of an empirical study conducted in an end-user programming environment to examine the impact of two separate factors in fault localization techniques that affect technique effectiveness. Our results shed new insights into fault localization techniques for end-user programmers and the factors that affect them, with significant implications for the evaluation of those techniques

Gravity compensation in complex plasmas by application of a temperature gradient

Micron sized particles are suspended or even lifted up in a gas by thermophoresis. This allows the study of many processes occurring in strongly coupled complex plasmas at the kinetic level in a relatively stress-free environment. First results are presented. The technique is also of interest for technological applications.Comment: 4 pages, 4 figures, final version to be published in Phys. Rev. Let