Computing Possible and Certain Answers over Order-Incomplete Data

This paper studies the complexity of query evaluation for databases whose relations are partially ordered; the problem commonly arises when combining or transforming ordered data from multiple sources. We focus on queries in a useful fragment of SQL, namely positive relational algebra with aggregates, whose bag semantics we extend to the partially ordered setting. Our semantics leads to the study of two main computational problems: the possibility and certainty of query answers. We show that these problems are respectively NP-complete and coNP-complete, but identify tractable cases depending on the query operators or input partial orders. We further introduce a duplicate elimination operator and study its effect on the complexity results.Comment: 55 pages, 56 references. Extended journal version of arXiv:1707.07222. Up to the stylesheet, page/environment numbering, and possible minor publisher-induced changes, this is the exact content of the journal paper that will appear in Theoretical Computer Scienc

The Effects of Intercritical Heat Treatments on the Mechanical Properties of 0.14wt%C - 0.56wt%Mn - 0.13wt%Si Structural Steel

Effect of intercritical heat treatment on 0.14wt%C 0.56wt%Mn 0.13wt%Si structural steel has been investigated. Specimens for single quenching and those for double quenching were prepared for intercritical heat treatment. The heat treatment of the experimental steel was based on intercritical annealing in the ferrite + austenite temperature range of the Fe-C phase diagram at temperatures 745oC,755oC, 765oC, 775oC, 785oC, 795oC and 805oC for 1 hour at each temperature in a laboratory muffle heat treatment furnace followed by quenching in plain water to room temperature. Specimens for single quenching were subjected to the above heat treatment route once while those for double quenching were subjected to the heat treatment route twice. Afterwards the specimens that were subjected to single quenching and those that were subjected to double quenching were separately tempered in a laboratory muffle heat treatment furnace at a temperature of 200oC for 1 hour and cooled to room temperature in still air. The results revealed that single quenching eliminated the yield strength, increased the tensile strength and hardness properties but decreased the ductility and notch impact toughness properties of the experimental steel. Moreover, the results also revealed that double quenching eliminated the yield strength, and produced a greater increase in tensile strength and hardness properties than single quenching but a greater decrease in the ductility and notch impact toughness properties than single quenching of the experimental steel. Tempering increased the yield strength, ductility and notch impact toughness properties of the quenched steels but decreased their tensile strength and hardness properties. The established heat treatment conditions can be useful for manufacturing steels of high strength and hardness and good ductile and notch impact toughness properties

Possible and Certain Answers for Queries over Order-Incomplete Data

To combine and query ordered data from multiple sources, one needs to handle uncertainty about the possible orderings. Examples of such "order-incomplete" data include integrated event sequences such as log entries; lists of properties (e.g., hotels and restaurants) ranked by an unknown function reflecting relevance or customer ratings; and documents edited concurrently with an uncertain order on edits. This paper introduces a query language for order-incomplete data, based on the positive relational algebra with order-aware accumulation. We use partial orders to represent order-incomplete data, and study possible and certain answers for queries in this context. We show that these problems are respectively NP-complete and coNP-complete, but identify many tractable cases depending on the query operators or input partial orders

Data Association and Track Management for the Gaussian Mixture Probability Hypothesis Density Filter

The Gaussian mixture probability hypothesis density (GM-PHD) recursion is a closed-form solution to the probability hypothesis density (PHD) recursion, which was proposed for jointly estimating the time-varying number of targets and their states from a sequence of noisy measurement sets in the presence of data association uncertainty, clutter, and miss-detection. However the GM-PHD filter does not provide identities of individual target state estimates, that are needed to construct tracks of individual targets. In this paper, we propose a new multi-target tracker based on the GM-PHD filter, which gives the association amongst state estimates of targets over time and provides track labels. Various issues regarding initiating, propagating and terminating tracks are discussed. Furthermore, we also propose a technique for resolving identities of targets in close proximity, which the PHD filter is unable to do on its own

Emotional/Psychiatric Symptom Change and Amygdala Volume After Anterior Temporal Lobectomy

Introduction Patients who undergo anterior temporal lobectomy (ATL) to treat temporal lobe epilepsy (TLE) often experience worsened or de novo psychiatric symptoms. There is evidence to suggest that the pathophysiology of epilepsy and mood disorders are linked both functionally or structurally in the brain.1,2 While several studies have examined the role that changes in hippocampal volume may play in predicting post-surgical depression, the role of the amygdala in such prediction has been overlooked, despite extensive literature demonstrating its contribution to emotion processing and expression.3,4 The goal of this project was to determine if change in amygdala volume is a predictor of depression and/or anxiety in TLE patients who undergo ATL, with specific attention given to side of surgery. Methods Data was collected from 32 patients who underwent ATLs (19 right, 13 left, matched samples). Pre- and post-surgery Personality Assessment Inventory (PAI) data were collected on 14 ATL patients. The following PAI subscales were utilized in this analysis: Anxiety: PAIANX; Anxiety Related Disorder: PAIARD; Depression: PAIDEP). Volumetric analysis was performed on pre- and post-surgical T1 MRIs using Freesurfer’s longitudinal processing function. Left and right amygdala volumes, change scores, and amygdala asymmetry ratios were calculated taking into account whole brain volume. 55% of the patients were seizurefree after 1 year (RTLE= 8, LTLE= 9); 29% received an Engel Class score of 2 or 3 (RTLE= 7, LTLE= 2