Evaluation of Deep Convolutional Nets for Document Image Classification and Retrieval

This paper presents a new state-of-the-art for document image classification and retrieval, using features learned by deep convolutional neural networks (CNNs). In object and scene analysis, deep neural nets are capable of learning a hierarchical chain of abstraction from pixel inputs to concise and descriptive representations. The current work explores this capacity in the realm of document analysis, and confirms that this representation strategy is superior to a variety of popular hand-crafted alternatives. Experiments also show that (i) features extracted from CNNs are robust to compression, (ii) CNNs trained on non-document images transfer well to document analysis tasks, and (iii) enforcing region-specific feature-learning is unnecessary given sufficient training data. This work also makes available a new labelled subset of the IIT-CDIP collection, containing 400,000 document images across 16 categories, useful for training new CNNs for document analysis

Structure of the Charge-Density Wave in Cuprate Superconductors: Lessons from NMR

Using a mix of numerical and analytic methods, we show that recent NMR $^{17}$O measurements provide detailed information about the structure of the charge-density wave (CDW) phase in underdoped YBa$_2$Cu$_3$O$_{6+x}$. We perform Bogoliubov-de Gennes (BdG) calculations of both the local density of states and the orbitally resolved charge density, which are closely related to the magnetic and electric quadrupole contributions to the NMR spectrum, using a microscopic model that was shown previously to agree closely with x-ray experiments. The BdG results reproduce qualitative features of the experimental spectrum extremely well. These results are interpreted in terms of a generic "hotspot" model that allows one to trace the origins of the NMR lineshapes. We find that four quantities---the orbital character of the Fermi surface at the hotspots, the Fermi surface curvature at the hotspots, the CDW correlation length, and the magnitude of the subdominant CDW component---are key in determining the lineshapes

Deceptive Intentions: Can Cues to Deception Be Measured before a Lie Is Even Stated?

Can deceitful intentions be discriminated from truthful ones? Previous work consistently demonstrated that deceiving others is accompanied by nervousness/stress and cognitive load. Both are related to increased sympathetic nervous system (SNS) activity. We hypothesized that SNS activity already rises during intentions to lie and, consequently, cues to deception can be detected before stating an actual lie. In two experiments, controlling for prospective memory, we monitored SNS activity during lying, truth telling, and truth telling with the aim of lying at a later instance. Electrodermal activity (EDA) was used as an indicator of SNS. EDA was highest during lying, and compared to the truth condition, EDA was also raised during the intention to deceive. Moreover, the switch from truth telling toward lying in the intention condition evoked higher EDA than switching toward non-deception related tasks in the lie or truth condition. These results provide first empirical evidence that increased SNS activity related to deception can be monitored before a lie is stated. This implies that cues to deception are already present during the mere intention to lie. © 2015 Ströfer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

The effectiveness of a mediation program in symmetrical versus asymmetrical neighbor-to-neighbor conflicts

Purpose – The last decades, neighborhood mediation programs have become an increasingly popular method to deal with conflicts between neighbors. In the current paper the aim is to propose and show that conflict asymmetry, the degree to which parties differ in perceptions of the level of conflict, may be important for the course and outcomes of neighborhood mediation. \ud \ud Design/methodology/approach – Data for testing the hypotheses were based on coding all (261) files of neighbor conflicts reported to a Dutch neighborhood mediation program in the period from 2006 through 2008. \ud \ud Findings – As expected, cases were more often about asymmetrical than symmetrical conflicts. Moreover, compared to symmetrical conflicts, asymmetrical conflicts less often led to a mediation session; the degree of escalation was lower; and, particularly in asymmetrical conflicts, a mere intake session already contributed to positive conflict outcomes. \ud \ud Originality/value – Past research on the effectiveness of mediation programs mainly focused on cases in which a mediation session effectively took place. However, persuading parties to participate in a mediation session forms a major challenge for mediators. In fact, many cases that are signed-up for mediation programs do not result in an actual mediation. The current study examines the entire mediation process – from intake to follow-up\u

High-Stakes Conflicts and the Link between Theory and Practice:Celebrating the Work of Ellen Giebels

In this tribute to the 2012 recipient of the IACM's Jeffrey Rubin's Theory‐to‐Practice Award, we celebrate the work of Ellen Giebels. We highlight her groundbreaking research on influence tactics in crisis negotiations and other high‐stakes conflict situations, showing how her focus on theoretical foundations and careful design has delivered contributions of practical relevance. We then hear from two early career researchers who share how Ellen's research and mentorship fostered their own desire to deliver impactful research. We conclude by inviting Ellen to reflect on future research questions and to underscore her vision on the use of technology in conflict and negotiations research