A discovery about the positional distribution pattern among candidate homologous pixels and its potential application in aerial multi-view image matching

In aerial multi-view photogrammetry, whether there is a special positional distribution pattern among candidate homologous pixels of a matching pixel in the multi-view images? If so, can this positional pattern be used to precisely confirm the real homologous pixels? These problems have not been studied at present. Therefore, the study of the positional distribution pattern among candidate homologous pixels based on the adjustment theory in surveying is investigated in this paper. Firstly, the definition and computing method of pixel’s pseudo object-space coordinates are given, which can transform the problem of multi-view matching for confirming real homologous pixels into the problem of surveying adjustment for computing the pseudo object-space coordinates of the matching pixel. Secondly, according to the surveying adjustment theory, the standardized residual of each candidate homologous pixel of the matching pixel is figured out, and the positional distribution pattern among these candidate pixels is theoretically inferred utilizing the quantitative index of standardized residual. Lastly, actual aerial images acquired by different sensors are used to carry out experimental verification of the theoretical inference. Experimental results prove not only that there is a specific positional distribution pattern among candidate homologous pixels, but also that this positional distribution pattern can be used to develop a new object-side multi-view image matching method. The proposed study has an important reference value on resolving the defects of existing image-side multi-view matching methods at the mechanism level.

The Every Day Work of Studying the Law in Everyday Life

Susan Silbey began her academic training in political science and in the course of her studies became a sociologist of law, the last two decades as a member of the Massachusetts Institute of Technology's anthropology department and management school. The disciplinary transformations ground, in part, her attention to the ways in which the everyday life of scholarship has led her to study the everyday life of the law. In this article, she describes her scholarly life through seven chapters of relatively distinct challenges and themes. Across the arc of her life, she identifies the recurrent influence of both serendipity and theoretical inference acting within the immediate constraints of family and personal capacity. Reading across descriptions of her work on regulatory enforcement, dispute negotiation and mediation, and popular legal culture and consciousness, she points to the necessity of reconciling on-the-ground vicissitudes of doing legal work with the theories and narratives social scientists construct to make sense of institutions and history. She muses on theoretical attempts to align the particular and the general, the micro and macro forces working in legal cultures, and concludes by celebrating the ubiquity of social ordering whose own momentum both seduces and frustrates social scientists.

Being Pluralist About Understanding Others

Intersubjective interactions are highly complex processes that integrate a variety of contextual aspects—physical, pragmatic, social, cultural, normative, institutional—into which embodied individuals, with varying emotions, intents, desires, and motivations, enter. We elucidate the role of context in different varieties of social understanding. We defend a pluralist approach to social cognition and in that framework consider the limited role of mindreading understood as a form of theoretical inference or simulation, as well as the importance of embodied interaction. We argue that all of these practices need to be considered in order to comprehend the rich effects of context on social cognition. We exemplify the bidirectional influence between social understanding and context specifically by focusing on communicative practices and material engagements.

Control of entropy in neural models of environmental state

Humans and animals construct internal models of their environment in order to select appropriate courses of action. The representation of uncertainty about the current state of the environment is a key feature of these models that controls the rate of learning as well as directly affecting choice behaviour. To maintain flexibility, given that uncertainty naturally decreases over time, most theoretical inference models include a dedicated mechanism to drive up model uncertainty. Here we probe the long-standing hypothesis that noradrenaline is involved in determining the uncertainty, or entropy, and thus flexibility, of neural models. Pupil diameter, which indexes neuromodulatory state including noradrenaline release, predicted increases (but not decreases) in entropy in a neural state model encoded in human medial orbitofrontal cortex, as measured using multivariate functional MRI. Activity in anterior cingulate cortex predicted pupil diameter. These results provide evidence for top-down, neuromodulatory control of entropy in neural state models.

Multi-asset portfolio with trapezoidal fuzzy present values

The main purpose of the following paper is to present characteristics of a multi-asset portfolio in case of present values of composing financial instruments being modelled by a trapezoidal fuzzy number. Throughout the analysis a fuzzy expected discount factor and imprecision risk assessments are calculated. Thanks to that, there arises a possibility to describe the influence of portfolio diversification on imprecision risk. Presented theoretical inference and obtained conclusions are supported by numerical example.

Performance Analysis of Honeypot with Petri Nets

As one of the active defense technologies, the honeypot deceives the latent intruders to interact with the imitated systems or networks deployed with security mechanisms. Its modeling and performance analysis have not been well studied. In this paper, we propose a honeypot performance evaluation scheme based on Stochastic Petri Nets (SPN). We firstly set up performance evaluation models for three types of defense scenarios (i.e., firewall; firewall and Intrusion Detection System (IDS); firewall, IDS and honeypot) based on SPN. We then theoretically analyze the SPN models by constructing Markov Chains (MC), which are isomorphic to the models. With the steady state probabilities based on the MC, the system performance evaluation is done with theoretical inference. Finally, we implement the proposed three SPN models on the PIPE platform. Five parameters are applied to compare and evaluate the performance of the proposed SPN models. The analysis of the probability and delay of three scenarios shows that the simulation results validate the effectiveness in security enhancement of the honeypot under the SPN models.

Effects of the Slot Harmonics on the Stator Current in an Induction Motor with Bearing Fault

Bearing faults are the most frequent faults of induction motors. The current spectrum analysis is an easy and popular method for the monitoring and detection of bearing faults. After a presentation of the existing fault models, this paper illustrates an analytical approach to evaluate the effects of the slot harmonics on the stator current in an induction motor with bearing fault. Simple and clear theoretical analysis results in some new current characteristic frequencies. Experimental tests with artificial bearing outer raceway fault are carried out by measuring stator current signals. The experimental results by spectral analysis of the stator current agree well with the theoretical inference.