Intelligent digital image firewall system for filtering privacy or sensitive images

As the commonest part of social networks, sharing images in social network not only provides more information, but also gives more intuitive view than text. However, images also can leak out information more easily than text, so the audit of image content is particularly essential. The disclosure of a tiny image, which involves sensitive information about individual, society even the state, may trigger a series of serious problems. In this paper, we design a kind of intelligent image firewall to detect and filter sensitive or privacy images. Two different approaches of the firewall are proposed. In the first approach, we propose an image firewall based on joint sparse representation, which can provide accurate and robust privacy prediction, and also can provide rich spatial relationship information. In the second approach, we propose a method based on the deep learning (Faster RCNN), which can predict the privacy relationships or actions (like kiss, hug and hand in hand) among the persons of an image. Experimental results show the effectiveness of the two kinds of approaches.     

Examining multiple feature evaluation and classification methods for improving the diagnosis of Parkinson’s disease

An accurate diagnosis of Parkinson’s disease by specialists involves many neurological, psychological and physical examinations. The specialists investigate a number of symptoms and signs when examining the nervous system conditions of a person. The diagnosis involves reviewing the medical history and genetic factor of the person. The recent diagnosis methodology to Parkinson’s disease relies on voice disorders analysis. This methodology entails extracting feature sets of a recorded person’s voice then utilizing a machine learning technique to identify the healthy and Parkinson’s cases from the voice. This paper attempts to improve the diagnoses of Parkinson’s disease by testing multiple feature evaluation and classification machine learning methods based on the voice disorders analysis. The aim of this paper is to find the optimal solution to the problem by (i) proposing a new Multiple Feature Evaluation Approach (MFEA) of a multi-agent system (ii) implementing five independent classification schemas which are Decision Tree, Naïve Bayes, Neural Network, Random Forests, and Support Vector Machine on the Parkinson’s diagnosis before and after applying the MFEA, and (iii) evaluating the diagnosis accuracy of the results. The methodology of the tests encompasses 10-fold cross-validation to evaluate the learning of methods and track variation in their performance. The test results show that the MFEA of the multi-agent system finds the best set of features and improves the performance of the classifiers. The average rate of improvement in the diagnostic accuracy of the classifiers are Decision Tree 10.51%, Naïve Bayes 15.22%, Neural Network 9.19%, Random Forests 12.75%, and Support Vector Machine 9.13%. These results show that the MFEA makes a significant improvement to the classifiers’ diagnosis results.     

Feature selection using Ant Colony Optimization (ACO) and Road Sign Detection and Recognition (RSDR) system

Road Sign Detection and Recognition (RSDR) is aimed to enable drivers maintain basic functionality with the aim of identifying and notifying driver through the existing restrictions so that the process is a success on the present widened road. Examples for RSDR include ‘traffic light ahead’ or ‘pedestrian crossing’ signs. An innovative RSDR system has been introduced which comprises of pre-processing, edge detection, feature extraction, features selection and Ensemble Fuzzy Support Vector Machine (EFSVM) classifier. Feature selection is carried out successfully by deployment of Ant Colony Optimization (ACO) algorithm to determine most prominent and definitive features. These features are then fed into the ensemble SVM to enable both road side traffic detection as well as recognition. Suggested system’s performance is analyzed and evaluated with respect to road signs having a capable recognition rate.     

产品空间位置、价格音节长度对消费者价格感知的影响

本研究采用实验法考察了视听单通道及双通道下产品空间位置与价格音节长度对消费者价格感知的潜在影响。结果发现,呈现在空间右侧以及以较长音节播放的产品使得被试的价格感知升高;短音节条件下,个体对空间右侧产品的价格感知显著高于空间左侧,长音节条件下两侧则无显著差异;相对于单通道刺激呈现,视听通道呈现信息一致时出现信息冗余效应,个体判断的速度更快,验证了共激活模型假设,视听不一致条件下的速度降低则支持了预测编码模型。     

记忆的顿悟优势效应

记忆的顿悟优势效应指, 与加工非顿悟问题相比, 加工顿悟问题能够产生更优的记忆保持量。该效应在顿悟的两种操作性定义以及不同实验材料中稳定出现。基于顿悟阶段观, 研究者提出两种理论解释记忆的顿悟优势效应的认知机制：认知的生成效应和表征转化理论认为, 顿悟加工过程中的认知努力、适当迁移加工以及顿悟的表征转换加工促进记忆的保持效果; 情绪的“啊哈”体验理论认为, 加工顿悟问题后的情绪对后续的信息提取具有促进作用。未来的研究可从优化顿悟的指标、巩固记忆的顿悟优势效应、评估其持续性以及更加系统探讨记忆的顿悟优势效应的认知机制等四个方面展开。     

Characterization of controlled gamblers and pathological gamblers using the social representation theory

Introduction

In industrialized countries, gambling disorder tends to become a major issue. The use of the social representation theory provides clues for a better understanding of pathological gamblers.

Structure sociale et cultures organisationnelles : une application du modèle des représentations sociales

The theme of organizational culture has been subject of many studies, which postulates are divergent. Consensual, shared and transmitted by the direction for some persons, they follow from the articulation of professional identities models for other persons. Social representation theory can allow us to understand that co-existence of consensual and specific elements, depending on the social structure of the organization. A questionnaire, developed after 24 semi-directive interviews, has been submitted to 95 employees of a large distribution company. Results show that organizational culture is a representation organized on six themes, socially elaborated on the interaction of groups situated in different positions. Consensual elements pass through the various groups, and some elements, more specifics, show the differences between these groups, depending on their strategic links.     

Muscular Imaginings—A Phenomenological and Enactive Model for Imagination*

A phenomenological model (labeled ‘EC’) is developed as an alternative to current analyses of the imagination in sport philosophy, heirs to an Enlightenment notion that conceptualizes imaginings as abstract, eidetic, and representational. EC describes how Eidetic and Corporeal Imaginings (EIs & CIs) phenomenologically structure our imaginative undertakings. EIs keep the ‘ideal’ aspect, but CIs—enacted, corporeal, non-representational—are more fundamental and foundational. Sports are particularly suited to express CIs’ muscular imaginings, which result in novel performances. An enactive framework theorizes CIs as non-representational interactions.     

知觉表征精度对工作记忆中抑制干扰能力的影响

工作记忆的容量十分有限,需要选择性地抑制与目标无关信息的干扰,工作记忆容量高的个体,其抑制干扰的能力也更强。本研究采用带有不同形状干扰刺激的色块颜色回忆任务考察干扰对工作记忆容量和表征精度的影响,结果发现,当负荷超出工作记忆容量范围时,干扰减少了记忆所能表征客体的个数;当负荷在工作记忆容量范围内时,干扰降低了记忆中表征客体的精度。更进一步,研究采用独立的知觉任务来测量知觉表征的精度,并探讨作为信息加工的初始阶段的知觉表征如何影响工作记忆加工过程中抑制干扰的能力。将实验中收集的48名有效被试按照知觉表征精度的高低平均分为两组,结果发现上述干扰效应主要表现在知觉表征精度较低的组中,并且该组中知觉表征精度越高的个体,其工作记忆抑制干扰的能力也越强。本研究为实践中通过知觉训练来提升工作记忆的抑制干扰能力提供了理论指导。     

EPIGENETICS,REPRESENTATION, AND SOCIETY

In recent decades, advances in the life sciences have created an unprecedentedly detailed picture of heredity and the formation of the phenotype where clusters of simplistic reductionist and deterministic views and interpretations have begun to lose ground to more complex and holistic notions. The developments in gene regulation and epigenetics have become a vivid emblem of the ongoing ‘softening’ of heredity. Despite this headway, the outlook and rhetoric widely popular in the twentieth century favoring the ‘gene’ in the ‘gene?genetic plasticity?phenotype?environment’ tetrad have not been successfully tackled but continue to exist in parallel with a new, equally monochromatic, viewpoint championing genetic plasticity. An examination of epigenetics and its presentation in the public sphere, open to a conversation with the social disciplines and philosophy, could address this dichotomy and contribute to the discourse. This article outlines key biological aspects of epigenetics and discusses the language, presentation and wider resonance of this field of life science research.