scholarly journals Real-world size of objects serves as an axis of object space

2021 ◽  
Author(s):  
Taicheng Huang ◽  
Yiying Song ◽  
Jia Liu
Keyword(s):  
Real World ◽  
Principal Component ◽  
Texture Features ◽  
Physical World ◽  
Task Demands ◽  
Deep Convolutional Neural Networks ◽  
Object Space ◽  
Critical Object ◽  
Dimensional Object ◽  
Object Features

Abstract Our mind can represent various objects from the physical world metaphorically into an abstract and complex high-dimensional object space, with a finite number of orthogonal axes encoding critical object features. However, little is known about what features serve as axes of the object space to critically affect object recognition. Here we asked whether the feature of objects’ real-world size constructed an axis of object space with deep convolutional neural networks (DCNNs) based on three criteria of sensitivity, independence and necessity that are impractical to be examined altogether with traditional approaches. A principal component analysis on features extracted by the DCNNs showed that objects’ real-world size was encoded by an independent axis, and the removal of this axis significantly impaired DCNN’s performance in recognizing objects. With a mutually-inspired paradigm of computational modeling and biological observation, we found that the shape of objects, rather than retinal size, co-occurrence, task demands and texture features, was necessary to represent the real-world size of objects for DCNNs and humans. In short, our study provided the first evidence supporting the feature of objects’ real-world size as an axis of object space, and devised a novel paradigm for future exploring the structure of object space.

scholarly journals Real-world size of objects serves as an axis of object space

2021 ◽  
Author(s):  
Taicheng Huang ◽  
Yiying Song ◽  
Jia Liu
Keyword(s):  
Real World ◽  
Temporal Cortex ◽  
Principal Component ◽  
Physical World ◽  
Task Demands ◽  
Deep Convolutional Neural Networks ◽  
Object Space ◽  
The Real ◽  
Ventral Temporal Cortex ◽  
Dimensional Object

Our mind can represent various objects from the physical world metaphorically into an abstract and complex high-dimensional object space, with a finite number of orthogonal axes encoding critical object features. Previous fMRI studies have shown that the middle fusiform sulcus in the ventral temporal cortex separates the real-world small-size map from the large-size map. Here we asked whether the feature of objects' real-world size constructed an axis of object space with deep convolutional neural networks (DCNNs) based on three criteria of sensitivity, independence and necessity that are impractical to be examined altogether with traditional approaches. A principal component analysis on features extracted by the DCNNs showed that objects' real-world size was encoded by an independent component, and the removal of this component significantly impaired DCNN's performance in recognizing objects. By manipulating stimuli, we found that the shape and texture of objects, rather than retina size, co-occurrence and task demands, accounted for the representation of the real-world size in the DCNNs. A follow-up fMRI experiment on humans further demonstrated that the shape, but not the texture, was used to infer the real-world size of objects in humans. In short, with both computational modeling and empirical human experiments, our study provided the first evidence supporting the feature of objects' real-world size as an axis of object space, and devised a novel paradigm for future exploring the structure of object space.

scholarly journals Exploiting Proximity-Based Mobile Apps for Large-Scale Location Privacy Probing

2018 ◽  
Vol 2018 ◽  
pp. 1-22 ◽  
Author(s):  
Shuang Zhao ◽  
Xiapu Luo ◽  
Xiaobo Ma ◽  
Bo Bai ◽  
Yankang Zhao ◽  
...  
Keyword(s):  
Social Networks ◽  
Case Studies ◽  
Real World ◽  
Emission Reduction ◽  
Large Scale ◽  
Location Privacy ◽  
Mobile Apps ◽  
Physical World ◽  
Typical Type ◽  
Location Spoofing

Proximity-based apps have been changing the way people interact with each other in the physical world. To help people extend their social networks, proximity-based nearby-stranger (NS) apps that encourage people to make friends with nearby strangers have gained popularity recently. As another typical type of proximity-based apps, some ridesharing (RS) apps allowing drivers to search nearby passengers and get their ridesharing requests also become popular due to their contribution to economy and emission reduction. In this paper, we concentrate on the location privacy of proximity-based mobile apps. By analyzing the communication mechanism, we find that many apps of this type are vulnerable to large-scale location spoofing attack (LLSA). We accordingly propose three approaches to performing LLSA. To evaluate the threat of LLSA posed to proximity-based mobile apps, we perform real-world case studies against an NS app named Weibo and an RS app called Didi. The results show that our approaches can effectively and automatically collect a huge volume of users’ locations or travel records, thereby demonstrating the severity of LLSA. We apply the LLSA approaches against nine popular proximity-based apps with millions of installations to evaluate the defense strength. We finally suggest possible countermeasures for the proposed attacks.

scholarly journals UAV Recognition Based on Micro-Doppler Dynamic Attribute-Guided Augmentation Algorithm

2021 ◽  
Vol 13 (6) ◽  
pp. 1205
Author(s):  
Caidan Zhao ◽  
Gege Luo ◽  
Yilin Wang ◽  
Caiyun Chen ◽  
Zhiqiang Wu
Keyword(s):  
Recognition Performance ◽  
Principal Component ◽  
Texture Features ◽  
Training Model ◽  
Recognition Algorithm ◽  
Discrete Wavelet ◽  
Dynamic Feature ◽  
Complex Environments ◽  
Time Frequency ◽  
Model Training

A micro-Doppler signature (m-DS) based on the rotation of drone blades is an effective way to detect and identify small drones. Deep-learning-based recognition algorithms can achieve higher recognition performance, but they needs a large amount of sample data to train models. In addition to the hovering state, the signal samples of small unmanned aerial vehicles (UAVs) should also include flight dynamics, such as vertical, pitch, forward and backward, roll, lateral, and yaw. However, it is difficult to collect all dynamic UAV signal samples under actual flight conditions, and these dynamic flight characteristics will lead to the deviation of the original features, thus affecting the performance of the recognizer. In this paper, we propose a small UAV m-DS recognition algorithm based on dynamic feature enhancement. We extract the combined principal component analysis and discrete wavelet transform (PCA-DWT) time–frequency characteristics and texture features of the UAV’s micro-Doppler signal and use a dynamic attribute-guided augmentation (DAGA) algorithm to expand the feature domain for model training to achieve an adaptive, accurate, and efficient multiclass recognition model in complex environments. After the training model is stable, the average recognition accuracy rate can reach 98% during dynamic flight.

Developing a Web Application for the Integration of Real-World, Scientific, Problem-Solving into the Secondary Classroom

2013 ◽  
pp. 422-432
Author(s):  
Susan E. Gill ◽  
Nanette I. Marcum-Dietrich ◽  
John Fraser
Keyword(s):  
Problem Solving ◽  
Real World ◽  
Web Application ◽  
Physical World ◽  
Scientific Problem Solving ◽  
Secondary Classroom ◽  
The World ◽  
Interdisciplinary Framework ◽  
K 12

In the 21st century, digital natives, born into a world of omnipresent technology, spend much of their lives online. However, many teachers still see the use of educational technologies as a challenge (e.g., Ertmer, 2005; Li, 2007). The authors propose that the familiarity and ubiquity of these media offer a valuable way to engage students in meaningful learning. In the last decade, the National Science Foundation has invested heavily in bringing technology into the K-12 classroom by funding an array of cyberlearning applications to investigate how they can transform student learning. Model My Watershed is one of those experimental platforms that integrates online learning with an understanding of the physical world within an interdisciplinary framework. This case study documents the development of this application from concept through implementation and beyond. It provides insights into the challenges of application design and deployment for those entering the world of cyberlearning design.

Selected Shape and Texture Features for Automatic Detection of Acute Lymphoblastic Leukemia

2018 ◽  
pp. 162-183
Author(s):  
Vanika Singhal ◽  
Preety Singh
Keyword(s):  
Acute Lymphoblastic Leukemia ◽  
Lymphoblastic Leukemia ◽  
Principal Component ◽  
Texture Features ◽  
Automatic Detection ◽  
Support Vector ◽  
Shape Features ◽  
Geometrical Properties ◽  
Correlation Based Feature Selection ◽  
Human Interpretation

Acute Lymphoblastic Leukemia is a cancer of blood caused due to increase in number of immature lymphocyte cells. Detection is done manually by skilled pathologists which is time consuming and depends on the skills of the pathologist. The authors propose a methodology for discrimination of a normal lymphocyte cell from a malignant one by processing the blood sample image. Automatic detection process will reduce the diagnosis time and not be limited by human interpretation. The lymphocyte images are classified based on two types of extracted features: shape and texture. To identify prominent shape features, Correlation based Feature Selection is applied. Principal Component Analysis is applied on the texture features to reduce their dimensionality. Support Vector Machine is used for classification. It is observed that 16 shape features are able to give a classification accuracy of 92.3% and that changes in the geometrical properties of the nucleus emerge as significant features contributing towards detecting a malignant lymphocyte.

The Problem

2019 ◽  
pp. 48-58
Author(s):  
Dale Purves
Keyword(s):  
Nervous System ◽  
Real World ◽  
Physical World ◽  
Sensory Systems ◽  
Fundamental Question ◽  
Physical Parameters ◽  
Everyday Experience ◽  
Nervous Systems ◽  
Neural Connections ◽  
Sensory Inputs

Although understanding neural functions has progressed at a remarkable pace in recent decades, a fundamental question remains: How does the nervous system relate the objective world to the subjective domain of perception? Everyday experience implies that the neural connections on which we and other animals depend link physical parameters in the environment with useful responses. But that interpretation won't work: biological sensory systems cannot measure the physical world. Whereas something is linking sensory inputs to useful responses, it is not the physical world that instruments measure. How, then, have we animals met this challenge, and what is it that we end up perceiving? The purpose of this chapter is to suggest how nervous systems have evolved to deal with the inability to convey the objective properties of the real world.

Ensemble Classification System for Scientific Chart Recognition from PDF Files

2012 ◽  
Vol 2 (4) ◽  
pp. 1-10 ◽  
Author(s):  
S. Nagarajan ◽  
V. Karthikeyani
Keyword(s):  
Feature Extraction ◽  
Classification System ◽  
Texture Features ◽  
Portable Document Format ◽  
Ensemble Classification ◽  
3 Dimensional ◽  
Feature Based ◽  
Separation Feature ◽  
Object Features ◽  
Document Format

Portable Document Format (PDF) is the most frequently used universal document format on the Internet and E-Publishing. Wide usage of PDF files has increased the need of conversion tools that convert PDF file content to text or HTML formats. A PDF converter can be categorized into two domains, namely, text recognition and graphics recognition. This paper focus on graphic recognition, especially chart type identification, which is concerned with developing algorithms that has the ability to determine the type of a given chart image from a PDF file. In the proposed system, initially an enhanced connected component and statistical feature based method is used to separate the chart region from other regions. The chart region is then analyzed and grouped as either 2-dimensional or 3-dimensional chart. After separating the graphic component from the text components, feature extraction is performed. The features can be grouped as object features, texture features and shape features. The combined feature vector is then classified using ensemble classification system. Experimental results show that the chart separation, feature extraction and ensemble classification models significantly improve the quality of chart identification.

scholarly journals Exploring sensorimotor performance and user experience within a virtual reality golf putting simulator

2020 ◽  
Author(s):  
David J. Harris ◽  
Gavin Buckingham ◽  
Mark R. Wilson ◽  
Jack Brookes ◽  
Faisal Mushtaq ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Construct Validity ◽  
Real World ◽  
High Performance ◽  
Task Demands ◽  
Self Report ◽  
The Real ◽  
Task Load ◽  
Golf Putting ◽  
Effective Transfer

Abstract In light of recent advances in technology, there has been growing interest in virtual reality (VR) simulations for training purposes in a range of high-performance environments, from sport to nuclear decommissioning. For a VR simulation to elicit effective transfer of training to the real-world, it must provide a sufficient level of validity, that is, it must be representative of the real-world skill. In order to develop the most effective simulations, assessments of validity should be carried out prior to implementing simulations in training. The aim of this work was to test elements of the physical fidelity, psychological fidelity and construct validity of a VR golf putting simulation. Self-report measures of task load and presence in the simulation were taken following real and simulated golf putting to assess psychological and physical fidelity. The performance of novice and expert golfers in the simulation was also compared as an initial test of construct validity. Participants reported a high degree of presence in the simulation, and there was little difference between real and virtual putting in terms of task demands. Experts performed significantly better in the simulation than novices (p = .001, d = 1.23), and there was a significant relationship between performance on the real and virtual tasks (r = .46, p = .004). The results indicated that the simulation exhibited an acceptable degree of construct validity and psychological fidelity. However, some differences between the real and virtual tasks emerged, suggesting further validation work is required.

Fuzzy Boundaries, Strange Negotiations

2011 ◽  
pp. 338-361
Author(s):  
Andrew Wenn
Keyword(s):  
Cultural Capital ◽  
Real World ◽  
Virtual Community ◽  
Physical World ◽  
Complex Interaction ◽  
Focus Attention ◽  
Material Technology ◽  
Complex Material

In 1997, attempting to focus attention on the imploding boundaries between organism and machine Mizuko Ito wrote about multi-user dungeons (MUDs). These are communities where people who have created online personae come together as a virtual community and act out roles in ways that they imagine this person would. Whilst others have extolled the virtualness of these online worlds (Benedikt, 1991; Heim, 1991; Rheingold, 1995), Ito showed us that there are other ways of seeing that reveal these worlds as a “complex interaction between a network of various ‘real world’ material technologies as well as the cultural capital of its users and designers” (Ito 1997, p. 91). Whilst much of Turkle’s (1996) book focuses on life beyond the screen and people’s behavior in what many see as the virtuality of cyberspace, towards the end of the book, she hints that there is a physical world that these “cyberplayers” are bound to and will ultimately die in (1996). In a rather more pragmatic vein, Cringley reminds us that some one has to do the wiring, that there is a complex material technology beneath all this. It is this interplay between the virtual and material technologies that I wish to explore here.

scholarly journals Making Science Fiction Real: Neoliberalism, Real-Life and Esports in Eve Online

2018 ◽  
Vol 10 (3) ◽  
Author(s):  
Mark Richard Johnson ◽  
Robert Mejia
Keyword(s):  
Science Fiction ◽  
Virtual Worlds ◽  
Real World ◽  
Free Market ◽  
Real Life ◽  
Physical World ◽  
The Real ◽  
Contemporary World ◽  
Neoliberal Capitalism ◽  
Political Economic

In this paper, we argue that EVE Online is a fruitful site for exploring how the representational and political-economic elements of science fiction intersect to exert a sociocultural and political-economic force on the shape and nature of the future-present. EVE has been oft heralded for its economic and sociocultural complexity, and for employing a free market ethos and ethics in its game world. However, we by contrast seek not to consider how EVE reflects our contemporary world, but rather how our contemporary neoliberal milieu reflects EVE. We explore how EVE works to make its world of neoliberal markets and borderline anarcho-capitalism manifest through the political economic and sociocultural assemblages mobilized beyond the game. We explore the deep intertwining of  behaviors of players both within and outside of the game, demonstrating that EVE promotes neoliberal  activity in its players, encourages these behaviors outside the game, and that players who have found success in the real world of neoliberal capitalism are those best-positioned for success in the time-demanding and resource-demanding world of EVE. This thereby sets up a reciprocal ideological determination between the real and virtual worlds of EVE players, whereby each reinforces the other. We lastly consider the “Alliance Tournament” event, which romanticizes conflict and competition, and argue that it serves as a crucial site for deploying a further set of similar rhetorical resources. The paper therefore offers an understanding of the sociocultural and political-economic pressure exerted on the “physical” world by the intersection of EVE’s representational and material elements, and what these show us about the real-world ideological power of science fictional worlds.

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