scholarly journals Quantum-Based Creative Generation Method for a Dancing Robot

2020 ◽  
Vol 14 ◽  
Author(s):  
Peng Mei ◽  
GangYi Ding ◽  
QianKun Jin ◽  
FuQuan Zhang ◽  
YangFan Jiao
Keyword(s):  
Process Model ◽  
Generative Adversarial Networks ◽  
Knowledge Map ◽  
Human Society ◽  
Generation Process ◽  
Execution Plan ◽  
Artificial Brain ◽  
Dance Movements ◽  
Creative Generation ◽  
Quantum Modeling

In this paper, we propose a creative generation process model based on the quantum modeling simulation method. This model is mainly aimed at generating the running trajectory of a dancing robot and the execution plan of the dancing action. First, we used digital twin technology to establish data mapping between the robot and the computer simulation environment to realize intelligent controllability of the robot's trajectory and the dance movements described in this paper. Second, we conducted many experiments and carried out a lot of research into information retrieval, information fidelity, and result evaluation. We constructed a multilevel three-dimensional spatial quantum knowledge map (M-3DQKG) based on the coherence and entangled states of quantum modeling and simulation. Combined with dance videos, we used regions with convolutional neural networks (R-CNNs) to extract character bones and movement features to form a movement library. We used M-3DQKG to quickly retrieve information from the knowledge base, action library, and database, and then the system generated action models through a holistically nested edge detection (HED) network. The system then rendered scenes that matched the actions through generative adversarial networks (GANs). Finally, the scene and dance movements were integrated, and the creative generation process was completed. This paper also proposes the creativity generation coefficient as a means of evaluating the results of the creative process, combined with artificial brain electroenchalographic data to assist in evaluating the degree of agreement between creativity and needs. This paper aims to realize the automation and intelligence of the creative generation process and improve the creative generation effect and usability of dance movements. Experiments show that this paper has significantly improved the efficiency of knowledge retrieval and the accuracy of knowledge acquisition, and can generate unique and practical dance moves. The robot's trajectory is novel and changeable, and can meet the needs of dance performances in different scenes. The creative generation process of dancing robots combined with deep learning and quantum technology is a required field for future development, and could provide a considerable boost to the progress of human society.

scholarly journals Securing IoT Devices: A Robust and Efficient Deep Learning with a Mixed Batch Adversarial Generation Process for CAPTCHA Security Verification

Electronics ◽  
2021 ◽  
Vol 10 (15) ◽  
pp. 1798
Author(s):  
Stephen Dankwa ◽  
Lu Yang
Keyword(s):  
Deep Learning ◽  
Internet Of Things ◽  
Process Model ◽  
Good Practice ◽  
Knowledge Exchange ◽  
Turing Test ◽  
The Internet ◽  
Generation Process ◽  
Adversarial Attack ◽  
Mixed Batch

The Internet of Things environment (e.g., smart phones, smart televisions, and smart watches) ensures that the end user experience is easy, by connecting lives on web services via the internet. Integrating Internet of Things devices poses ethical risks related to data security, privacy, reliability and management, data mining, and knowledge exchange. An adversarial machine learning attack is a good practice to adopt, to strengthen the security of text-based CAPTCHA (Completely Automated Public Turing test to tell Computers and Humans Apart), to withstand against malicious attacks from computer hackers, to protect Internet of Things devices and the end user’s privacy. The goal of this current study is to perform security vulnerability verification on adversarial text-based CAPTCHA, based on attacker–defender scenarios. Therefore, this study proposed computation-efficient deep learning with a mixed batch adversarial generation process model, which attempted to break the transferability attack, and mitigate the problem of catastrophic forgetting in the context of adversarial attack defense. After performing K-fold cross-validation, experimental results showed that the proposed defense model achieved mean accuracies in the range of 82–84% among three gradient-based adversarial attack datasets.

Knowledge Generation in Mid Size Entrepreneurial Firms

2005 ◽  
Vol 9 (4) ◽  
pp. 51-63 ◽  
Author(s):  
Anurag Mishra ◽  
M. Akbar
Keyword(s):  
Process Model ◽  
Case Analysis ◽  
Knowledge Generation ◽  
Generic Model ◽  
Entrepreneurial Firms ◽  
Generation Process ◽  
Knowledge Assets ◽  
Developed Markets ◽  
Knowledge Based ◽  
Line Diagram

Literature on medium sized enterprises (MSEs) is limited both in developed markets and emerging markets. This paper addresses this gap and explores MSEs from a knowledge-based perspective. Grounded in the case based research often MSEs, the paper identifies the knowledge assets employed by highly successful firms. The paper performs a detailed case analysis of three such firms from our sample. We trace the knowledge generation process through a detailed line diagram and based on the case analysis, build a generic model for analyzing the knowledge conversion process in MSEs. The contribution of this work is articulated in the process model that integrates the various classes of knowledge assets in the context of transitional firms in India. The paper also develops a few empirically testable propositions, filling a major gap in existing literature on knowledge management.

scholarly journals Emotion Classification Using a Tensorflow Generative Adversarial Network Implementation

Symmetry ◽  
2018 ◽  
Vol 10 (9) ◽  
pp. 414 ◽  
Author(s):  
Traian Caramihale ◽  
Dan Popescu ◽  
Loretta Ichim
Keyword(s):  
Assisted Living ◽  
Generative Adversarial Networks ◽  
Generation Process ◽  
Emotion Classification ◽  
Generative Adversarial Network ◽  
Adversarial Network ◽  
Testing Dataset ◽  
Behavior Tracking ◽  
Domestic Appliance ◽  
Facial Images

The detection of human emotions has applicability in various domains such as assisted living, health monitoring, domestic appliance control, crowd behavior tracking real time, and emotional security. The paper proposes a new system for emotion classification based on a generative adversarial network (GAN) classifier. The generative adversarial networks have been widely used for generating realistic images, but the classification capabilities have been vaguely exploited. One of the main advantages is that by using the generator, we can extend our testing dataset and add more variety to each of the seven emotion classes we try to identify. Thus, the novelty of our study consists in increasing the number of classes from N to 2N (in the learning phase) by considering real and fake emotions. Facial key points are obtained from real and generated facial images, and vectors connecting them with the facial center of gravity are used by the discriminator to classify the image as one of the 14 classes of interest (real and fake for seven emotions). As another contribution, real images from different emotional classes are used in the generation process unlike the classical GAN approach which generates images from simple noise arrays. By using the proposed method, our system can classify emotions in facial images regardless of gender, race, ethnicity, age and face rotation. An accuracy of 75.2% was obtained on 7000 real images (14,000, also considering the generated images) from multiple combined facial datasets.

The Incremental Commitment Spiral Model for Service-Intensive Projects

2013 ◽  
pp. 94-115
Author(s):  
Supannika Koolmanojwong ◽  
Barry Boehm ◽  
Jo Ann Lane
Keyword(s):  
Web Services ◽  
Process Model ◽  
Software Process ◽  
Business Environment ◽  
Process Models ◽  
Software Systems ◽  
Generation Process ◽  
Software Process Models ◽  
Commercial Off The Shelf ◽  
Spiral Model

To provide better service to customers and remain competitive in the business environment, a wide variety of ready-to-use software and technologies are available for one to “grab and go” in order to build up software systems at a rapid pace. Currently, a wide variety of Web services are available and ready to use for this purpose. Current software process models also support commercial-off-the-shelf (COTS)-based development processes. However, although COTS and Web Services are similar, they are different in many perspectives. On one hand, there are various software process models that support Web services development. Yet there is no process model that supports the project that uses services provided by others. This chapter introduces the Incremental Commitment Spiral Model (ICSM), a new generation process model that provides development guidelines, from exploring a Web service alternative to deployment and maintenance with case studies.

The Incremental Commitment Spiral Model for Service-Intensive Projects

2014 ◽  
pp. 2142-2162 ◽  
Author(s):  
Supannika Koolmanojwong ◽  
Barry Boehm ◽  
Jo Ann Lane
Keyword(s):  
Web Services ◽  
Process Model ◽  
Software Process ◽  
Business Environment ◽  
Process Models ◽  
Software Systems ◽  
Generation Process ◽  
Software Process Models ◽  
Commercial Off The Shelf ◽  
Spiral Model

To provide better service to customers and remain competitive in the business environment, a wide variety of ready-to-use software and technologies are available for one to “grab and go” in order to build up software systems at a rapid pace. Currently, a wide variety of Web services are available and ready to use for this purpose. Current software process models also support commercial-off-the-shelf (COTS)-based development processes. However, although COTS and Web Services are similar, they are different in many perspectives. On one hand, there are various software process models that support Web services development. Yet there is no process model that supports the project that uses services provided by others. This chapter introduces the Incremental Commitment Spiral Model (ICSM), a new generation process model that provides development guidelines, from exploring a Web service alternative to deployment and maintenance with case studies.

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