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2nd international conference on computing innovation and applied physics, conf-ciap 2023

2nd International Conference on Computing Innovation and App...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

The proceedings contain 56 papers. The topics discussed include: the improvements to the minimum curvature race line optimization;a quantitative analysis on the influence of temperature on head loss along PVC pipe and the choice of pipe diameter;computing character tables of symmetric groups using higher order permutation representations;convex optimization and the smallest ball problem;application of generalized Poisson regression for the development of modeling motorcycle accidents based on rider characteristics;congruences and subdirect decompositions in universal algebra;real model for micro swimmer and the study of the relationship between the swimming speed, pitch angle, and rotation rate for the flagellum;and investigation of the negative speed's effect on the base of the Braitenberg vehicle.

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Application of trapped ions in quantum-computing: Fidelity, scalability and integrated technology 2

Application of trapped ions in quantum-computing: Fidelity, ...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Xiaoxiao, Wang Jilin University 2699 Qianjin Dajie Jilin Province Changchun China

Quantum computing, which is based on the rules of quantum mechanics, has great potential in many fields for its theoretical ability to simulate any natural process based on quantum mechanics. Many types of physical implementations of quantum computers have been developed, and the method based on trapped ions is a promising one. However, there is still a lot of work that need to be done, like how to improve the fidelity and scalability of those quantum computers. Besides laser light, microwave and waveguides have also been used in some experiments. © Published under licence by IOP Publishing Ltd.

关键词： Trapped ions

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computing character tables of symmetric groups using higher order permutation representations 2

Computing character tables of symmetric groups using higher ...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Lei, Zikang University of Waterloo 200 University Ave W WaterlooONN2L 3G1 Canada

In this paper, we will introduce the topic of representation theory by focusing on the techniques of computing character tables of finite groups, in particular, the symmetric group Sn. First, we will introduce some basic concepts of representation theory of finite groups over ., . Then we will compute the character tables for S 3 and S 4 using the classical methods introduced in Section 2. Also, we will construct a series of representations for Sn and compute their characters. Finally, we will compute the character tables for S 5 and S 6 using our method introduced in Section 3. © Published under licence by IOP Publishing Ltd.

关键词： Group theory

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On the convergence acceleration of vanilla Generative Adversarial Network 2

On the convergence acceleration of vanilla Generative Advers...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Si, Hang School of Physics Technology University of Wuhan Hubei Wuhan430072 China

Generative Adversarial Network (GAN) is very successful and widely used in both academic and industrial fields. It is inspired by game theory where two models, a generator and a critic, compete with each other, learn from each other, and make each other stronger and stronger. Most improvements focused on stability and there are already many different models such as deep convolutional GAN (DCGAN) and Wassertein GAN (WGAN) that have succeeded. But the speed of the convergence during training process is also an essential ability that needs to be enhanced. In this paper, a decreasing noise is added to the MNIST data and these new data are delivered to the discriminator of the vanilla GAN to accelerate the training process. The result shows that this change could accelerate the convergence and not affect the results' quality a lot. And this improvement should be general enough to apply to the other models. © Published under licence by IOP Publishing Ltd.

关键词： Generative adversarial networks

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Congruences and subdirect decompositions in universal algebra 2

Congruences and subdirect decompositions in universal algebr...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Zhao, Ranran University of Waterloo 200 University Ave W WaterlooONN2L 3G1 Canada

In this paper, we will focus on the topic of congruences and factorizations in universal algebra. We will first provide an introduction to universal algebra by defining lattices, algebras, congruences and other core structures. Next, we will explore the congruence and factorization properties of an algebra. Then, Birkhoff theorem indicates that every algebra can be embedded into a product of subdirectly irreducible algebras. Based on these fundamental concepts, Heyting algebra will be discussed as a typical example in universal algebra. The one-to-one correspondence between filters and congruences of a Heyting algebra will be proved. Lastly, we will show a specific way to justify the subdirectly irreducibility of a Heyting algebra. © Published under licence by IOP Publishing Ltd.

关键词： Algebra

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Research advanced in the visual SLAM methods under indoor environment 2

Research advanced in the visual SLAM methods under indoor en...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Lu, Zhengsheng Wang, Jinchang Zhang, Zelin Zhu, Conghua Virginia Polytechnic Institute and State University 24060 United States Shangqiu Normal University 476000 China Tongji University 201804 China University of Nottingham NG7 2QL United Kingdom

Simultaneous localization and mapping (SLAM) have been a hotspot study topic in the computer vision community these days, which aims to locate the agent's position and perceive the surrounding environment to build a map. In Visual SLAM, the camera is the external sensor used, creating an environment map while locating itself. Compared with radar and other rangefinders, the visual sensor is usually tiny and has low power consumption, which has been the mainstream framework in SLAM research task. This paper starts from the system overview of visual SLAM, introduces the landmark achievements and research hotspots of visual SLAM, and discusses the key issues and three research methods based on visual SLAM in indoor environment. Meanwhile, the applications of visual SLAM in dynamic scenes and large indoor environments are listed. Finally, the trend of its future development is prospected. © Published under licence by IOP Publishing Ltd.

关键词： Indoor positioning systems

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XCovNet: A wide deep learning model for CXR-based COVID-19 detection 2

XCovNet: A wide deep learning model for CXR-based COVID-19 d...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Jana, Aryyama Kumar Paul, Rudrendu Kumar Department of Computer Science School of Computing and Augmented Intelligence Arizona State University TempeAZ United States Information Systems Department Boston University BostonMA United States

The high death toll and economic impact of the COVID-19 pandemic emphasize the need for effective population screening technologies. The high cost, limited availability, and slow nature of CT scans and PCR-based tests renders them impractical for frequent use among the general public. As chest X-ray (CXR) imaging is fast and economical, a high accuracy CXR-based test would be well-suited for such screenings. Deep learning algorithms are widely used to aid medical image diagnoses. We use a collection of state-of-the-art pre-trained deep neural network models with additional layers to detect the COVID-19 cases from a sample of healthy, COVID-19, and pneumonia patients. We observed models trained with concatenated features of multiple pre-trained deep learning architectures outperform the individual and ensemble models. Our final model obtained a recall of greater than 98% and a precision of greater than 95% on two separate datasets. The wide architecture of xCovNet may contribute to its robust behavior, providing a systematic approach to construct a reliable deep learning model for emerging datasets. © Published under licence by IOP Publishing Ltd.

关键词： COVID-19

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Comprehensive study and analysis for StarGAN and StarGAN-v2 in the task of image generation 2

Comprehensive study and analysis for StarGAN and StarGAN-v2 ...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Cai, Yuanan Li, Yepeng Zhang, Zhenyu Department of Computer Engineering Baskin School of Engineering University of California Santa CruzCA95064 United States Department of Cognitive Science University of California - San Diego La Jolla CA92092 United States Department of Information Technology Monash University Wellington Rd ClaytonVIC3800 Australia

With the continuous development of deep learning and artificial intelligence industry, more and more neural networks have been developed. Among them, one typical network widely used is StarGAN. It solves the problem of requiring multiple generators and discriminators for multiple domains and style transitions. In this article, we will analyze and explore StarGAN v1 and StarGAN v2. including StarGAN's development history, advantages and disadvantages in the application, etc. At the same time, we will compare StarGAN with other neural networks such as CycleGAN and MSGAN through some discrimination criteria, and clearly demonstrate the influence of different networks on the generation of image data sets through quantitative and qualitative analysis. In addition, we also found a representative code on some of the actual uses of StarGAN for hair replacement through online sources. Since this code may be used to confuse the use of StarGAN v1 and v2, we will also improve this code in the article and put forward suggestions for changes. In this paper, we carried out the specific analysis of StarGAN's loss function based on the existing data and put forward some relevant insights. By taking the data we searched for StarGAN, it can be found that StarGAN could use as few resources as possible to achieve clearer and more varied results during the image generation task © Published under licence by IOP Publishing Ltd.

关键词： Deep learning

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Approaches to NMR sensitivity enhancement based on theoretical analysis 2

Approaches to NMR sensitivity enhancement based on theoretic...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Du, Meining Department of Physics The University of Hong Kong Hong Kong Hong Kong

Nuclear magnetic resonance (NMR) has been broadly investigated and applied in many industries (e.g., medical treatment, food safety and materials) as a powerful approach to explore the internal structure and composition of substances. However, the need for more sensitivity has been one of the most severe problems hindering the practical application of NMR. This paper suggests various approaches to deal with this defect, from adjusting factors based on the theoretical principle to the progressive hyperpolarization method. Classified by polarization sources, several representative sub-fields of hyperpolarization are further interpreted and analyzed, including Dynamic Nuclear Polarization (DNP), Optical Pumping (OP) and Parahydrogen Induced Polarization (PHIP). Based on the analysis and prospect of the aforementioned feasible methods, the main factors that restrict the sensitivity of NMR will be identified. Moreover, the prospects and new technologies brought by the methods based on different theoretical foundations have been considered to improve these factors and make NMR apply to a broader range of fields. Overall, these results not only indicate the current research status but also shed light on guiding further exploration of methods of enhancing NMR sensitivity and usability. © Published under licence by IOP Publishing Ltd.

关键词： Nuclear magnetic resonance

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CNN combined with data augmentation for face recognition on small dataset 2

CNN combined with data augmentation for face recognition on ...

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2nd international conference on computing innovation and applied physics, conf-ciap 2023

作者： Chen, Siru Department of Electrical and Computer Engineering University of Alberta EdmontonABT6G 2R3 Canada

Faces have universal structures yet contain distinct features among individuals. Recognizing individuals based on their faces has always been a popular topic in pattern recognition, and computer vision and many traditional approaches have yielded satisfying results. In recent years, rapid growth in deep learning has encouraged researchers to use deep learning methods to solve authentication problems. Convolutional neural networks are one of the most popular deep neural networks with multiple layers and the ability to reduce parameters by using kernels to capture features from input. It has outstanding performance in pattern recognition due to its ability to extract features and take images as inputs. In machine learning, data augmentation is a technique to seemingly enlarge a dataset to avoid underfitting or overfitting problems caused by insufficient data. This paper uses convolutional neural networks to solve face recognition problems on a small dataset. It compares performance with traditional face recognition methods such as Principal Component Analysis and examines the impact on performance using data augmentation. Overall, data augmentation boosts the accuracy of the network but also results in an unsteady learning curve. The convolutional neural network performs well on pattern recognition and obtains an accuracy of 94% in an augmented dataset with only two convolutional layers. © Published under licence by IOP Publishing Ltd.

关键词： Face recognition

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