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2024 Latin America Optics and Photonics Conference, LAOP 2024

作者： Lagutchev, Alexei S. Bogdanov, Simeon I. Boltasseva, Alexandra Shalaev, Vladimir M. School of Electrical and Computer Engineering Birck Nanotechnology Center Purdue Quantum Science and Engineering Institute Purdue University West LafayetteIN47907 United States Oak RidgeTN37931 United States Department of Electrical and Computer Engineering Nick Holonyak Jr. Micro and Nanotechnology Laboratory Illinois Quantum Information Science and Technology Center University of Illinois at Urbana-Champaign UrbanaIL60801 United States

We report on a table-top system for characterizing single photon emitter fluorescence lifetimes, spectra, photon correlation and spin properties. Measurements are facilitated by automation and machine learning. ©...

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Vidu4D: single generated video to high-fidelity 4D reconstruction with dynamic Gaussian surfels 24

Vidu4D: single generated video to high-fidelity 4D reconstru...

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Proceedings of the 38th International Conference on Neural information Processing Systems

作者： Yikai Wang Xinzhou Wang Zilong Chen Zhengyi Wang Fuchun Sun Jun Zhu Department of Computer Science and Technology BNRist Center Tsinghua University Department of Computer Science and Technology BNRist Center Tsinghua University and ShengShu and College of Electronic and Information Engineering Tongji University Department of Computer Science and Technology BNRist Center Tsinghua University and ShengShu

ISBN: (纸本)9798331314385

Video generative models are receiving particular attention given their ability to generate realistic and imaginative frames. Besides, these models are also observed to exhibit strong 3D consistency, significantly enhancing their potential to act as world simulators. In this work, we present Vidu4D, a novel reconstruction model that excels in accurately reconstructing 4D (i.e., sequential 3D) representations from single generated videos, addressing challenges associated with non-rigidity and frame distortion. This capability is pivotal for creating high-fidelity virtual contents that maintain both spatial and temporal coherence. At the core of Vidu4D is our proposed Dynamic Gaussian Surfels (DGS) technique. DGS optimizes time-varying warping functions to transform Gaussian surfels (surface elements) from a static state to a dynamically warped state. This transformation enables a precise depiction of motion and deformation over time. To preserve the structural integrity of surface-aligned Gaussian surfels, we design the warped-state geometric regularization based on continuous warping fields for estimating normals. Additionally, we learn refinements on rotation and scaling parameters of Gaussian surfels, which greatly alleviates texture flickering during the warping process and enhances the capture of fine-grained appearance details. Vidu4D also contains a novel initialization state that provides a proper start for the warping fields in DGS. Equipping Vidu4D with an existing video generative model, the overall framework demonstrates high-fidelity text-to-4D generation in both appearance and geometry. Project page: https://***.

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Optimizing Quality of Service Parameters for Optical networks 15

Optimizing Quality of Service Parameters for Optical Network...

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15th International Conference on Computing Communication and networking Technologies, ICCCNT 2024

作者： Khurana, Jatin Jayasree, S. Gupta, Shivangi Gowrishankar, J. Birare, Komal M. Balaji, N.V. Chitkara University Institute of Engineering and Technology Chitkara University Centre for Interdisciplinary Research for Business and Technology Punjab India Prince Shri Venkateshwara Padmavathy Engineering College Department of Science and Humanities Chennai127 India Quantum University Research Center Quantum University India Jain [Deemed to be University School of Engineering and Technology Computer Science Engineering Karnataka Bangalore India Vishwakarma Institute of Information Technology Department of Information Technology Pune India Karpagam Academy of Higher Education Department of Computer Science Coimbatore641021 India

ISBN: (纸本)9798350370249

Optical networks are generally designed to offer best of provider (QoS) guarantees to users, which will deliver provider of the appropriate satisfactory. However, because of availability, capacity, and infrastructure constraints, those QoS parameters might not be without problems optimized. This paper explores exclusive strategies for optimizing the QoS parameters in optical networks. It examines numerous techniques inclusive of community slicing and clever manipulate for improving carrier availability, quit-to-end latency, and quit-to-end throughput. It also investigates a couple of routing strategies, together with redundant packet routing, multipath routing, and dynamic routing, to improve hyperlink and node reliabilities, and common hop-matter. Sooner or later, it discusses the potential of the use of disbursed manipulate algorithms for adjusting various QoS parameters in real-time. The paper draws on a spread of simulation situations to demonstrate the effectiveness of these optimization strategies and algorithms. Common, this paper gives an in-depth examination of the various optimization strategies to be had for boosting satisfactory of provider in optical networks. © 2024 IEEE.

关键词： Examination Manipulate Parameters Provider Reliabilities Throughput

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Deep simulated annealing for the discovery of novel dental anesthetics with local anesthesia and anti-inflammatory properties

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Acta Pharmaceutica Sinica B 2024年第7期14卷 3086-3109页

作者： Yihang Hao Haofan Wang Xianggen Liu Wenrui Gai Shilong Hu Wencheng Liu Zhuang Miao Yu Gan Xianghua Yu Rongjia Shi Yongzhen Tan Ting Kang Ao Hai Yi Zhao Yihang Fu Yaling Tang Ling Ye Jin Liu Xinhua Liang Bowen Ke State Key Laboratory of Oral Diseases and National Clinical Research Center for Oral Diseases West China Hospital of StomatologySichuan UniversityChengdu 610041China College of Computer Science Sichuan UniversityChengdu 610065China Department of Anesthesiology Laboratory of Anesthesia and Critical Care MedicineNational-Local Joint Engineering Research Centre of Translational Medicine of AnesthesiologyFrontiers Science Center for Disease-Related Molecular NetworkWest China HospitalSichuan UniversityChengdu 610041China

Multifunctional therapeutics have emerged as a solution to the constraints imposed by drugs with singular or insufficient therapeutic *** primary challenge is to integrate diverse pharmacophores within a single-molecule *** address this,we introduced DeepSA,a novel edit-based generative framework that utilizes deep simulated annealing for the modification of articaine,a wellknown local *** integrates deep neural networks into metaheuristics,effectively constraining molecular space during compound *** framework employs a sophisticated objective function that accounts for scaffold preservation,anti-inflammatory properties,and covalent *** a sequence of local editing to navigate the molecular space,DeepSA successfully identified AT-17,a derivative exhibiting potent analgesic properties and significant anti-inflammatory activity in various animal *** insights into AT-17 revealed its dual mode of action:selective inhibition of NaV1.7 and 1.8 channels,contributing to its prolonged local anesthetic effects,and suppression of inflammatory mediators via modulation of the NLRP3 inflammasome *** findings not only highlight the efficacy of AT-17 as a multifunctional drug candidate but also highlight the potential of DeepSA in facilitating AI-enhanced drug discovery,particularly within stringent chemical constraints.

关键词： Multifunctional drugs Deep simulated annealing Molecule generation Articaine derivatives AI-enhanced drug discovery

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Research on Data Security and Privacy of Smart Grids

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International Journal of network Security 2024年第5期26卷 901-910页

作者： Hwang, Min-Shiang Chang, Yung-Ling Lin, Ko-Yu Lin, Iuon-Chang Yang, Cheng-Ying Department of Computer Science & Information Engineering Asia University 500 Lioufeng Rd. Wufeng Taichung Taichung41354 Taiwan Fintech and Blockchain Research Center Asia University 500 Lioufeng Rd. Wufeng Taichung Taichung41354 Taiwan The Ph.D. Program in Artificial Intelligence Asia University Taiwan Department of Management Information Systems National Chung Hsing University 500 Lioufeng Rd. Wufeng Taichung Taichung41354 Taiwan Department of Computer Science University of Taipei Taipei Taiwan

Developing a smart grid is a trend nowadays and an indispensable basic necessity of life. In recent years, the electricity demand has risen rapidly due to economic development and quality of life improvement. The power grid in significant cities is unstable due to old equipment, and power outages occur frequently. The smart grid can adjust the grid’s distribution strategy through the consumer’s real-time electricity demand so that the consumer’s electricity consumption data is always transmitted to the grid. Failure to protect the privacy and security of such information will expose consumers’ habits and even make the grid unnecessarily wasteful. The smart grid’s abnormality detection efficiency determines the overall grid’s stability. Failure to detect anomalies or power theft in the grid promptly will not only lead to the selection of the wrong distribution strategy for the smart grid but also reduce the transmission efficiency of the grid. This research ensures the privacy and security of transmitted data to enhance the efficiency of abnormality detection in the smart grid. The research issues are divided into privacy of transmitted data, data security authentication, and anomaly detection efficiency. © (2024), (International Journal of network Security). All rights reserved.

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Automated Fruit Classification Based on Deep Learning Utilizing Yolov8 10

Automated Fruit Classification Based on Deep Learning Utiliz...

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10th IEEE Uttar Pradesh Section International Conference on Electrical, Electronics and computer engineering, UPCON 2023

作者： Dewi, Christine Kamlasi, Oksam M Chhabra, Gunjan Dai, Guowei Kaushik, Keshav Khan, Inam Ullah Satya Wacana Christian University Department of Information Technology Salatiga Indonesia Graphic Era Hill University Department of Computer Science and Engineering Dehradun India Agricultural Information Institute of Caas National Agriculture Science Data Center Beijing China School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun India Seas Isra University Department of Electronic Engineering Campus Islamabad Pakistan

ISBN: (纸本)9798350382471

The act of fruit identification entails the discernment and classification of various fruit varieties, predicated upon their visual attributes. This task can be accomplished through various methods, including manual inspection, traditional computer vision techniques, and more advanced approaches using machine learning and deep learning. Our work recognized 15 types of fruit. Our experiment used the fruit imagery dataset, consisting of class Avocado, Banana, Cherry, Apple Braeburn, Apple golden 1, Apricot, Grape, Kiwi, Mango, Orange, Papaya, Peach, Pineapple, Pomegranate and Strawberry. Yolov8 is one of the most popular learning models in the field of object detection. Convolutional neural networks (CNNs), thus simultaneously predicting multiple bounding boxes and probability classes from these bounding boxes. Yolov8 trains the entire image and directly optimizes detection performance, modeled as a Convolutional neural network (CNN). The percentage of detection of test results using *** for each of the 15 categories of fruit images with the average accuracy above is 0.97%, so it can be said to be quite good. After collecting data, Train training and system design implementation of Val Test Convolutional neural networks (CNN) algorithms enabled machine learning and were successfully detected using yolov8n. During the experimental process, we employ 100 epochs with the use of Google Collaboratory. Google Collaboratory has provided GPUs up to 12GB, making it easier and speeding up the fruit detection process. © 2023 IEEE.

关键词： Classification Convolutional Neural network(CNN) Google Collaboratory YOLOv8

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Enhancing python learning with PyTutor: Efficacy of a ChatGPT-Based intelligent tutoring system in programming education

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computers and Education: Artificial Intelligence 2024年 7卷

作者： Yang, Albert C.M. Lin, Ji-Yang Lin, Cheng-Yan Ogata, Hiroaki Department of Computer Science and Engineering National Chung Hsing University Taiwan Department of Computer Science and Information Engineering National Central University Taiwan Academic Center for Computing and Media Studies Kyoto University Japan

Programming is regarded as a focal point in the current rapidly evolving educational landscape. To aid learning in this domain, we developed PyTutor, an innovative intelligent tutoring system (ITS) that is designed to assist beginners in Python programming. PyTutor utilizes the ChatGPT model to offer continuous guidance, problem-solving hints, and detailed code explanations. It features a structured hint system for each question, covering pseudocode, cloze, basic, and advanced coding solutions. In our 11-week experiment, we compared 35 students who used PyTutor with 36 students who did not. The results indicated the effectiveness of PyTutor, particularly for students with weak foundations in programming. Those with lower initial knowledge exhibited higher engagement, completion rates, and success rates in in-class and after-class programming exercises. Nevertheless, we observed a potential risk of overreliance on PyTutor among students, which may impede the development of independent problem-solving skills. Thus, we recommend the balanced usage of PyTutor. In conclusion, PyTutor is a valuable ITS in programming education that considerably improves the learning outcomes of beginners. Its tailored approach renders it a promising tool for bridging knowledge gaps and enhancing overall educational experiences in the field of programming. © 2024 The Authors

关键词： Contrastive Learning

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Fuzzy Neural network Sliding-Mode Control with Actor-Critic for a Class of Robot Systems 10

Fuzzy Neural Network Sliding-Mode Control with Actor-Critic ...

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10th International Conference on Orange Technology, ICOT 2022

作者： Hung, Lon-Chen Wei, Chun-Cheng Chen, Hung-Jen Yang, Chih-Fu Cheng, Wei-Min Lunghwa University of Science and Technology Department of Electronic Engineering Taiwan School of Software and Big Data Changzhou College of Information Technology China Lunghwa University of Science and Technology Department of Computer Information and Network Engineering China

ISBN: (纸本)9781665454193

In this article, a robust fuzzy RBF neural network sliding-mode control with actor-critic for a class of robot systems. Trajectory tracking control of robotic systems has favorable performance for tracking control. The fuzzy RBF neural network sliding-mode and actor-critic method is handled to compensate the uncertainty and disturbance of system. The stability analysis is based on for the proposed adaptive and robust control method. The simulation results show the effectiveness under the uncertainties. © 2022 IEEE.

关键词： Sliding mode control

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Inverse Scattering of Two-dimensional Circular Cylindrical Conductors by Convolutional Neural network

Inverse Scattering of Two-dimensional Circular Cylindrical C...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Po-Hsiang Chen Hsiu-Hui Hsu Chien-Ching Chiu Wei Chien Kai-Xu Yu Department of Electrical and Computer Engineering Tamkang University New Taipei City Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan City Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

We used a Convolutional Neural network (CNN) to reconstruct the electromagnetic imaging of a perfect conductor in half-space through the traverse magnetic wave. Since the conventional iterative algorithm is time-consuming, we developed a real-time electromagnetic imaging technique to apply to the CNN to reconstruct the half-space conducting cylinders. The sizes and positions of the cylinders were calculated through the Direct Sampling Method (DSM) in the scattered field. The original ground truth was fed to CNN for training to predict accurate sizes and positions of the shape. The accurate size and position of the shape for the perfect conductor were reconstructed.

关键词： Magnetic field measurement Accuracy Shape Magnetic resonance imaging Two-dimensional displays Conductors Sampling methods

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Computational Modelling of Plurality and Definiteness in Chinese Noun Phrases 30

Computational Modelling of Plurality and Definiteness in Chi...

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Liu, Yuqi Chen, Guanyi van Deemter, Kees Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning National Language Resources Monitoring and Research Center for Network Media School of Computer Science Central China Normal University China Department of Information and Computing Sciences Utrecht University Netherlands

ISBN: (纸本)9782493814104

Theoretical linguists have suggested that some languages (e.g., Chinese and Japanese) are "cooler" than other languages based on the observation that the intended meaning of phrases in these languages depends more on their contexts. As a result, many expressions in these languages are shortened, and their meaning is inferred from the context. In this paper, we focus on the omission of the plurality and definiteness markers in Chinese noun phrases (NPs) to investigate the predictability of their intended meaning given the contexts. To this end, we built a corpus of Chinese NPs, each of which is accompanied by its corresponding context, and by labels indicating its singularity/plurality and definiteness/indefiniteness. We carried out corpus assessments and analyses. The results suggest that Chinese speakers indeed drop plurality and definiteness markers very frequently. Building on the corpus, we train a bank of computational models using both classic machine learning models and state-of-the-art pre-trained language models to predict the plurality and definiteness of each NP. We report on the performance of these models and analyse their behaviours. The code and data used in this paper are available at: https://***/andyzxq/chinese_np_def. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： Computational linguistics

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