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arXiv 2023年

作者： Pei, Qizhi Gao, Kaiyuan Wu, Lijun Zhu, Jinhua Xia, Yingce Xie, Shufang Qin, Tao He, Kun Liu, Tie-Yan Yan, Rui Gaoling School of Artificial Intelligence Renmin University of China China School of Computer Science and Technology Huazhong University of Science and Technology China Microsoft Research AI4Science China School of Information Science and Technology University of Science and Technology of China China Engineering Research Center of Next-Generation Intelligent Search and Recommendation Ministry of Education China Beijing Key Laboratory of Big Data Management and Analysis Methods China

Modeling the interaction between proteins and ligands and accurately predicting their binding structures is a critical yet challenging task in drug discovery. Recent advancements in deep learning have shown promise in addressing this challenge, with sampling-based and regression-based methods emerging as two prominent approaches. However, these methods have notable limitations. Sampling-based methods often suffer from low efficiency due to the need for generating multiple candidate structures for selection. On the other hand, regression-based methods offer fast predictions but may experience decreased accuracy. Additionally, the variation in protein sizes often requires external modules for selecting suitable binding pockets, further impacting efficiency. In this work, we propose FABind, an end-to-end model that combines pocket prediction and docking to achieve accurate and fast protein-ligand binding. FABind incorporates a unique ligand-informed pocket prediction module, which is also leveraged for docking pose estimation. The model further enhances the docking process by incrementally integrating the predicted pocket to optimize protein-ligand binding, reducing discrepancies between training and inference. Through extensive experiments on benchmark datasets, our proposed FABind demonstrates strong advantages in terms of effectiveness and efficiency compared to existing methods. Our code is available at Github3 Copyright © 2023, The Authors. All rights reserved.

关键词： Ligands

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A Mixed Approach for Pallet Building Problem with Practical Constraints 22nd

A Mixed Approach for Pallet Building Problem with Practical ...

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22nd International Conference on Enterprise Information Systems, ICEIS 2020

作者： Iori, Manuel Locatelli, Marco Moreira, Mayron C. O. Silveira, Tiago Department of Sciences and Methods for Engineering University of Modena and Reggio Emilia Reggio Emilia Italy Department of Engineering and Architecture University of Parma Parma Italy Department of Computer Science Federal University of Lavras Lavras Brazil

ISBN: (纸本)9783030754174

We study a pallet building problem that originates from a case study in a company that produces robotized systems for freight transportation and logistics. We generalize the problem by including the concept of family of items, which allows us to consider specific constraints such as visibility and contiguity. We solve the problem with an algorithm based on a two-step strategy: an Extreme Points heuristic is used to group items into horizontal layers and an exact method is invoked to stack layers one over the other to form pallets. The performance of the algorithm is assessed through extensive computational tests on real-world instances. The results show that the exact model considerably increases the solution quality, creating very compact packings with a limited computational effort. © 2021, Springer Nature Switzerland AG.

关键词： Pallets

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Scenario Approach for Parametric Markov Models

arXiv

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arXiv 2023年

作者： Liu, Ying Turrini, Andrea Hahn, Moritz Xue, Bai Zhang, Lijun State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences China University of Chinese Academy of Sciences China Institute of Intelligent Software Guangzhou China Formal Methods and Tools University of Twente Enschede Netherlands

In this paper, we propose an approximating framework for analyzing parametric Markov models. Instead of computing complex rational functions encoding the reachability probability and the reward values of the parametric model, we exploit the scenario approach to synthesize a relatively simple polynomial approximation. The approximation is probably approximately correct (PAC), meaning that with high confidence, the approximating function is close to the actual function with an allowable error. With the PAC approximations, one can check properties of the parametric Markov models. We show that the scenario approach can also be used to check PRCTL properties directly – without synthesizing the polynomial at first hand. We have implemented our algorithm in a prototype tool and conducted thorough experiments. The experimental results demonstrate that our tool is able to compute polynomials for more benchmarks than state-of-the-art tools such as PRISM and Storm, confirming the efficacy of our PAC-based synthesis. © 2023, CC BY.

关键词： Polynomial approximation

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A C0FINITE ELEMENT ALGORITHM FOR THE SIXTH ORDER PROBLEM WITH SIMPLY SUPPORTED BOUNDARY CONDITIONS

arXiv

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arXiv 2023年

作者： Li, Hengguang Yin, Peimeng Wayne State University Department of Mathematics DetroitMI48202 United States Multiscale Methods and Dynamics Group Computer Science and Mathematics Division Oak Ridge National Laboratory Oak RidgeTN37831 United States

In this paper, we study the sixth order equation with the simply supported boundary conditions in a polygonal domain. We propose a new mixed formulation that decomposes the sixth order problem into a system of Poisson equations. Depending on the interior angles of the domain, additional Poisson problems may be needed to confine the solution to the correct Sobolev space. In addition, we propose a C0finite element algorithm for the sixth order problem and provide the optimal error analysis. Numerical results are reported to verify the theoretical findings. © 2023, CC BY-NC-ND.

关键词： Boundary conditions

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Mixture of Knowledge Minigraph Agents for Literature Review Generation

arXiv

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arXiv 2024年

作者： Zhang, Zhi Liu, Yan Zhong, Sheng-Hua Chen, Gong Yang, Yu Cao, Jiannong The Hong Kong Polytechnic University the Department of Computing 999077 Hong Kong Shenzhen University the College of Computer Science and Software Engineering Guangdong Shenzhen518052 China The Education University of Hong Kong Centre for Learning Teaching and Technology 999077 Hong Kong

Literature reviews play a crucial role in scientific research for understanding the current state of research, identifying gaps, and guiding future studies on specific topics. However, the process of conducting a comprehensive literature review is yet time-consuming. This paper proposes a novel framework, collaborative knowledge minigraph agents (CKMAs), to automate scholarly literature reviews. A novel prompt-based algorithm, the knowledge minigraph construction agent (KMCA), is designed to identify relations between concepts from academic literature and automatically constructs knowledge minigraphs. By leveraging the capabilities of large language models on constructed knowledge minigraphs, the multiple path summarization agent (MPSA) efficiently organizes concepts and relations from different viewpoints to generate literature review paragraphs. We evaluate CKMAs on three benchmark datasets. Experimental results show the effectiveness of the proposed method, further revealing promising applications of LLMs in scientific research. © 2024, CC BY.

关键词： Reviews

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Enhancing Password Security: Analyzing Password Management Practices Among IT Students

Enhancing Password Security: Analyzing Password Management P...

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International IEEE Conference and Workshop: Óbuda on Electrical and Power Engineering (CANDO-EPE)

作者： Anita Mihalovicsne Kollar Jozsef Katona Department of Software Development and Application Institute of Computer Engineering University of Dunaujvaros Dunaujvaros Hungary Institute of Electronics and Communication Systems Kando Kalman Faculty of Electrical Engineering Obuda University Budapest Hungary GAMF Faculty of Engineering and Computer Science John Von Neumann University Kecskemet Hungary Department of Applied Quantitative Methods Faculty of Finance and Accountancy Budapest Business University Budapest Hungary

ISBN: (数字)9798331531119

ISBN: (纸本)9798331531126

Today, with the digital world in its full swing, strong password management is key to protecting sensitive information from both internal and external threats. The current research explores the passwords managing behavior of the IT students at the University of Dunaujvaros. A survey made in May 2024 questioned 68 students, 59 males and 9 females, about behaviors such as using passwords with complexity, not repeating them for multiple accounts or machines, changing them regularly, and which applications they use for password management. The findings have depicted that, as a whole, students appear to be moderately sensitive about the password security instructions. Nonetheless, most continue to indulge in unsafe practices, including easily remembered or weak passwords and infrequent password changes. Furthermore, approximately half of the responders use password management applications, indicating room for significant improvement in the future. The results suggest that intervention and special education measures should be taken to enhance the practice of password security among future IT experts. This research has good potential to contribute toward strategies designed for people behaving safely in password management, and hence promote a secure digital environment.

关键词： Surveys Continuing education Power engineering Correlation Engineering profession Education Passwords Complexity theory Security Protection

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AI and IoT in Smart Cities: A Methodology, Transformation, and Challenges 8th

AI and IoT in Smart Cities: A Methodology, Transformation, a...

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8th International Conference on Information System Design and Intelligent Applications, ISDIA 2024

作者： Begishev, Ildar Isavnin, Alexey Nedelkin, Alexey Lydia, E. Laxmi Kumar, K. Vijaya Doctor of Law Institute of Digital Technologies and Law Department of Criminal Law and Procedure Kazan Innovative University named after V. G. Timiryasov Kazan Russia Doctor of Physical-Mathematical Sciences Department of Business-Informatics and Mathematical Methods in Economics Kazan Federal University Naberezhnye Chelny Institute KFU Naberezhnye Chelny Russia Department of Computer Science Plekhanov Russian University of Economics Moscow Russia Vijayawada520007 India GITAM School of Technology Visakhapatnam Campus Visakhapatnam India

ISBN: (纸本)9789819748945

The Internet of Things (IoT) with smart cities and smart homes enables us to progressively sense and alter our surroundings. However, Artificial Intelligence (AI) must leverage such distinguishing abilities and detected data. We are heading in that way with sophisticated IoT technologies. As connected items become more authoritative, we are seeing a smart city movement away from cloud-based IoT systems and toward edge AI and embedded AI. Lower latency, better privacy, and the necessity to process data close to the source have all influenced this decision. According to a current report, smart cities can have 70 billion linked things by 2023. These cities will become smarter as a result of these networked things and introduce hazards and privacy concerns. As a result of the numerous smart city initiatives and plans that have been implemented in current years, we will not only see the anticipated aids but also the hazards that have been presented. The present and future movements in smart cities and IoT are discussed. This chapter provides an overview of several smart city techniques and elements that can be or are now automated with the help of the Internet of Things (IoT), and Artificial Intelligence (AI). Novel components of smart cities of smart parking and smart governance are determined through Artificial Intelligence (AI) in the Internet of Things (IoT). Finally, the IoT's flaws and solutions in the context of smart cities are determined. This work focuses on identifying the transformation and challenges faced in developing a smart city in AI. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Artificial intelligence (AI) Challenges Internet of things (IoT) Smart cities Transformation

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Automatic Calculation of Loss Rate of Cotton Pickers Based on Deep Neural Network and Image Processing 5

Automatic Calculation of Loss Rate of Cotton Pickers Based o...

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5th International Conference on Machine Learning and Machine Intelligence, MLMI 2022

作者： Tian, Jialue Qian, Zhongmin Xie, Qing Sun, Yongfei Shi, Lei College of Computer Science and Technology Nanjing University of Aeronautics and Astronautics China Fundamental Experiment Teaching Department Nanjing University of Aeronautics and Astronautics China Key Laboratory of Modern Agricultural Equipment Ministry of Agriculture and Rural Affairs China Nanjing Institute of Agricultural Mechanization Ministry of Agriculture and Rural Affairs China

ISBN: (纸本)9781450397551

The loss rate of cotton pickers is an important indicator to measure the quality of cotton pickers, which is directly the vital interests of cotton farmers. To obtain the loss rate of cotton pickers in real-time, this paper takes the cotton field images after a cotton picker harvesting as the research object, combines the deep learning method and image processing technology, and proposes a method for calculating the loss rate of cotton pickers. First, nearly 5,000 ha-rvested cotton field images were collected manually to establish a data set. Then a lightweight Yolov5s neural network model was constructed to detect the cotton areas in the image and obtain the regions of interest (ROI). After that, each ROI was processed by binarization, dilation, erosion, and masking to obtain a more accurate cotton area, which excludes cotton husks, branches, and leaves in the entire image. Finally, a convolutional neural network was used to build a regression model to calculate the cotton loss rate for the whole image. The experimental results show that: 1) The constructed lightweight Yolov5s model can detect cotton areas at a speed of 43 frames per second and an average accuracy of 84.8%, which meets the needs of cotton pickers. 2) For the calculation of the image cotton loss rate, the difference between the calculated loss rate and the actual loss rate is less than 1% for 90% of the images;only 1.1% of the images have a difference greater than 2%, and the maximum difference does not exceed 3%. Therefore, the method proposed in this paper can realize the real-time calculation of the loss rate of cotton pickers. © 2022 ACM.

关键词： Cotton

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Micro-Doppler Analysis of Target Based on the Clustering Prior to Solve the Block Sparse Forward and Backward TVAR Model

Micro-Doppler Analysis of Target Based on the Clustering Pri...

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2021 CIE International Conference on Radar, Radar 2021

作者： Jin, Shuojing Hong, Ling Dai, Fengzhou Xidian University National Laboratory of Radar Signal Processing Xi'an China Key Laboratory of Modern Teaching Technology Ministry of Education School of Computer Science Shaanxi Normal University Xi'an China

ISBN: (纸本)9781665498142

Micro-Doppler features generated by target micromotion are usually unique and can be used as an important basis for target recognition, which reflects the fine features of target. In this paper, we propose an algorithm based on cluster-structured prior to solve block sparse forward and backward time-varying autoregressive (TVAR) model to perform Micro-Doppler analysis of the target. Firstly, convert the time-varying coefficients into the form of time-invariant coefficients. Then, an improved algorithm based on extended block sparse Bayesian learning (EBSBL) is used to solve the time-invariant block sparse coefficients by adopting a cluster-structured prior. At the same time, the priori information with known boundary is applied. Finally, the electromagnetic simulation results show that the proposed algorithm has advantages in Micro-Doppler analysis, which can not only give a clearer TF diagram than traditional methods, but also has a strong anti-noise performance. © 2021 IEEE.

关键词： block sparsity cluster-structured prior EBSBL forward and backward TVAR model Micro-Doppler feature

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Leveraging Artificial Intelligence in Online Educational Platforms to Enhance Continuous Professional Development in the teaching Profession

Leveraging Artificial Intelligence in Online Educational Pla...

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International Conference on Computational and Characterization Techniques in Engineering & sciences (CCTES)

作者： Khujakulov Sherzod Amankulovich Mannabov Javlon Tokhirovich Kadirov Tulkin Bakhridinovich Taylakov Umid Kuvandikovich Christo Ananth T. Ananth Kumar Senior Teacher of the the Samarkand Regional National Center for Training Teachers in New Methods Teacher of the Samarkand Regional National Center for Training Teachers in New Methods (PhD) Samarkand Agroinnovations and Research University Department of Electronics and Communication Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Avadi Uzbekistan&Adjunct Faculty Samarkand State University Chennai India Computer Science and Engineering IFET College of Engineering Tamilnadu India

ISBN: (数字)9798350364699

ISBN: (纸本)9798350364705

To keep up with the dynamic nature of the modern classroom, teachers must have access to online learning platforms for professional development purposes. This investigation looks at how these platforms can be used to improve teachers' skills, make information sharing easier, and open doors to CPD opportunities. This study examines the relationship between online resources and methods to demonstrate how digital tools have an impact on teacher training and professional development by leveraging AI. It also draws attention to the fact that these platforms are helping with information-methodological support for teachers as well as the ongoing reforms in our nation. Incorporating empirical observations and case studies, the analysis demonstrates how effective online platforms are in fostering a collaborative and innovative environment for professional learning. Digital transformation has the potential to radically alter how teachers obtain professional development, and this study emphasizes that fact. This will enable teachers to effectively address the demands of modern classrooms.

关键词： Training Digital transformation Information sharing Focusing Collaboration Artificial intelligence

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