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2022 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2022

作者： Das, Supantha Hazra, Arnab Pati, Soumen Kumar Ghosh, Soumadip Mallik, Saurav Banerjee, Suharta Mukherji, Ayan Li, Aimin Zhao, Zhongming Academy of Technology Hooghly Department of Information Technology West Bengal India Future Institute of Technology Kolkata Department of Computer Science and Engineering West Bengal India Maulana Abul Kalam Azad University of Technology West Bengal Haringhata Department of Bioinformatics West Bengal Nadia India Sister Nivedita University Department of Computer Science and Engineering West BengalNew Town Kolkata India Harvard T H Chan School of Public Health Department of Environmental Health BostonMA United States Meghnad Saha of Institute of Technology Department of Computer Science and Engineering West Bengal Kolkata India Pailan College of Management & Technology Department of Computer Science and Engineering West Bengal Kolkata India Xi'an University of Technology School of Computer Science & Engineering Shaanxi Xi'an710048 China The University of Texas Health Science Center Center for Precision Health School of Biomedical Informatics HoustonTX77030 United States

ISBN: (纸本)9781665468190

Chronic kidney disease (CKD) is as severe as cancer in today s world. It may even lead to the permanent failure of kidney. The initial detection of this disease is needed for timely cure. Our work presents a classifier (named ANFIS) in accordance with the notion of neuro-fuzzy in order to detect the existence of chronic kidney disease. We use blood test results of several patients for our research study. We compare our proposed classifier with some conventional classifiers such as Multi-layer Perceptron, Support Vector Machine, Logistic Regression and Decision Tree. Experimental results indicates that our proposed neuro-fuzzy rule-based classifier performs better than the other classifiers used here. ANFIS has given 3% to 4% better accuracy compared to the other classifiers. © 2022 IEEE.

关键词： Decision trees

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Design of Digital Image Encryption Scheme with Cryptographic Analysis 3

Design of Digital Image Encryption Scheme with Cryptographic...

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3rd International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency, SUMMA 2021

作者： Kordov, Krasimir Zhelezov, Stanimir Nachev, Atanas Gueorguiev, Nikolay Pavlova, Daniela Konstantin Preslavsky University of Shumen Dept. of Computer Informatics Shumen Bulgaria University of Library Studies and Information Technologies Sofia Bulgaria Institute of Metal Science Equipment and Technology with Hydroaerodynamic Center Bulgarian Academy of Sciences Sofia Bulgaria

ISBN: (纸本)9781665439817

In this paper a new cryptographic algorithm, de-signed for digital image encryption is proposed. The encryption scheme is based on two chaotic maps, combined for constructing a pseudorandom generator. Using the chaotic behavior of the pseudorandom generator, permutation and substitution operations are performed for completing the encryption process. For proving the security of the cryptographic scheme, an extensive cryptographic analysis is performed including statistical tests for randomness, key-space analysis, key sensitivity, visual analysis, histogram analysis, correlation analysis, entropy analysis, number of pixels change rate and encryption/decryption key sensitivity analysis. The results from empirical experiments are presented in this paper. © 2021 IEEE.

关键词： Cryptography

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Temporal Multi-Agent’s Logic, Knowledge, Uncertainty, and Plausibility 15th

Temporal Multi-Agent’s Logic, Knowledge, Uncertainty, and P...

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15th International KES Conference on Agent and Multi-Agent Systems-Technologies and Applications, KES-AMSTA 2021

作者： Rybakov, Vladimir Institute of Mathematics and Computer Science Siberian Federal University Svobodny Pr. Krasnoyarsk660041 Russia A.P. Ershov Institute of Informatics Systems SB RAS Academy Lavrentjev pr. 6 Novosibirsk630090 Russia

ISBN: (纸本)9789811629938

The paper studies temporal logic implementing multi-agent’s approach and formalizing knowledge and uncertainty. We consider non-transitive linear time and multi-valued models—the ones using separate valuations Vj for the agent’s knowledge of facts and summarized (agreed) valuation together with rules for computation truth values for compound formulas. The basic mathematical problems we study here are decidability and decidability w.r.t. admissible rules. First, we study the general case—the logic with non-uniform intransitivity—and solve its decidability problem. Also, we consider a modification of this logic—temporal logic with uniform non-transitivity—and solve the problem of recognizing admissibility in this logic. The conclusion contains a discussion and a list of open problems. © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Temporal logic

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NeRF-Editing: Geometry Editing of Neural Radiance Fields

arXiv

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arXiv 2022年

作者： Yuan, Yu-Jie Sun, Yang-Tian Lai, Yu-Kun Ma, Yuewen Jia, Rongfei Gao, Lin Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences China School of Computer and Control Engineering University of Chinese Academy of Sciences China School of Computer Science & Informatics Cardiff University United Kingdom Alibaba Group China

Implicit neural rendering, especially Neural Radiance Field (NeRF), has shown great potential in novel view synthesis of a scene. However, current NeRF-based methods cannot enable users to perform user-controlled shape deformation in the scene. While existing works have proposed some approaches to modify the radiance field according to the user's constraints, the modification is limited to color editing or object translation and rotation. In this paper, we propose a method that allows users to perform controllable shape deformation on the implicit representation of the scene, and synthesizes the novel view images of the edited scene without re-training the network. Specifically, we establish a correspondence between the extracted explicit mesh representation and the implicit neural representation of the target scene. Users can first utilize well-developed mesh-based deformation methods to deform the mesh representation of the scene. Our method then utilizes user edits from the mesh representation to bend the camera rays by introducing a tetrahedra mesh as a proxy, obtaining the rendering results of the edited scene. Extensive experiments demonstrate that our framework can achieve ideal editing results not only on synthetic data, but also on real scenes captured by users. Copyright © 2022, The Authors. All rights reserved.

关键词： Mesh generation

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Development of a Calibration-Free Brain-computer Interface Utilizing Common Spatial Patterns and Artificial Neural Networks for EEG Signal Analysis

Development of a Calibration-Free Brain-Computer Interface U...

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Human-computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Korhan Cengiz Shreyas J Udayaprasad P K Gururaj H L Dilip Kumar S M College of Information Technology University of Fujairah UAE Faculty of Organization and Informatics University of Zagreb Croatia Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal Karnataka India Department of Artificial Intelligence & Machine Learning Global Academy of Technology Bengaluru India Dept. of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore India

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

A brain computer interface (BCI) system uses a technique known calibration, that takes 20 to 30 minutes to accomplish. For the objective of creating a reliable decoder, the calibration process is challenging and expensive. In order to address the drawbacks of the current system, a spectral-spatial technique has been suggested. The motor imagery (MI) data set, comprising 15 electroencephalography (EEG) signals and fourteen test subjects, is taken into consideration. The two modules are designed to extract characteristics and process data. An artificial neural network (ANN) is used to independently train and test the suggested spectral-spatial algorithm. Based on it, a variety of machine learning techniques, including random forest (RF), neural networks (NN), and XGboost, are used to classify the data, that is then sent to the hidden layer (Lth layer). The obtained results indicates 2% of improvement in comparison with existing methodology.

关键词： Training Machine learning algorithms Artificial neural networks Electroencephalography Brain-computer interfaces Calibration Reliability

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Advances in RNA secondary structure prediction and RNA modifications: Methods, data, and applications

arXiv

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arXiv 2025年

作者： Yang, Shu Pham, Nhat Truong Li, Ziyang Baik, Jae Young Lee, Joseph Zhai, Tianhua Yu, Weicheng Hou, Bojian Shang, Tianqi He, Weiqing Duong-Tran, Duy Naik, Mayur Shen, Li Dept. of Biostatistics Epidemiology and Informatics University of Pennsylvania Philadelphia United States Dept. of Integrative Biotechnology Sungkyunkwan University Suwon Korea Republic of Dept. of Computer and Information Science University of Pennsylvania Philadelphia United States Dept. of Mathematics United States Naval Academy Annapolis United States

Due to the hierarchical organization of RNA structures and their pivotal roles in fulfilling RNA functions, the formation of RNA secondary structure critically influences many biological processes and has thus been a crucial research topic. This review sets out to explore the computational prediction of RNA secondary structure and its connections to RNA modifications, which have emerged as an active domain in recent years. We first examine the progression of RNA secondary structure prediction methodology, focusing on a set of representative works categorized into thermodynamic, comparative, machine learning, and hybrid approaches. Next, we survey the advances in RNA modifications and computational methods for identifying RNA modifications, focusing on the prominent modification types. Subsequently, we highlight the interplay between RNA modifications and secondary structures, emphasizing how modifications such as m6A dynamically affect RNA folding and vice versa. In addition, we also review relevant data sources and provide a discussion of current challenges and opportunities in the field. Ultimately, we hope our review will be able to serve as a cornerstone to aid in the development of innovative methods for this emerging topic and foster therapeutic applications in the future. Copyright © 2025, The Authors. All rights reserved.

关键词： Prediction models

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Wireless sensor network to connect isolated nodes using link assessment technique 3

Wireless sensor network to connect isolated nodes using link...

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3rd International Conference on Intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021

作者： Sundaram, B. Barani Pandey, Amit Abiko, Aschalew Tirulo Vijaykumar, Janga Genale, Adola Haile Karthika, P. Bule Hora University College of Informatics Bule hora Ethiopia College of Informatics CSI Executive Member CSRSCD BHU Ethiopia Wachemo University School of Computing and Informatics Hosana Ethiopia Bule Hora University College of Informatics Dept. of Information Technology Bule Hora Ethiopia Bule Hora University Department of Information Science Bule hora Ethiopia Kalasalingam Academy of Research and Education Department of Computer Applications Krishnankoil India

ISBN: (纸本)9780738111834

A simultaneous geography control effort is implemented for full-reachability systems and a genetic algorithm with dynamic transformation to find the breakthrough in a blaze-scene. The proposed scheme efficiently takes care of the issue of separate node for transmission run. The suggested technique makes it possible to improve the display of the genetic algorithm in order to maintain a strategic distance from the possible arrangements which fall into nearby ideal. Different experimental simulations have to be confirmed the performance quality, reliability and timeliness of designed approaches. In the Wireless Sensor established network, can connect at least two sensors in a network sensors and deliver jointly via the obtained transmission extend to form the network of total accessibility. Accordingly, excellent blaze exhaust system with complete network accessibility the proposed approaches in this paper established topology and real-time routing methods. This device supports the protection and security of individuals in a blaze scene. © 2021 IEEE.

关键词： Network topology

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CURRICULUM REINFORCEMENT LEARNING FOR QUANTUM ARCHITECTURE SEARCH UNDER HARDWARE ERRORS

arXiv

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arXiv 2024年

作者： Patel, Yash J. Kundu, Akash Ostaszewski, Mateusz Bonet-Monroig, Xavier Dunjko, Vedran Danaci, Onur Applied Quantum Algorithms Leiden University Netherlands Institute of Theoretical and Applied Informatics Polish Academy of Sciences Poland Joint Doctoral School Silesian University of Technology Poland Warsaw University of Technology Institute of Computer Science Poland Lorentz Institute Leiden University Netherlands LIACS Leiden University Netherlands

The key challenge in the noisy intermediate-scale quantum era is finding useful circuits compatible with current device limitations. Variational quantum algorithms (VQAs) offer a potential solution by fixing the circuit architecture and optimizing individual gate parameters in an external loop. However, parameter optimization can become intractable, and the overall performance of the algorithm depends heavily on the initially chosen circuit architecture. Several quantum architecture search (QAS) algorithms have been developed to design useful circuit architectures automatically. In the case of parameter optimization alone, noise effects have been observed to dramatically influence the performance of the optimizer and final outcomes, which is a key line of study. However, the effects of noise on the architecture search, which could be just as critical, are poorly understood. This work addresses this gap by introducing a curriculum-based reinforcement learning QAS (CRLQAS) algorithm designed to tackle challenges in realistic VQA deployment. The algorithm incorporates (i) a 3D architecture encoding and restrictions on environment dynamics to explore the search space of possible circuits efficiently, (ii) an episode halting scheme to steer the agent to find shorter circuits, and (iii) a novel variant of simultaneous perturbation stochastic approximation as an optimizer for faster convergence. To facilitate studies, we developed an optimized simulator for our algorithm, significantly improving computational efficiency in simulating noisy quantum circuits by employing the Pauli-transfer matrix formalism in the Pauli-Liouville basis. Numerical experiments focusing on quantum chemistry tasks demonstrate that CRLQAS outperforms existing QAS algorithms across several metrics in both noiseless and noisy environments. © 2024, CC BY.

关键词： Curricula

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Enhancing Acceptance of Automated Vehicles Through Gamification: Insights from a Driving Simulator Study

SSRN

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SSRN 2025年

作者： Li, Chenchang Yin, Rao Yang, Bo Guan, Muhua Xie, Kun Nakano, Kimihiko Institute of Industrial Science University of Tokyo Tokyo153-8505 Japan School of Design & Innovation China Academy of Art Hangzhou311100 China School of Computer Science & System Engineering Kyushu Institute of Technology Fukuoka820-8502 Japan Department of Civil and Environmental Engineering Transportation Informatics Lab Old Dominion University NorfolkVA23529 United States

Automated vehicles hold great potential to revolutionize transportation, but subjective user acceptance remains a major obstacle to their widespread adoption and the realization of anticipated safety benefits. Recognizing this challenge, this study explores the role of gamification in enhancing user acceptance of automated vehicles and promoting safer driver engagement. By designing a gamified interaction framework and implementing it in a driving simulator experiment, the research addresses three core questions: Does gamification work? Why does it work? How can it be effectively implemented? In the experiment, participants experienced automated driving scenarios with integrated gamified interactions during overtaking tasks. Data on users' attitudes, behaviors, and eye movements were collected and analyzed through qualitative and quantitative methods. Furthermore, the study incorporated design research techniques, including interviews and user journey mapping, into the scientific framework to derive meaningful and actionable insights. The results reveal that gamification significantly improves user acceptance by enhancing Perceived Ease of Use and strengthening Behavioral Intentions. At a deeper mechanistic level, gamification enhances users' situational awareness and trust by increasing their perception efficiency during interactions and raising their risk tolerance, thereby shifting the balance between safety and reward. Based on these mechanisms and further findings, the study proposes three design strategies to maximize the benefits of gamification: designing system transparency, tailoring experiences to individual user characteristics, and leveraging incentive mechanisms to engage and motivate users effectively. This study's findings provide theoretical foundations and practical design directions for leveraging gamification to enhance human-vehicle interactions, utimately contributing to the development of safer and more efficient automated driving systems. © 2

关键词： Eye movements

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Reversibility in chemical reactions 12th

Reversibility in chemical reactions

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12th International Conference on Reversible Computation, RC 2020

作者： Kuhn, Stefan Aman, Bogdan Ciobanu, Gabriel Philippou, Anna Psara, Kyriaki Ulidowski, Irek School of Computer Science and Informatics De Montfort University Leicester United Kingdom Romanian Academy Institute of Computer Science Iaşi Romania Faculty of Computer Science A.I. Cuza University Iaşi Romania Department of Computer Science University of Cyprus Nicosia Cyprus School of Informatics University of Leicester Leicester United Kingdom

ISBN: (纸本)9783030473600

In this chapter we give an overview of techniques for the modelling and reasoning about reversibility of systems, including out-of-causal-order reversibility, as it appears in chemical reactions. We consider the autoprotolysis of water reaction, and model it with the Calculus of Covalent Bonding, the Bonding Calculus, and Reversing Petri Nets. This exercise demonstrates that the formalisms, developed for expressing advanced forms of reversibility, are able to model autoprotolysis of water very accurately. Characteristics and expressiveness of the three formalisms are discussed and illustrated. © The Author(s) 2020.

关键词： Petri nets

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