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作者： Shankar, K. Lakshmanaprabu, S.K. Gupta, Deepak Khanna, Ashish de Albuquerque, Victor Hugo C. School of Computing Kalasalingam Academy of Research and Education Krishnankoil India B. S. Abdur Rahman Crescent Institute of Science and Technology Chennai India Maharaja Agrasen Institute of Technology Delhi India Graduate Program in Applied Informatics University of Fortaleza Fortaleza Brazil

The security of digital images is an essential and challenging task on shared communication Model. Generally, high secure working environment and data are also secured with an encryption and decryption method by using secret and public keys. In this paper, the innovative encryption technique for image security, ie, Multiple key-based Homomorphic Encryption (MHE) technique is proposed. For increasing the security level of encryption and decryption processes, the optimal key is selected using Adaptive Whale Optimization (AWO) algorithm. Fitness function was considered for optimization as PSNR of plain and cipher images. The original image was transformed into blocks and then rearranged utilizing encryption process, this work achieved maximum security, much better than other encryption techniques. From the outcomes, one can achieve incredible quality of the proposed model, the maximum PSNR, and the minimum MSE contrasted with other encryption schemes. © 2018 John Wiley & Sons, Ltd.

关键词： Cryptography

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Model-Based Analysis of Microservice Resiliency Patterns

Model-Based Analysis of Microservice Resiliency Patterns

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Working IEEE/IFIP Conference on Software Architecture

作者： Nabor C. Mendonca Carlos M. Aderaldo Javier Camara David Garlan Post Graduate Program in Applied Informatics University of Fortaleza Brazil Post Graduate Program in Applied Informatics University of Fortaleza CE Brazil University of York York UK School of Computer Science Carnegie Mellon University Pittsburgh PA USA

ISBN: (数字)9781728146591

ISBN: (纸本)9781728146607

Microservice application developers try to mitigate the impact of partial outages typically by implementing service-to-service interactions that use well-known resiliency patterns, such as Retry, Fail Fast, and Circuit Breaker. However, those resiliency patterns-as well as their available open-source implementations-are often documented informally, leaving it up to application developers to figure out when and how to use those patterns in the context of a particular microservice application. In this paper, we take a first step towards improving on this situation by introducing a model checking-based approach in which we use the PRISM probabilistic model checker to analyze the behavior of the Retry and Circuit Breaker resiliency patterns as continuous-time Markov chains (CTMC). This approach has enabled us to quantify the impact of applying each resiliency pattern on multiple quality attributes, as well as to determine how to best tune their parameters to deal with varying service availability conditions, in the context of a simple client-service interaction scenario.

关键词： Circuit breakers Resilience Integrated circuit modeling Probabilistic logic Transient analysis Circuit faults Analytical models

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Dynamic Deployment and Control of an NDN Network for Military Multi-UAVs Based Surveillance Applications

Dynamic Deployment and Control of an NDN Network for Militar...

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International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Otávio A. Rocha da Cruz Carlos Eduardo Pereira Antonio Santos da Silva João Paulo J. da Costa Paulo Mendes Edison Pignaton de Freitas Graduate Program in Electrical Engineering Federal University of Rio Grande do Sul Rio Grande do Sul Brazil Institute of Informatics Federal University of Rio Grande do Sul Rio Grande do Sul Brazil Hamm-Lippstadt University of Applied Sciences (HSHL) Hamm Germany Karlsruhe Institute of Technology (KIT) Karlsruhe Germany Airbus Taufkirchen Germany

ISBN: (数字)9798350357882

ISBN: (纸本)9798350357899

The military usage of Unmanned Aerial Vehicles (UAVs) has garnered attention, especially after their employment in the Ukrainian war. Despite the most commented lethal usage, they have many other applications from which surveillance for imagery acquisition is one of primal importance. Using a standalone UAV for this purpose is well-known, but to cope with the scale of battlefield operations, using multi- UAV systems is an asset of great value. However, these systems rely on ad hoc networks that require solutions beyond conventional ones based on the Internet Protocol (IP). This paper addresses this concern by proposing a communication support mechanism for multi-UAV military surveillance systems based on the Information-Centric Networks (ICN) paradigm. The proposed approach consists of the dynamic deployment of an ICN network based on microservices architecture, where the communication services of each UAV are deployed according to their resources. The solution is validated in a simulated battlefield scenario where a surveillance UAV provides data demanded by other nodes. The results demonstrate that the proposed solution minimizes the data delivery delays by successfully deploying the customized set of microservices to support the transmission, even when a UAV with a low battery level is replaced at runtime.

关键词： Military communication Runtime Protocols Surveillance Information-centric networking Microservice architectures Autonomous aerial vehicles

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The effect of stereochemical constraints on the radius of gyration of folded proteins

arXiv

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arXiv 2025年

作者： Logan, Jack A. Sumner, Jacob Grigas, Alex T. Shattuck, Mark D. O'Hern, Corey S. Department of Mechanical Engineering Yale University New HavenCT06520 United States Graduate Program in Computational Biology & Biomedical Informatics Yale University New HavenCT06520 United States Integrated Graduate Program in Physical and Engineering Biology Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department The City College of New York New YorkNY10031 United States Department of Applied Physics Yale University New HavenCT06520 United States Department of Physics Yale University New HavenCT06520 United States

Proteins are composed of linear chains of amino acids that fold into complex three-dimensional structures. A general feature of folded proteins is that they are compact with a radius of gyration Rg(N) ∼ Nν that obeys power-law scaling with the number of amino acids N in each protein and ν ∼ 1/3. In this study, we investigate the internal scaling of the radius of gyration Rg(n) versus the chemical separation n between amino acids for all subchains of length n. We show that for globular proteins Rg(n) ∼ nν1,2 with a larger exponent ν1 > 1/3 for small n and a smaller exponent ν2 g(N) ∝ Nν. To describe this scaling behavior for Rg(n), we carry out folding simulations for a series of coarse-grained models for proteins beginning with the freely-jointed and freely-rotating chain models composed of spherical monomers and varying degrees of stereochemical constraints. We show that a minimal model, which coarse-grains amino acids into a single spherical backbone atom and one variable-sized spherical side-chain atom, and enforces bend- and dihedral-angle constraints, can recapitulate Rg(n) for x-ray crystal structures of globular proteins. In addition, this model predicts the correct average packing fraction and size of the hydrophobic core, which are two key physical features that can be used to distinguish between computational 'decoys' and correctly folded proteins in protein design applications. © 2025, CC BY.

关键词： Spheres

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Identifying New Persons in the Context of the Robocup@Home Competition Using KNN

Identifying New Persons in the Context of the Robocup@Home C...

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IEEE Latin American Robotics Symposium, LARS

作者： David Segalle Gustavo Fardo Armênio Gustavo Fontes Lewin Everson De Souza Silva João Alberto Fabro Computer Engineering Course UTFPR-Federal University of Technology - Paraná Curitiba PR Brazil Computer Engineering Course - UTFPR Curitiba PR Brazil Eletronic Engineering Course - UTFPR Curitiba PR Brazil PPGCA-Graduate Program on Applied Informatics-UTFPR Curitiba PR Brazil

Robocup@Home proposes a challenge related to Person Recognition: after presented, a new ‘operator’ should become ‘immediately’ recognizable by the robot. The presentation procedure may require the operator to correctly interact with the robot, following a certain procedure, as instructed by the robot itself (for example, staying in front of the robot, so that the robot can take pictures of this person). In this paper, we propose the use of the KNN (K-Nearest Neighbor) supervised machine learning algorithm to include a new ‘operator’ in a database of persons recognizable by the robot. This algorithm uses information taken from an image segmentation of the face of the operator. The experiment evaluates how long it takes to include a new operator if the robot has from 1 to 12 current operators, evaluating also how long it takes to include this operator based on 1, 2 or more images of the new operator, taken from slightly different points of view. The results confirm that KNN can be used to ‘present to the robot’ up to 13 new operators, with up to 15 images for each operator, in less than 60 seconds.

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2D Basement Relief Inversion using Sparse Regularization.

arXiv

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arXiv 2024年

作者： Barboza, Francisco Márcio da Cunha Romão Silva, E. Arthur Anthony de Carvalho, Bruno Motta Department of Computing and Technology Federal University of Rio Grande do Norte Rio Grande do Norte Caicó Brazil Graduate Program on Systems and Computing Federal University of Rio Grande do Norte Rio Grande do Norte Natal Brazil Department of Informatics and Applied Mathematics Federal University of Rio Grande do Norte Rio Grande do Norte Natal Brazil

Basement relief gravimetry is a key application in geophysics, particularly important for oil exploration and mineral prospecting. It involves solving an inverse geophysical problem, where the parameters of a geological model are inferred from observed data. In this context, the geological model consists of the depths of constant-density prisms representing the basement relief, and the data correspond to the gravitational anomalies caused by these prisms. Inverse geophysical problems are typically ill-posed, as defined by Hadamard, meaning that small perturbations in the data can result in large variations in the solutions. To address this instability, regularization techniques, such as those proposed by Tikhonov, are employed to stabilize the solutions. This study presents a comparative analysis of various regularization techniques applied to the gravimetric inversion problem, including Smoothness Constraints, Total Variation, the Discrete Cosine Transform (DCT), and the Discrete Wavelet Transform (DWT) using Daubechies D4 wavelets. Optimization methods are commonly used in inverse geophysical problems because of their ability to find optimal parameters that minimize the objective function—in this case, the depths of the prisms that best explain the observed gravitational anomalies. The Genetic Algorithm (GA) was selected as the optimization technique. GA is based on Darwinian evolutionary theory, specifically the principle of natural selection, where the fittest individuals in a population are selected to pass on their traits. In optimization, this translates to selecting solutions that most effectively minimize the objective function. The results, evaluated using fit metrics and cumulative error analysis, demonstrate the effectiveness of all the regularization techniques and the Genetic Algorithm. Among the methods tested, the Smoothness constraint was briefly the most effective for the first and second synthetic models. For the third model, which was based on re

关键词： Discrete wavelet transforms

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A multicriteria approach to support task allocation in projects of distributed software development

A multicriteria approach to support task allocation in proje...

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作者： Simão Filho, Marum Pinheiro, Plácido R. Albuquerque, Adriano B. Simão, Régis P. S. Azevedo, Raimundo S. N. Nunes, Luciano C. Graduate Program in Applied Informatics University of Fortaleza Brazil Information Systems 7 de Setembro University Center Brazil

Organizations are increasingly investing in Distributed Software Development (DSD) over the years. A typical decision-making problem in the distributed scenario consists of deciding which team should be allocated each task. That decision takes into account a relative degree of subjectivity. That setting is suitable for applying Verbal Decision Analysis (VDA). This paper introduces an approach to support the allocation of tasks to distributed units in DSD projects, structured on the hybridisation of methods of Verbal Decision Analysis for classification and rank ordering applied to influencing factors and executing units. Firstly, a review of the literature was conducted aiming to identify the approaches to support the allocation of tasks in DSD contexts. Then, an approach was developed by applying VDA-based methods for classification and ordering. Bibliographic research and the application of surveys with professionals allowed identifying and characterising the main elements that influence task assignment in DSD projects. Afterwards, experiences were carried out in five real-world companies. In the end, the proposed approach has been submitted to the evaluation by the professionals of the participating companies and by some project management experts. The proposed approach comprises a workflow containing responsible actors and descriptions of the activities. Automated tools are also employed in automating the implementation of the approach. After applying the approach in five companies, task assignment recommendations are presented in groups for each company, according to the task type, i.e., requirements, architecture, coding, and testing, ranging from the most to the least preferable office. Results of the experiences and evaluations held during this work present evidence that the proposed approach is flexible, adaptable, and easy to understand and to use. Moreover, it helps to reduce decision subjectivity and to think of new aspects, supporting the task allocatio

关键词： Project management

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Patient Confidential Data Hiding and Transmission System Using Amplitude Quantization in the Frequency Domain of ECG Signals

引用

Sensors 2023年第22期23卷 9199-9199页

作者： Chen, Shuo-Tsung Ye, Ren-Jie Wu, Tsung-Hsien Cheng, Chun-Wen Zhan, Po-You Chen, Kuan-Ming Zhong, Wan-Yu Department of Medical Informatics Chung Shan Medical University Taichung40201 Taiwan Department of Information Center Chung Shan Medical University Hospital Taichung40201 Taiwan Graduate School of Applied Chinese Studies National Yunlin University of Science and Technology Yunlin 64002 Taiwan Bachelor’s Program in Business Management Fu Jen Catholic University New Taipei City242062 Taiwan

The transform domain provides a useful tool in the field of confidential data hiding and protection. In order to protect and transmit patients’ information and competence, this study develops an amplitude quantization system in a transform domain by hiding patients’ information in an electrocardiogram (ECG). In this system, we first consider a non-linear model with a hiding state switch to enhance the quality of the hidden ECG signals. Next, we utilize particle swarm optimization (PSO) to solve the non-linear model so as to have a good signal-to-noise ratio (SNR), root mean square error (RMSE), and relative root mean square error (rRMSE). Accordingly, the distortion of the shape in each ECG signal is tiny, while the hidden information can fulfill the needs of physiological diagnostics. The extraction of hidden information is reversely similar to a hiding procedure without primary ECG signals. Preliminary outcomes confirm the effectiveness of our proposed method, especially an Amplitude Similarity of almost 1, an Interval RMSE of almost 0, and SNRs all above 30. © 2023 by the authors.

关键词： Electrocardiograms

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Design and Deployment of an Efficient Communication Service for Multi-UAV Systems

Design and Deployment of an Efficient Communication Service ...

引用

International Conference on Unmanned Aircraft Systems (ICUAS)

作者： Pedro H. M. Pereira Faezeh Pasandideh Maik Basso Joao Paulo J. da Costa Edison Pignaton de Freitas Graduate Program in Electrical Engineering Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Hamm-Lippstadt University of Applied Sciences (HSHL) Hamm Germany Institute of Informatics Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil Department of "Technology and Systems" PK NRW Germany

Recent advances in the areas of microelectronics, information technology, and communication protocols have made possible the development of smaller devices, with increasing processing capacity and low energy consumption. This context contributed to the growth of applications based on the use of one or multiple Unmanned Aerial Vehicles (UAVs). Networks composed of multiple UAVs are being used as a matter of improving the effectiveness, accuracy, and minoring the time of missions. However, these applications demand a high rate of data exchange, such as the localization information of each UAV, which can be a challenge, due to the limited transmission power of certain drone platforms. This article proposes a communication service for multi-UAV systems based on dividing the UAV-fleet into groups using the communication protocol IEEE 802.11 ac. Each group has its local network, whose participants can be chosen based on the UAV’s localization or task assignment. UAVs/Drones within the same group constantly communicate, exchanging pose information and specific mission-related data. On the other hand, communication between different groups is only established by messenger drones in pre-set times. The communication service from its detailed implementation to its simulated and field validation experiments is presented in this paper. The results of three different network topologies provide evidence that the proposed communication service for multi-UAV is efficient and can be used for drone cooperative missions.

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Instruction Multi-Constraint Molecular Generation Using a Teacher-Student Large Language Model

arXiv

引用

arXiv 2024年

作者： Zhou, Peng Wang, Jianmin Li, Chunyan Wang, Zixu Liu, Yiping Sun, Siqi Lin, Jianxin Wei, Leyi Cai, Xibao Lai, Houtim Liu, Wei Wang, Longyue Liu, Yuansheng Zeng, Xiangxiang College of Information Science and Engineering Hunan University Changsha China The Interdisciplinary Graduate Program in Integrative Biotechnology Yonsei University Incheon21983 Korea Republic of School of Informatics Yunnan Normal University Kunming650500 China Department of Computer Science University of Tsukuba Tsukuba3058577 Japan Research Institute of Intelligent Complex Systems Fudan University Shanghai200433 China Shanghai AI Laboratory Shanghai200232 China Centre for Artificial Intelligence driven Drug Discovery Faculty of Applied Science Macao Polytechnic University China School of Informatics Xiamen University Xiamen China Tencent AI Lab China

While various models and computational tools have been proposed for structure and property analysis of molecules, generating molecules that conform to all desired structures and properties remains a challenge. Here, we introduce a multi-constraint molecular generation large language model, TSMMG, which, akin to a student, incorporates knowledge from various small models and tools, namely, the 'teachers'. To train TSMMG, we construct a large set of text-molecule pairs by extracting molecular knowledge from these 'teachers', enabling it to generate novel molecules that conform to the descriptions through various text prompts. We experimentally show that TSMMG remarkably performs in generating molecules meeting complex, natural language-described property requirements across two-, three-, and four-constraint tasks, with an average molecular validity of over 99% and success ratio of 82.58%, 68.03%, and 67.48%, respectively. The model also exhibits adaptability through zero-shot testing, creating molecules that satisfy combinations of properties that have not been encountered. It can comprehend text inputs with various language styles, extending beyond the confines of outlined prompts, as confirmed through empirical validation. Additionally, the knowledge distillation feature of TSMMG contributes to the continuous enhancement of small models, while the innovative approach to dataset construction effectively addresses the issues of data scarcity and quality, which positions TSMMG as a promising tool in the domains of drug discovery and materials science. Copyright © 2024, The Authors. All rights reserved.

关键词： Students

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