This paper presents an external wrench estimator that uses a hybrid dynamics model consisting of a firstprinciples model and a neural network. This framework addresses one of the limitations of the state-of-the-art mo...
Marianna Ruggieri, Andrea Scapellato; Preface of the Symposium “Qualitative Properties of Solutions of Differential Equations”, AIP Conference Proceedings, Volu
Marianna Ruggieri, Andrea Scapellato; Preface of the Symposium “Qualitative Properties of Solutions of Differential Equations”, AIP Conference Proceedings, Volu
In the dynamic landscape of artificial intelligence and machine learning, Reinforcement Learning (RL) has emerged as a powerful paradigm for training intelligent agents in sequential decision-making. As RL architectur...
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ISBN:
(数字)9798350359169
ISBN:
(纸本)9798350359176
In the dynamic landscape of artificial intelligence and machine learning, Reinforcement Learning (RL) has emerged as a powerful paradigm for training intelligent agents in sequential decision-making. As RL architectures progress in complexity, the need for informed decision-making regarding training strategies and related consequences on the software architecture becomes increasingly intricate. This work addresses this challenge by presenting the outcomes of a qualitative, in-depth study focused on best practices and patterns within training strategies for RL architectures, as articulated by practitioners. Leveraging a model-based qualitative research method, we introduce a formal architecture decision model to bridge the gap between scientific insights and practical implementation. We aim to enhance the understanding of practitioners' approaches in RL architecture. The paper analyzes 33 knowledge sources to discern established industrial practices, patterns, relationships, and decision drivers. Based on this knowledge, we introduce a formal Architectural Design Decision (ADD) model, encapsulating 6 decisions, 29 decision options, and 19 decision drivers, providing robust decision-making support for this critical facet of RL-based software architectures.
The API Rate Limit pattern controls the rate at which clients make API requests by counting the number of requests in a specified time interval and reacting against abusive clients, in order to protect the limited res...
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ISBN:
(纸本)9798400700408
The API Rate Limit pattern controls the rate at which clients make API requests by counting the number of requests in a specified time interval and reacting against abusive clients, in order to protect the limited resources of the API from exhaustion and denial of service attacks. This practice helps service providers to prevent abuse and ensure fair resource allocation, maintain system stability, monitor and control service availability, protect against DDoS attacks In this research paper, we have identified patterns covering the API Rate Limit pattern adoption starting from its documentation to its implementation. Our objective is to elucidate the trade-offs associated with different identified patterns and offer guidance to developers in making informed decisions when choosing the most suitable Rate Limit method, scope, and granularity for their service. By providing a comprehensive overview of how to adopt the Rate Limit pattern, this paper aims to enhance the understanding of how APIs can be designed to facilitate high scalability, security, reliability, and service availability. Furthermore, we present each pattern along with known uses observed in real-world APIs and technologies.
With the advent of state-of-art technologies,the Telecare Medicine Information System(TMIS)now offers fast and convenient healthcare services to patients at their ***,this architecture engenders new risks and challeng...
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With the advent of state-of-art technologies,the Telecare Medicine Information System(TMIS)now offers fast and convenient healthcare services to patients at their ***,this architecture engenders new risks and challenges to patients'and the server's confidentiality,integrity and *** order to avoid any resource abuse and malicious attack,employing an authentication scheme is widely considered as the most effective approach for the TMIS to verify the legitimacy of patients and the ***,several authentication protocols have been proposed to this *** recently,Chaudhry et *** that there are vulnerabilities of impersonation attacks in Islam et al.'s ***,they introduced an improved protocol to mitigate those security ***,Qiu et *** that these schemes are vulnerable to the man-in-the-middle,impersonation and offline password guessing ***,they introduced an improved scheme based on the fuzzy verifier techniques,which overcome all the security flaws of Chaudhry et al.'s ***,there are still some security flaws in Qiu et al.'s *** this article,we prove that Qiu et al.'s protocol has an incorrect notion of perfect user anonymity and is vulnerable to user impersonation ***,we introduce an improved protocol for authentication,which reduces all the security flaws of Qiu et al.'s *** also make a comparison of our protocol with related protocols,which shows that our introduced protocol is more secure and efficient than previous protocols.
An important issue in data mining and information retrieval is the problem of multiple similarity or n-similarity. This problem entails finding a group of n data points with the highest similarity within a large datas...
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There are many challenges in maintaining the desired quality of service levels in modern microservice and cloud applications. Numerous techniques and patterns, such as API Rate Limit, Load Balancing, and Request Bundl...
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This paper presents an approach to architectural knowledge management that does not assume existing architectural design decisions or pattern applications are documented as architectural knowledge, but benefits from m...
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ISBN:
(纸本)9798400700408
This paper presents an approach to architectural knowledge management that does not assume existing architectural design decisions or pattern applications are documented as architectural knowledge, but benefits from more existing data. We drew inspiration from manual qualitative research methods for mining patterns and architectural knowledge and created a guideline model of which the ADD models are instances. We evaluated our approach on 11 cases from the gray literature. We found that it can provide suitable recommendations after modeling only a single case and reaches theoretical saturation and recommendations with low to very low errors after only 6-8 cases. Our approach shows that creating a reusable architectural design space is possible based only on limited case data. Our approach not only provides a novel approach to architectural knowledge management but can also be used as a tool for pattern mining.
The rapid evolution of artificial intelligence (AI) and robotics technologies are bringing drastic changes to society and industry in these recent years. The impressive progress in facilitating smart manufacturing in ...
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The rapid evolution of artificial intelligence (AI) and robotics technologies are bringing drastic changes to society and industry in these recent years. The impressive progress in facilitating smart manufacturing in this era of Industry 4.0 has made our lives much more convenient than ever before. Despite the greater reliability and stability of the robotic system, there are several challenges to overcome such as the restrictions of scenes, obstacles, and hardware specifications. Since a high precision positioning algorithm is of paramount importance in devising a mobile robot, the research in developing simultaneous localization and mapping has been garnered immerse attention especially from domains of the computer vision and autonomous robots. In this paper, a novel method is presented to significantly enhance the positioning precision of indoor unmanned guided vehicles. The approach involves several steps, including setting up hardware configurations and collecting relevant data by installing necessary devices and system packages within the robot operating system (ROS). Trilateration is employed to determine the relative position of the mobile robot using distance measurements. Coordinate transformation is then conducted to convert the collected input data of relative distances and orientations. Trajectory paths are obtained, and occupancy maps are constructed to estimate the resulting trajectory and generate a 2D grid map. Indoor localization and mapping are achieved using three drawstring displacement sensors along with orientation information from an Inertial Measurement Unit (IMU). The proposed method is extensively evaluated through experimentation on predefined navigation paths, and its performance is compared to state-of-the-art methods such as RealSense T265, Hector SLAM, and wheel odometry. The results show that the proposed method exhibits compelling performance in both mean error and occupancy map construction. Ultimately, the findings reported herein
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