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Give Pedestrian More Choice: Socially Aware Navigation Using Reinforcement Learning with Human Action Entropy Maximization 18th

Give Pedestrian More Choice: Socially Aware Navigation Using...

引用

18th International Conference on Intelligent Autonomous systems (IAS)

作者： Wu, Jiaxu Asama, Hajime An, Qi Yamashita, Atsushi Univ Tokyo Grad Sch Engn Dept Precis Engn 7-3-1 HongoBunkyo Ku Tokyo 1138656 Japan Univ Tokyo Grad Sch Frontier Sci Dept Human & Engn Environm Studies 5-1-5 Kashiwanoha Kashiwa Chiba 2778563 Japan

ISBN: (纸本)9783031449802;9783031449819

Robot navigation in a human-populated environment has spurred wide interest in recent years. While moving safely and efficiently are basic requirements for robot navigation, it is also important for robots to move in a socially acceptable way that obeys the social norms. However, since the social norms are subtle and diverse, most of the rule-based methods considered only situations of pairwise human-robot confrontation, and are difficult to generalize to crowded scenarios. In this paper, we propose a socially aware navigation method using reinforcement learning with human action entropy maximization, in which the diversity of human choices is considered as a reward to inform the robot of the socially acceptable interaction with a crowd. By learning to maximize this reward, the proposed method realizes social acceptability by giving pedestrians more choices to enlarge their chance to take their preferred action. The experiments demonstrate that the proposed method enables the robot to learn socially aware navigation that provides neighboring pedestrians with efficient and safe traffic, outperforming state-of-the-art methods.

关键词： Robot navigation Reinforcement learning Human-robot interaction

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PLATERA: A Comprehensive Web-Based System and Sensor Dataset for Activity Recognition in Households Environments 1

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16th International Conference on Ubiquitous Computing and Ambient Intelligence

作者： Diaz-Jimenez, David Luis Lopez, Jose Gaitan-Guerrero, Juan F. Espinilla, Macarena Univ Jaen Jaen Spain

ISBN: (数字)9783031775710

ISBN: (纸本)9783031775703;9783031775710

In this work we present a web-based system, PLATERA, and an extensive dataset, Living Dataset PLATERA, designed to be used for activity recognition and monitoring in households environments. Each user of the platform can access different functions depending on their role, including activity monitoring, data management, sensor visualization, home creation, and sensor management. The dataset contains information gathered from a variety of sensors, including motion sensors that use passive infrared (PIR) technology to detect movement, anchor devices that measure Received Signal Strength Indicator (RSSI) to determine location, and activity bands that record physical activity data. Temperature and humidity sensors provide accurate measurements of environmental conditions, while magnetic technology powers the opening and closing sensors that operate doors. Through this work we hope to encourage the development of sensor-based activity recognition systems.

关键词： Activity Recognition Smart Homes Sensor Data Web-Based System Internet of Things

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Maritime Vessel Detection and Classification in Harbor Environment Using Deep Learning 20th

Maritime Vessel Detection and Classification in Harbor Envir...

引用

20th International Workshop on Combinatorial Image Analysis (IWCIA)

作者： Waleed, Khalid Farooq, Muhammad Umar Raza, Rana Hammad Natl Univ Sci & Technol NUST Pakistan Navy Engn Coll PNEC Karachi Pakistan

ISBN: (纸本)9783031665936;9783031665943

Automatic surveillance of docks, harbors, and seaports is considered crucial for ensuring smooth port operations. The identification and tracking of maritime vessels in these environments are generally facilitated by Radar and Automatic Identification System (AIS). However, radar faces challenges in detection of small non-metallic vessels, as well as there are other issues such as radar signal clutter, high electromagnetic radiation, and higher costs. Similarly, AIS also face challenges such as device malfunctioning or illegal manipulation etc. Consequently, cameras have been increasingly used in maritime traffic management systems. In recent years, Convolutional Neural networks (CNNs) have shown significant progress in object detection and classification tasks. Though, obtaining large scale maritime datasets with focus on harbor environment still remains a challenge. In this study, experimentation with various pre-trained state-of-the-art CNN models were conducted on images captured from harbor environments in Karachi and Grand Canal in Venice. The dataset presented several challenges such as high-density traffic, occlusions, shadows, background infrastructure, wave motion, boat wakes and reflection on water surface. The pre-trained CNNs were finetuned using a combination of small datasets to obtain both detector and classifier which outperformed previously published results on the MarDCT dataset. Specifically, the proposed model achieved a DR (Detection Rate) of 0.81, FAR (False Alarm Rate) of 0.07 and an average accuracy of 98.78% on the MarDCT dataset.

关键词： Maritime Traffic Vessel Detection Vessel Classification Machine Learning Deep Learning Convolutional Neural networks

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Literature Survey: Complaint Management System Using Blockchain Technology 8th

Literature Survey: Complaint Management System Using Blockch...

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Shetye, Isha Morwadkar, Suchitra Chavan, Bhakti Rajole, Samruddhi Kulkarni, Sanika MKSSSs Cummins Coll Engn Women Dept Informat Technol Pune 411052 Maharashtra India

ISBN: (纸本)9789819713127;9789819713134

In a world where technological advancements are rapidly evolving, the need for secure and trustworthy digital processes is very important. As digital interactions play a significant role in daily lives, issues like data breaches, unauthorized access, and fraudulent activities have raised profound concerns. To address these real world problems, Blockchain technology emerges as a transformative solution. The paper highlights the unique characteristics of Blockchain which includes decentralization, security, immutability, transparency, and anonymity revolutionizing the management of police complaints, particularly through First Information Reports in Complaint Management System. The paper addresses the various challenges faced by the traditional Complaint Management System which includes manual intervention, security concerns, lack of transparency, and delays. The paper proposes Blockchain technology as a solution to surmount these challenges by providing a decentralized, tamper-proof, and transparent platform for complaint registration, tracking, investigation, and resolution. The literature survey encompasses various research studies that propose and explore Blockchain-based solutions for complaint management and outlines a need for shift from traditional Complaint Management System to Blockchain-based Complaint Management System.

关键词： Blockchain Complaint Management System (CMS) Decentralization First Information Report (FIR) Immutability Security Traditional Complaint Management System (t-CMS)

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Development of an IALF Overarching Learning Module for Circular Economy 14th

Development of an IALF Overarching Learning Module for Circu...

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14th International Conference on Learning Factories (CLF)

作者： Barth, Jonas Ruzicic, Nada Mennenga, Mark Panagiotopoulou, Vasiliki Wolf, Matthias Ayroa, Ricardo Vega Sattari, Massoud Koeppe, Gesine Weyand, Astrid Seyfried, Stefan Mangers, Jeff Thiede, Sebastian Niemeyer, Jan Felix Khoulenjani, Zahra Ghazanfarpour Petrusch, Natalie Metternich, Joachim Weigold, Matthias Herrmann, Christoph Hummel, Vera Braun, Anja Stavropoulos, Panagiotis Tech Univ Darmstadt Otto Berndt Str 2 D-64287 Darmstadt Germany Reutlingen Univ ESB Business Sch Alteburgstr 150 D-72762 Reutlingen Germany Technol Univ Braunschweig Inst Machine Tools & Prod Technol Langer Kamp 19B D-38106 Braunschweig Germany Univ Patras Dept Mech Engn & Aeronaut Lab Mfg Syst & Automat Patras 26504 Greece Graz Univ Technol Inst Innovat & Ind Management Kopernikusgasse 24-2 A-8010 Graz Austria ITA Acad GmbH Vaalserstr 460 D-52074 Aachen Germany Univ Luxembourg Fac Sci Technol & Med 6 Rue Richard Coudenhove Kalergi L-1359 Esch Sur Alzette Luxembourg Univ Twente Fac Engn Technol Dept Design Prod & Management Chair Mfg Syst De Horst 2Bldg 20 NL-7522 LW Enschede Netherlands Fraunhofer IPK Pascalstr 8-9 D-10587 Berlin Germany

ISBN: (纸本)9783031654107;9783031654114

The increasing importance of sustainable business models due to the scarcity of resources and resulting political regulations leads many companies and research institutions towards the concept of Circular Economy. Subsequently, the learning factory community is facing the challenge of expanding existing concepts to include Circular Economy in their learning factories. Therefore, a learning factory- and competency-based module for Circular Economy is developed by eight members of the International Association of Learning Factories to define a common ground. The module covers the basics of Circular Economy in the production environment and make it tangible through concrete use cases. To achieve these goals, extensive research on existing concepts has been conducted by IALF experts to analyze learning objectives and requirements in detail and derive required competencies. Based on that, the learning module is developed.

关键词： Circular Economy learning module competency development

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Transfer Learning for Speaker Verification with Short-Duration Audio 1

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8th Smart Trends in Computing and Communications (SmartCom)

作者： Fathima, Noor Simha, J. B. Abhi, Shinu REVA Univ REVA Acad Corp Excellence RACE Bangalore Karnataka India

ISBN: (数字)9789819713134

ISBN: (纸本)9789819713127;9789819713134

Speaker verification or identifying the legitimacy of a speaker's identification from their voice is a fundamental problem in speech processing and biometrics. The growing requirement for efficient and secure speaker verification systems, particularly in applications such as voice assistants, authentication, and communications, has increased the necessity for reliable verification even with short-duration audio samples. Short-duration audio provides a considerable barrier because of the limited information available for processing. In this research, it is investigated to make use of the transfer learning strategies to meet this difficulty and improve speaker verification systems' performance. The primary goal of this research is to investigate how transfer learning can be used to improve speaker verification while working with short-duration audio. To get started, a varied dataset of brief audio samples from a variety of speakers, languages, and settings is gathered. To improve the quality and diversity of the dataset, these audio samples are then put through preprocessing procedures such as noise reduction, feature extraction, and data augmentation. To validate speakers based on data samples collected from a few speakers, during this process, speech signals from each speaker are collected for roughly 20-30 s. The speakers are enrolled using a pre-trained 3D convolutional neural network (3D-CNN) at the enrollment step. Speaker verification is performed on the data samples by enrolling the necessary speakers and creating a speaker model for each speaker. The speakers are then validated at the authentication stage.

关键词： Speaker recognition Speaker verification Speaker identification Three-dimensional convolutional neural network (3D-CNN)

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Developing a Hybrid Pseudo-Random Numbers Generator 2nd

Developing a Hybrid Pseudo-Random Numbers Generator

引用

2nd International Conference on Forthcoming networks and Sustainability in the AIoT Era (FoNeS-AIoT)

作者： Mohammed, Saja J. Univ Mosul Coll Comp & Math Comp Sci Dept Mosul Iraq

ISBN: (纸本)9783031628801;9783031628818

Pseudo-random numbers (PRNs) play a vital role in many fields, such as cyber security, simulations, games, and statistical analysis. They provide the level of unpredictability necessary for secure communication and data protection. A Pseudo Random Number Generator (PRNG) is an important tool that can generate number sequences exhibiting statistical properties similar to that of True Random Numbers (TRNs). This paper proposes a PRNG based on multiple principles: feature extraction, biometrics, and a 6D hyperchaotic system. The proposed tool combines these three topics in a specific order to utilize the randomization inherent in each one. The resulting sequence (LPB-chao sequence) underwent a set of randomization tests to ensure its randomization. These tests were applied inside the proposed tool to produce only randomly strong sequences and reject the weak ones. The practical experiments proved that there is great key sensitivity, and the execution time is linearly proportional to the length of the generated sequence.

关键词： Biometrics Cryptography Cyber Security Pseudo Random Number Generator (PRNG) 6D Hyperchaotic System

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How Indirect and Direct Interaction Affect the Trustworthiness in Normal and Explainable Human-Robot Interaction 21st

How Indirect and Direct Interaction Affect the Trustworthine...

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21st International Conference on Smart Technologies and Education (STE) on Smart Technologies for a Sustainable Future

作者： Pham, Truong An Espinosa-Leal, Leonardo Arcada Univ Appl Sci Grad Sch & Res Jan Magnus Janssons Pl 1 Helsinki 00560 Finland

ISBN: (纸本)9783031619045;9783031619052

Human-robot interaction (HRI) attracts significant attention from the public due to the ubiquity of robots in factories, restaurants, and even at home. However, the engagement of users in interacting with the robot is still a question mark due to the challenging trustworthiness. The trustworthiness becomes more complicated when discussing indirect interaction - humans observe the robot - and direct interaction - humans and robots may interact or not interact when being close to each other - in the robotic design. Several studies were conducted to analyze human trust in either indirect or direct aspects of robotic systems. The shortage of benchmarking indirect interaction and direct interaction initiates a significant gap in designing and developing a more subtle robotic system in complex scenarios that involve different stakeholders, such as users and observers, known as indirect users. In this study, we propose a novel guideline for evaluating such robotic systems in human-robot interaction. Particularly, we analyze differences between indirect and direct interaction about human trustworthiness in HRI. In addition, we also investigate the simulation methodology including virtual reality and video to evaluate a human-robot interaction scenario in both normal and explainable robotic systems by integrating a visual feedback module. By conducting quantitative and qualitative experiments, there is no significant difference between indirect and direct interaction in the trustworthiness of HRI. Instead, the explainable feature is recognized as the key factor in improving the trustworthiness of a robotic system.

关键词： human-robot interaction augmented reality virtual reality

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Drawbacks of Programming Dataflow Architectures and Methods to Overcome Them 1

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2nd Serbian International Conference on Applied Artificial Intelligence (SICAAI)

作者： Korolija, Nenad Univ Belgrade Sch Elect Engn Bulevar Kralja Aleksandra 73 Belgrade Serbia

ISBN: (数字)9783031608407

ISBN: (纸本)9783031608391;9783031608407

Compared to the control-flowparadigm dataflow paradigm is proven to be superior for certain classes of high-performance computing algorithms, such as AI. However, this comes with the cost. Many problems should be solved in order to efficiently utilize dataflow hardware. Some of them are programming dataflow architectures and debugging issues that arise during this process, relatively long simulation time, finding suitable dataflow hardware, and difficulties with the debugging hardware problems that might occur. This paper analyses existing solutions for accelerating high-performance computing algorithms along with problems that each architecture introduces, as well as potential solutions to the aforementioned drawbacks of utilizing the dataflow paradigm for accelerating algorithms. The analysis is performed on both hardware and software levels. Results indicate that dataflow hardware has the potential to be efficiently used along with control-flow hardware using AI. The best performance is achieved when combining control-flow and dataflow hardware on the same chip die.

关键词： High-Performance Computing Control-flow Dataflow

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Flexible and Transportable Illumination Control System for Machine Vision Applications 10th

Flexible and Transportable Illumination Control System for M...

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International Conference on New Technologies, Development and Application - Advanced Production Processes and Intelligent systems

作者： Gusic, Muhamed Sokic, Emir Univ Sarajevo Dept Automat Control & Elect Fac Elect Engn Sarajevo 71000 Bosnia & Herceg

ISBN: (纸本)9783031662706;9783031662713

During the development of machine vision setups for industrial applications, namely automatic visual inspection systems, the type of required lighting and correct illumination position and intensity are often not known in advance. In order to solve a specific machine vision task, an engineer needs to propose and implement a suitable image processing algorithm and design the accompanying lighting system. Testing different illumination concepts, especially "in the field", using off-the-shelf lighting systems is time consuming. The paper presents a custom-made, cost effective, transportable and flexible system which may be used for testing different illumination techniques and simultaneously control multiple lighting modules. In addition to the hardware part, the developed software used for control the system is presented in the paper. The proposed device usefulness is demonstrated by solving a suitable multi-light digital image processing task.

关键词： machine vision visual inspection illumination control system embedded systems digital image processing

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