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arXiv 2024年

作者： Fredriksson, Scott Saradagi, Akshit Nikolakopoulos, George Robotics and AI group The Department of Computer Science Electrical and Space Engineering Luleå University of Technology Sweden

In this article, we introduce a novel strategy for robotic exploration in unknown environments using a semantic topometric map. As it will be presented, the semantic topometric map is generated by segmenting the grid map of the currently explored parts of the environment into regions, such as intersections, pathways, dead-ends, and unexplored frontiers, which constitute the structural semantics of an environment. The proposed exploration strategy leverages metric information of the frontier, such as distance and angle to the frontier, similar to existing frameworks, with the key difference being the additional utilization of structural semantic information, such as properties of the intersections leading to frontiers. The algorithm for generating semantic topometric mapping utilized by the proposed method is lightweight, resulting in the method’s online execution being both rapid and computationally efficient. Moreover, the proposed framework can be applied to both structured and unstructured indoor and outdoor environments, which enhances the versatility of the proposed exploration algorithm. We validate our exploration strategy and demonstrate the utility of structural semantics in exploration in two complex indoor environments by utilizing a Turtlebot3 as the robotic agent. Compared to traditional frontier-based methods, our findings indicate that the proposed approach leads to faster exploration and requires less computation time. Copyright © 2024, The Authors. All rights reserved.

关键词： Semantics

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Job Shop Scheduling Using Genetic and Heuristic Exchange Algorithms for AGVs

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Journal of Institute of Control, robotics and Systems 2022年第2期28卷 191-201页

作者： Wang, Jun-Kyung Eoh, Gyuho Park, Tae-Hyoung Department of Control Robot Engineering Chungbuk National University Korea Republic of Industrial AI Research Center Chungbuk National University Korea Republic of Department of Intelligent Systems and Robotics Chungbuk National University Korea Republic of

Solving a job shop scheduling problem (JSSP) entails allocating entire jobs to machines to minimize the processing time. Generally, the transit time between machines is not considered in the conventional JSSP because it is shorter than the processing time. In a real production environment, however, the transit time of an autonomous ground vehicle (AGV) is long due to the need to solve random problems, such as finding an indirect route or avoiding collisions. Moreover, AGVs sometimes need to transport the job on directional roads with upstream and downstream constraints. Therefore, we present an AGV job scheduling algorithm considering the transit time. This study considers not only the transportation times of the jobs from one machine to another but also collisions on limited roads, similar to in a real environment. A near-optimal job sequence was obtained by combining the genetic algorithm (GA) with simulation and was comparing this with the traditional method. Additionally, this paper presents heuristics that deal with deadlocks in the process of combining JSSP and simulation. The combination of GA and heuristics was tested using various simulations. © ICROS 2022.

关键词： Genetic algorithms

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Topic Modeling Analysis of Chinese Medicine Literature on Potential Treatment

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Chinese Journal of Integrative Medicine 2024年第12期30卷 1128-1136页

作者： QIAN Jia-nan KANG Yan-lan HE You-cheng HU Hong-yi Department of Gastroenterology Longhua HospitalShanghai University of Traditional Chinese MedicineShanghai 200032China Institute of Digestive Diseases Longhua HospitalShanghai University of Traditional Chinese MedicineShanghai 200032China Institute of AI and Robotics Academy for Engineering&TechnologyFudan UniversityShanghai 200433China Clinical Research Center Longhua HospitalShanghai 200032China

Objective:To analyze Chinese medicine(CM)prescriptions for gastroesophageal reflux disease(GERD),we model topics on GERD-related classical CM literature,providing insights into the potential ***:Clinical guidelines were used to identify symptom terms for GERD,and CM literature from the database"Imedbooks"was retrieved for related prescriptions and their corresponding sources,indications,and other *** was applied to identify the main topics and visualize the ***:A total of 36,207entries are queried and 1,938 valid entries were acquired after manually *** topics were identified by BERTopic,including digestion function abate,stomach flu,respiratory-related symptoms,gastric dysfunction,regurgitation and gastrointestinal dysfunction in pediatric patients,vomiting,stroke and alcohol accumulation are associated with the risk of GERD,vomiting and its causes,regurgitation,epigastric pain,and symptoms of ***:Topic modeling provides an unbiased analysis of classical CM literature on GERD in a time-efficient and scale-efficient *** on this analysis,we present a range of treatment options for relieving symptoms,including herbal remedies and non-pharmacological interventions such as acupuncture and dietary therapy.

关键词： gastroesophageal reflux disease BERTopic prescription topic modeling Chinese medicine

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A Comparative Analysis of Fraud Detection from Diverse Datasets to Algorithmic Performance 8

A Comparative Analysis of Fraud Detection from Diverse Datas...

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8th International Conference on computer Science and engineering, UBMK 2023

作者： Iscan, Can Nardemir, Mehmet Akif Akbulut, Fatma Patlar Formica Ai R&d Center Istanbul Turkey Istanbul Kültür University Department of Computer Engineering Istanbul Turkey

ISBN: (纸本)9798350340815

The growth of e-wallets and the ease with which credit card information may be obtained online have contributed to the rise of credit card fraud in the digital age. In order to detect and prevent fraudulent acts in these areas, advanced and effective fraud detection systems must be created. In this work, we describe the results of a deep dive into the field of fraud detection using electronic money and credit card transactions as case studies. We investigate the most recent advances in deep learning, to tackle the challenging problem of fraud detection in these advanced settings. We conduct comprehensive experiments, utilizing e-wallet and credit card transaction datasets, to experimentally assess the performance of the suggested models. In terms of detecting and preventing fraudulent transactions, the experimental results provide more evidence that deep learning models are superior to more traditional rule-based paradigms. Using carefully constructed confusion matrices and receiver operating characteristic (ROC) curves, we elaborate on the models' ability to accurately discern and appraise the fraudulent undertones permeating the complexities of transactional data, as well as a variety of performance metrics. © 2023 IEEE.

关键词： Deep learning

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Real-time Architecture for Audio-Visual Active Speaker Detection

Real-time Architecture for Audio-Visual Active Speaker Detec...

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2022 IEEE International Conference on robotics and Biomimetics, ROBIO 2022

作者： Huang, Min Wang, Wen Lin, Zheyuan Tesema, Fiseha B. Ji, Shanshan Gu, Jason Wan, Minhong Song, Wei Li, Te Zhu, Shiqiang The Intelligent Robotics Research Center Zhejiang Lab Zhejiang Engineering Research Center for Intelligent Robotics Hangzhou311100 China Department of Electrical and Computer Engineering Dalhousie University Canada

ISBN: (纸本)9781665481090

Continuously measuring the speaking state of users with robot in a human-robot Interaction(HRI) system improves metrics of interaction quality. Meanwhile, mainstream active speaker detection (ASD) algorithms emphasize achieving high AUCs at frame level in the AVA-Active Speaker dataset and pay less attention to get real-time performance in robotic systems. In this paper, we propose a model named FSDNet to keep a high AUC score in the AVA-Active Speaker dataset while reducing time cost, our model increase AUC score by 0.1% compared with the State-Of-The-Art and need only 75% running time. Furthermore, we put forward an architecture with a time-related prediction function to make our algorithm more effective and generative in interactive robotic systems. The code is released at https://***/huangmin9966/FSDNet-RealTimeArch. © 2022 IEEE.

关键词： Human robot interaction

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Maximizing Resource Efficiency in Cloud Data centers through Knowledge-Based Flower Pollination Algorithm (KB-FPA)

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computers, Materials & Continua 2024年第6期79卷 3757-3782页

作者： Nidhika Chauhan Navneet Kaur Kamaljit Singh Saini Sahil Verma Kavita Ruba Abu Khurma Pedro A.Castillo University Institute of Computing Department Chandigarh UniversityPunjab140413India Department of Computer Science and Engineering Chandigarh UniversityPunjab140413India Universidade Federal do Piauí TeresinaPiauí64049-550Brazil MEU Research Unit Faculty of Information TechnologyMiddle East UniversityAmman11831Jordan Applied Science Research Center Applied Science Private UniversityAmman11931Jordan Department of Computer Engineering Automatics and RoboticsUniversity of GranadaGranada18071Spain

Cloud computing is a dynamic and rapidly evolving field,where the demand for resources fluctuates *** paper delves into the imperative need for adaptability in the allocation of resources to applications and services within cloud computing *** motivation stems from the pressing issue of accommodating fluctuating levels of user demand *** adhering to the proposed resource allocation method,we aim to achieve a substantial reduction in energy *** reduction hinges on the precise and efficient allocation of resources to the tasks that require those most,aligning with the broader goal of sustainable and eco-friendly cloud computing *** enhance the resource allocation process,we introduce a novel knowledge-based optimization *** this study,we rigorously evaluate its efficacy by comparing it to existing algorithms,including the Flower Pollination Algorithm(FPA),Spark Lion Whale Optimization(SLWO),and Firefly *** findings reveal that our proposed algorithm,Knowledge Based Flower Pollination Algorithm(KB-FPA),consistently outperforms these conventional methods in both resource allocation efficiency and energy consumption *** paper underscores the profound significance of resource allocation in the realm of cloud *** addressing the critical issue of adaptability and energy efficiency,it lays the groundwork for a more sustainable future in cloud computing *** contribution to the field lies in the introduction of a new resource allocation strategy,offering the potential for significantly improved efficiency and sustainability within cloud computing infrastructures.

关键词： Cloud computing resource allocation energy consumption optimization algorithm flower pollination algorithm

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Bucketed Ranking-based Losses for Efficient Training of Object Detectors

arXiv

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arXiv 2024年

作者： Yavuz, Feyza Cam, Baris Can Dogan, Adnan Harun Oksuz, Kemal Akbas, Emre Kalkan, Sinan Department of Computer Engineering METU Ankara Turkey Five AI Ltd. United Kingdom METU ROMER Robotics Center Ankara Turkey

Ranking-based loss functions, such as Average Precision Loss and Rank&Sort Loss, outperform widely used score-based losses in object detection. These loss functions better align with the evaluation criteria, have fewer hyperparameters, and offer robustness against the imbalance between positive and negative classes. However, they require pairwise comparisons among P positive and N negative predictions, introducing a time complexity of O(PN), which is prohibitive since N is often large (e.g., 108 in ATSS). Despite their advantages, the widespread adoption of ranking-based losses has been hindered by their high time and space complexities. In this paper, we focus on improving the efficiency of ranking-based loss functions. To this end, we propose Bucketed Ranking-based Losses which group negative predictions into B buckets (B N) in order to reduce the number of pairwise comparisons so that time complexity can be reduced. Our method enhances the time complexity, reducing it to O(max(N log(N), P2)). To validate our method and show its generality, we conducted experiments on 2 different tasks, 3 different datasets, 7 different detectors. We show that Bucketed Ranking-based (BR) Losses yield the same accuracy with the unbucketed versions and provide 2× faster training on average. We also train, for the first time, transformer-based object detectors using ranking-based losses, thanks to the efficiency of our BR. When we train CoDETR, a state-of-the-art transformer-based object detector, using our BR Loss, we consistently outperform its original results over several different backbones. Code is available at: https://***/blisgard/BucketedRankingBasedLosses. © 2024, CC BY.

关键词： Object detection

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Squid-inspired and wirelessly controllable display for active camouflage in aquatic-environment

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npj Flexible Electronics 2024年第1期8卷 900-909页

作者： Doyoung Kim Seung Won Seon Minkyung Shin Jihwan Kim Bogeun Kim Janghoon Joo Sang Uk Park Wooseok Kim Hee Kyu Lee Byeong Woon Lee Se Gi Lee Su Eon Lee Ji-Hun Seo Seung Ho Han Bong Hoon Kim Sang Min Won Department of Electrical and Computer Engineering Sungkyunkwan University2066Seobu-roJangan-guSuwon 16419Republic of Korea Department of Smart Wearable Engineering Soongsil UniversitySeoul 06978Republic of Korea Electronic Convergence Materials and Devices Research Center Korea Electronics Technology Institute(KETI)Seongnam 13509Republic of Korea Department of Materials Science and Engineering Korea UniversitySeoul 02841Republic of Korea Department of Robotics and Mechatronics Engineering DGISTDaegu 42988Republic of Korea

Achieving optimal camouflage in an aquatic environment necessitates the ability to modulate transmittance in response to the surrounding obscurity and potential *** adaptation involves a dynamic transition from transparency to a deep-blue color,especially in low-light or dark *** a strategy promotes a seamless assimilation with the surroundings,enabling the absorption of searchlights and,subsequently,diminishing the risk of detection by ***,the presence of sophisticated mechanisms that facilitates stable and efficient control of transmittance is imperative,enabling smooth transition between transparent and deep-blue hues within the aquatic *** study presents nature-inspired programmable camouflage system that integrates an electrochromic display as the primary transmittance change element and a wireless base module for power and data *** technology offers a robust and flexible construction,ensuring stable operation as demonstrated through mechanical-fatigue experiments and quantitative simulation.A custom circuit and a power-control software package enable active control of multiple electrochromic displays while submerged in water.

关键词： transparency submerged lights

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Competition on robust deep learning

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National Science Review 2023年第6期10卷 13-15页

作者： Yinpeng Dong Chang Liu Wenzhao Xiang Hang Su Jun Zhu Department of Computer Science and Technology Institute for AI Tsinghua-Bosch Joint ML Center THBI Lab BNRist Center Tsinghua University Institute of Image Communication and Networks Engineering in the Department of Electronic Engineering (EE) Shanghai Jiao Tong University Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Peng Cheng Laboratory Pazhou Laboratory (Huangpu)

PROBLEM In recent years,the rapid development of artificial intelligence (ai) technology,especially machine learning and deep learning, is profoundly changing human production and *** various fields,such as robotics,face recognition,autonomous driving and healthcare,ai is playing an important ***,although ai is promoting the technological revolution and industrial progress,its security risks are often *** studies have found that the wellperforming deep learning models are extremely vulnerable to adversarial examples [1-3].The adversarial examples are crafted by applying small,humanimperceptible perturbations to natural examples,but can mislead deep learning models to make wrong *** vulnerability of deep learning models to adversarial examples can raise security and safety threats to various realworld applications.

关键词： robustness adversarial example adversarial training deep learning

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Soft Arm-Motor Thrust Characterization for a Pneumatically Actuated Soft Morphing Quadrotor

arXiv

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arXiv 2025年

作者： Sumathy, Vidya Haluska, Jakub Nikolokopoulos, George Robotics & AI Group Department of Computer Electrical and Space Engineering Luleå University of Technology LuleåSE-97187 Sweden

In this work, an experimental characterization of the configuration space of a soft, pneumatically actuated morphing quadrotor is presented, with a focus on precise thrust characterization of its flexible arms, considering the effect of downwash. Unlike traditional quadrotors, the soft drone has pneumatically actuated arms, introducing complex, nonlinear interactions between motor thrust and arm deformation, which make precise control challenging. The silicone arms are actuated using differential pressure to achieve flexibility and thus have a variable workspace compared to their fixed counterparts. The deflection of the soft arms during compression and expansion is controlled throughout the flight. However, in real time, the downwash from the motor attached at the tip of the soft arm generates a significant and random disturbance on the arm. This disturbance affects both the desired deflection of the arm and the overall stability of the system. To address this factor, an experimental characterization of the effect of downwash on the deflection angle of the arm is conducted. © 2025, CC BY.

关键词： Pneumatics

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