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2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)最新文献

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Collision-Free Navigation Using Laser Scanner and Tablet Computer for an Omni-Directional Mobile Robot System with Active Casters 基于激光扫描仪和平板电脑的主动脚轮全方位移动机器人系统无碰撞导航
Jae Hoon Lee, Katsunori Tanaka, S. Okamoto
A novel mobile system for effective object transportation was developed in this paper. By installing the proposed multiple double-wheel-type active casters to an object, the system itself becomes an omni-directional mobile robot that can be controlled with a tablet computer in a teleoperation manner. Each active caster was designed as an independent module having a micro-computer to control motors of both wheels; a Bluetooth communication component to connect with a tablet computer; a battery as a power source and so on. The operator's command for the desired motion of the main platform is transformed into an appropriate velocity command for each wheel based on the kinematic relationship between the object and the wheel coordinates. Collision avoidance navigation algorithm with a laser scanner attached to the object and a user interface with a tablet computer are also proposed for safe usage in real fields. The developed system and the collision avoidance algorithm were demonstrated through experiments.
本文提出了一种新型的移动物体有效运输系统。通过将所提出的多个双轮型主动脚轮安装到一个物体上,系统本身就变成了一个全方位的移动机器人,可以用平板电脑进行远程操作控制。每个主动脚轮被设计成一个独立的模块,有一个微型计算机来控制两个轮子的电机;蓝牙通信组件,用于与平板电脑连接;电池作为电源等等。根据物体与车轮坐标之间的运动关系,将操作人员对主平台期望运动的指令转换为对每个车轮适当的速度指令。为了在实际环境中安全使用,还提出了在物体上附加激光扫描仪的避碰导航算法和带有平板电脑的用户界面。通过实验验证了所开发的系统和避碰算法。
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引用次数: 2
On Certain Properties of Vague Relational Databases 模糊关系数据库的若干性质
Dženan Gušić, Z. Šabanac, Sanela Nesimović
This paper represents a natural continuation of our previous study. In our earlier research we proved that the inclusive inference rule and the union inference rule for new vague functional dependencies are sound, and sketched a proof of the fact that the set of the main inference rules is a complete set. In the present paper we rigorously prove that: reflexive, augmentation, transitivity, pseudo-transitivity, and decomposition inference rules are also sound. Some additional insights in completeness of the main inference rules are also provided.
这篇论文是我们以前研究的自然延续。在之前的研究中,我们证明了新的模糊功能依赖的包含推理规则和并推理规则是可靠的,并初步证明了主推理规则集是完备集。本文严格证明:自反性、增广性、及物性、伪及物性和分解推理规则也是健全的。还提供了关于主要推理规则完整性的一些附加见解。
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引用次数: 2
Introducing CrowdMapping: A Novel System for Generating Autonomous Driving Aiding Traffic Network Databases CrowdMapping:一种辅助自动驾驶交通网络数据库生成的新系统
M. Szántó, L. Vajta
High definition maps of the road networks and the roads' environment have proven to be utterly useful for autonomous driving. Such maps can prove to be useful for the autonomous vehicle for numerous purposes - e.g. preliminary route planning, danger preparation and avoidance, etc. However, producing sufficient data for such maps can be costly because of the high variability of road conditions in the time domain and depending on the load of the elements of the given piece of transport infrastructure - i.e. road loads. In this paper, the CrowdMapping architecture is introduced, which presents a novel framework developed for the generation of an extensive and high definition road database, exploiting the opportunities offered by crowdsourcing, image processing, and cloud computing. State-of-the-art research is presented in the fields related to the development of the functions of the CrowdMapping framework. The currently ongoing research and development activities linked to CrowdMapping carried out at the Budapest University of Technology and Economics are also listed in chapter III. of this paper, as well as the future work possibilities, which are listed in chapter IV.
事实证明,道路网络和道路环境的高清地图对自动驾驶非常有用。这样的地图可以被证明对自动驾驶汽车有很多用途——例如,初步路线规划、危险准备和避免等。然而,为这种地图制作足够的数据可能是昂贵的,因为道路条件在时域上的高度可变性,并且取决于给定运输基础设施的要素的负载-即道路负载。本文介绍了CrowdMapping架构,该架构利用众包、图像处理和云计算提供的机会,为生成广泛且高清的道路数据库提供了一个新的框架。在与CrowdMapping框架的功能开发相关的领域中展示了最新的研究成果。第三章还列出了布达佩斯科技经济大学目前正在进行的与CrowdMapping相关的研究和开发活动。以及未来工作的可能性,这些在第四章中列出。
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引用次数: 6
Forecasting Corporate Revenue by Using Deep-Learning Methodologies 利用深度学习方法预测公司收入
Kostadin Mishev, Ana Gjorgjevikj, I. Vodenska, Ljubomir T. Chitkushev, W. Souma, D. Trajanov
In the past few years, deep learning evolved into a powerful machine learning technique, which uses multiple layers for feature representation to learn specific attitudes of the raw input data, in order to produce state of the art prediction results. Deep learning has become popular in many application domains which use rich variety of data. Large volumes of online business news provide an opportunity to explore various aspects of companies. Sentiment analysis of text establishes a new viewpoint of large scale data identifying, among other features, the tone of the author towards the subject of the text. Hence, the sentiment of news articles offers an insight into the internal state of the company, potential for revenue growth, and it can be useful for corporate decision making of the company. In this paper, we demonstrate a deep convolution LSTM neural network that uses a fusion of data including company stock price and sentiment of company-related news articles as time-series, in order to predict the revenue growth or decline of the companies belonging to the Dow Jones Industrial Average. Additionally, we present a method based on transfer learning for sentiment analysis of news articles related to finances, and compare this method with standard statistical sentiment analysis approaches.
在过去的几年里,深度学习发展成为一种强大的机器学习技术,它使用多层特征表示来学习原始输入数据的特定态度,以产生最先进的预测结果。深度学习已经在许多使用丰富数据的应用领域中流行起来。大量的在线商业新闻为探索公司的各个方面提供了机会。文本情感分析建立了一种大规模数据识别的新观点,其中包括作者对文本主题的语气。因此,新闻文章的情绪提供了一个洞察公司的内部状态,收入增长的潜力,它可以为公司的企业决策有用。在本文中,我们展示了一个深度卷积LSTM神经网络,它使用包括公司股票价格和公司相关新闻文章情绪在内的数据融合作为时间序列,以预测道琼斯工业平均指数公司的收入增长或下降。此外,我们提出了一种基于迁移学习的方法,用于金融相关新闻文章的情感分析,并将该方法与标准的统计情感分析方法进行了比较。
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引用次数: 7
Surface Roughness Optimization of Poly-Jet 3D Printing Using Grey Taguchi Method 基于灰色田口法的Poly-Jet 3D打印表面粗糙度优化
K. Aslani, F. Vakouftsi, John (Ioannis) D. Kechagias, N. Mastorakis
In the current study, the surface finish of specimens fabricated with PolyJet 3D Printing Direct process is discussed. Three surface roughness indicators were measured at three positions, while three process parameters namely layer thickness, build style and scale were examined. An L4 orthogonal array was employed for the design of experiments. Grey-Taguchi method was applied in order to optimize all surface roughness parameters. The effect of each parameter has been investigated using ANOM (Analysis of Means), while ANOVA (Analysis of Variances) has been performed to identify each parameter importance onto the surface texture. Additionally, the findings of this study were compared with the results of a similar optimization study conducted before, using the usual Taguchi method. It was concluded that 16 µm of layer thickness and glossy style provide the optimum surface roughness results, while built style is the most dominant factor. All the results of the Grey Taguchi method are compatible with the ones of the usual Taguchi method.
本研究主要讨论了PolyJet 3D Printing Direct工艺制备样品的表面光洁度。在三个位置测量了三个表面粗糙度指标,同时检查了三个工艺参数,即层厚,构建风格和尺度。采用L4正交阵列进行试验设计。采用灰色田口法对各表面粗糙度参数进行优化。使用ANOM(均值分析)研究了每个参数的影响,而使用ANOVA(方差分析)来确定每个参数对表面纹理的重要性。此外,本研究的结果与之前使用常用的田口方法进行的类似优化研究的结果进行了比较。结果表明,16µm的层厚和光面样式提供了最佳的表面粗糙度结果,而构造样式是最主要的因素。灰色田口法的结果与常用田口法的结果基本一致。
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引用次数: 16
Motion Based Masking of a Moving Vehicle's Environment 基于运动掩蔽的移动车辆环境
Tamás Mészégető, Benedek Tass, M. Szántó
The problem of autonomous vehicle navigation requires the use of high-definition and well-maintained maps. Such a map can be constructed using the method developed for the so-called CrowdMapping architecture. This paper proposes a method for constructing masks for such map creation purposes via segmenting dynamic and static regions of an image sequence. The segmentation is performed by comparing a calculated and a predicted optical flow field. The proposed segmentation algorithm contains a single image depth estimation part for predicting the expected optical flow field. The comparison method of the two flow fields is also presented in this paper. The proposed method has been evaluated both qualitatively and quantitatively using the KITTI vision dataset, and achieved a filtering error of 7…12% compared to manually prepared ground truth images.
自动驾驶汽车导航的问题需要使用高清和维护良好的地图。这种地图可以使用为所谓的“众图”架构开发的方法来构建。本文提出了一种通过分割图像序列的动态和静态区域来构建这种地图创建目的的掩模的方法。通过比较计算光流场和预测光流场来进行分割。该分割算法包含一个图像深度估计部分,用于预测期望的光流场。本文还提出了两种流场的比较方法。利用KITTI视觉数据集对该方法进行了定性和定量评估,与人工制备的地面真实图像相比,该方法的滤波误差为7…12%。
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引用次数: 0
Accurate Object Detection System on HoloLens Using YOLO Algorithm 基于YOLO算法的全息透镜精确目标检测系统
Haythem Bahri, D. Krčmařík, J. Kočí
We demonstrate in our paper, an implementation on Microsoft HoloLens, deep learning supported in the context of object detection. The main aim of this system is to create the more accurate object detection model for Augmented Reality using communication between the deep learning processing and the Microsoft HoloLens as Input/Output device. This system aims to help the wearable device user to detect and to recognize between objects in real world. For the object detection approach, a deep learning model has been used for the implementation of this system called YOLO. This model is near to real-time and it supports to detect more than 9000 objects. Our system provides the annotation of augmented object detected and its limitation area or bounding box via HoloLens. It allows to detect the new position of moving object in a few milliseconds. Preliminary results show a great rate of object detection with a detection time comparable.
在我们的论文中,我们展示了在微软HoloLens上的实现,在目标检测的背景下支持深度学习。该系统的主要目的是利用深度学习处理和微软HoloLens作为输入/输出设备之间的通信,为增强现实创建更准确的对象检测模型。该系统旨在帮助可穿戴设备用户检测和识别现实世界中的物体。对于目标检测方法,使用了一个称为YOLO的深度学习模型来实现该系统。该模型接近实时,支持检测9000多个目标。我们的系统通过HoloLens对检测到的增强物体及其限制区域或边界框进行标注。它可以在几毫秒内检测到移动物体的新位置。初步结果表明,该方法的目标检测率与检测时间相当。
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引用次数: 19
Development Methodology of Reconfigurable Robotic Systems. Application to BROS Project 可重构机器人系统的开发方法。申请BROS项目
Mohamed Oussama Ben Salem, O. Mosbahi
This research paper proposes a methodology to develop reconfigurable robotic systems. This methodology aims at guaranteeing the safety of such systems from their design to their implementation, and passing through verification. We apply the contribution to BROS (Browser-based Reconfigurable Orthopedic Surgery), a real robotic system.
本文提出了一种开发可重构机器人系统的方法。该方法旨在保证此类系统从设计到实施并通过验证的安全性。我们将贡献应用于BROS(基于浏览器的可重构骨科手术),一个真实的机器人系统。
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引用次数: 0
Fluid Flow Sensors Design Based on Electromagnetic Drag Effect 基于电磁阻力效应的流体流量传感器设计
K. Zeyde, V. Sharov
In this paper, we describe the possibility of establishing the effect of electromagnetic drag on the microwave range. We are conducting an initial study of the use of this effect for novel fluid flow sensors designing. Two different experimental stands on circular and rectangular waveguides are considered. The study is carried out using a vector network analyzer at frequencies of 8-12 GHz (X-band). Distilled water is used as a moving medium. The experiment is optimized on the basic parameters (including the temperature of the liquid) to obtain the maximum magnitude of the target observation effect. As an optimization criterion, the difference of the arrival phase of two coherent waves propagating in identical media is used, one of which has a translational motion, and the second is at rest. In conclusion, findings are presented describing the main optimization results. The principle of detecting the effect of drag on guided waves in the transmission lines is set. As a sensor test experiment, a scheme using a signal analyzer is provided.
在本文中,我们描述了建立电磁阻力对微波范围影响的可能性。我们正在对利用这种效应设计新型流体流量传感器进行初步研究。考虑了圆波导和矩形波导两种不同的实验台。该研究使用频率为8-12 GHz (x波段)的矢量网络分析仪进行。蒸馏水被用作流动介质。实验对基本参数(包括液体温度)进行优化,以获得最大量级的目标观测效果。采用在同一介质中传播的两个相干波的到达相位之差作为优化准则,其中一个具有平移运动,另一个具有静止运动。最后,给出了优化的主要结果。提出了在传输线中检测阻力对导波影响的原理。作为传感器测试实验,提出了一种采用信号分析仪的方案。
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引用次数: 2
Artificial Intelligence in Audit and Accounting: Development, Current Trends, Opportunities and Threats - Literature Review 人工智能在审计和会计:发展,当前趋势,机遇和威胁-文献综述
Aneta Zemánková
The aim of this paper is to analyze the current situation regarding artificial intelligence in audit and accounting, including the newest trends, opportunities and threats. Due to its innovative character, this field is constantly changing, with the biggest companies investing enormous amounts of capital to achieve wide use of artificial intelligence in audit and accounting. One of the main goals of the paper is to provide an analysis of audit tasks that benefit from artificial intelligence implementation, with an emphasis on risk assessment. Another goal is to outline artificial intelligence technologies used in audit and accounting. The most practical purpose of the paper is to evaluate the current applications and audit tools developed by Big4 companies, the four leading consulting companies in audit and accounting. The results of the paper include overview of seven essential audit tasks proving the significance of using artificial intelligence in accounting and audit process. The research also confirmed that the technologies most commonly used are genetic algorithms and programming, fuzzy systems, neural networks and hybrid systems, the combination of the aforementioned technologies, with the synthesis of expert systems and neural networks proven to be the most successful. Finally, the practical result of this paper is a summary of the Big4 latest developed artificial intelligence tools and innovations, mainly for audit planning, benchmarking and documents analysis.
本文的目的是分析人工智能在审计和会计领域的现状,包括最新的趋势、机会和威胁。由于其创新性,这一领域不断变化,最大的公司投入了大量资金来实现人工智能在审计和会计中的广泛应用。本文的主要目标之一是对受益于人工智能实施的审计任务进行分析,重点是风险评估。另一个目标是概述在审计和会计中使用的人工智能技术。本文最实际的目的是评估Big4公司(审计和会计领域的四大领先咨询公司)目前开发的应用程序和审计工具。本文的结果包括概述了七项基本审计任务,证明了在会计和审计过程中使用人工智能的重要性。研究还证实,最常用的技术是遗传算法和编程、模糊系统、神经网络和混合系统,上述技术的结合,专家系统和神经网络的综合被证明是最成功的。最后,本文的实践成果是对Big4最新开发的人工智能工具和创新进行总结,主要用于审计规划、对标和文件分析。
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引用次数: 9
期刊
2019 International Conference on Control, Artificial Intelligence, Robotics & Optimization (ICCAIRO)
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