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2018 IEEE 16th International Symposium on Intelligent Systems and Informatics (SISY)最新文献

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Digital Forensics: Evidence Analysis via Intelligent Systems and Practices DigForASP - CA17124. Challenges and Achievements: Plenary Talk 数字取证:通过智能系统和实践进行证据分析。挑战与成就:全体会议
Pub Date : 2022-09-15 DOI: 10.1109/SISY56759.2022.10036257
Jesús Medina
The Action COST DigForAsp is composed of more than 250 specialists and researchers from 36 countries, which is focused on searching for and consolidating of synergies in order to face the challenges in digital forensics, improve processes and obtain more efficient results, throughout the application of Artificial Intelligence and Automatic Reasoning tools. DigForASP aims to create one of the largest European intergovernmental networks for the coordination of European scientific and technical research in Digital Forensic, under the support of the European Cooperation Program in Science and Technology (COST), funded by the European Commission, which seeks to strengthen scientific and technical research in Europe by financing the establishment of collaborative networks between researchers. In this talk, the description of digital forensic and the specific goals of the Action will be presented. Moreover, we will also pay attention to current challenges and achievements.
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引用次数: 0
Kinematic quantification of knee joint asymmetry during preparatory phase of a standing backward tucked salto 膝关节不对称的运动学量化在准备阶段的站立向后折叠salto
Pub Date : 2020-01-01 DOI: 10.1109/SISY50555.2020.9217081
Stefania Cerasela Patrascu Domokos, Andrei Dragomir, S. Mirica, M. Domokos, I. Borozan, A. Nagel, V. Argesanu
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引用次数: 0
Fuzzy Based Indoor Navigation for Mobile Robots 基于模糊的移动机器人室内导航
Máté Tóth, D. Stojcsics, Zsolt Domozi, I. Lovas
In today's world the expansion of autonomous robots is getting bigger and bigger, while in everyday life the people can meet devices which are capable of managing a wide range of tasks independently. In order to manage tasks these robots are equipped with sensors, which they use to be able to sample and analyze the parameters of their environment. The robots use obtained information to modify and help their own operation or rather its smooth running. Particular autonomous robots navigate themselves using the data utilized for their orientation and if necessary they manage obstacle avoidance in order, that the robot may reach its destination. Such sensors can be cameras too which provide image data of the robot's environment. The navigation procedure to be introduced in the article was developed for a Turtlebot robot utilizing stereo vision. The robot is modularly built. Real-time 3D reconstruction, which is the basis of navigation, is to be introduced in detail in another article yet to be published.
在当今世界,自主机器人的扩张越来越大,而在日常生活中,人们可以遇到能够独立管理各种任务的设备。为了管理任务,这些机器人配备了传感器,它们使用传感器来采样和分析环境参数。机器人使用获得的信息来修改和帮助自己的操作,或者更确切地说,它的平稳运行。特定的自主机器人使用用于定位的数据进行导航,如果必要的话,它们会按照顺序避开障碍物,使机器人能够到达目的地。这种传感器也可以是摄像头,提供机器人周围环境的图像数据。本文介绍的导航程序是为利用立体视觉的Turtlebot机器人开发的。这个机器人是模块化建造的。实时三维重建是导航的基础,将在另一篇尚未发表的文章中详细介绍。
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引用次数: 2
Cybersecurity Issues in Industrial Control Systems 工业控制系统中的网络安全问题
Z. Szabó
Incidents with a high level of damage that have been perceived worldwide increasingly indicate that compliance with international information security standards and statutory compliance, periodically revised, does not in itself mean full protection against attackers using prepared and targeted methods. When building a risk management system to address the challenge, we must be able to decide what extra solutions need to be spent money on, in addition to meeting the compliance requirements, for more effective data protection. This is not possible without the underlying threats of the particular business environment and infrastructure and the vulnerabilities of the systems involved. Today's challenges require complex cyber protection. This paper deals with security issues in industrial control systems through case studies.
全球范围内发生的严重损害事件日益表明,遵守定期修订的国际信息安全标准和法律合规性,本身并不意味着对使用准备好的和有针对性的方法的攻击者提供全面保护。在构建风险管理系统以应对这一挑战时,我们必须能够决定,除了满足合规性要求外,还需要在哪些额外的解决方案上投入资金,以实现更有效的数据保护。如果没有特定业务环境和基础设施的潜在威胁以及所涉及系统的漏洞,这是不可能的。当今的挑战需要复杂的网络保护。本文通过案例分析探讨了工业控制系统中的安全问题。
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引用次数: 2
Linked Rule-Premises to Optimize the Fuzzy-Based Risk Assessment 优化模糊风险评估的关联规则前提
E. Tóth-Laufer
In patient monitoring fuzzy-based evaluation can be used advantageously, because of its characteristics. This approach can work with input factors, for which sharp limits cannot be defined and it can handle uncertainties, subjectivity in the data as well as the evaluation process. The conventional Mamdani inference is the most suitable method, because it helps to build a model, which is much closer to human thinking, but its computational needs are very high, due to the complex-shape functions. This paper introduces a flexible patient monitoring system optimization, where the input functions can be tuned according to the personal statistics. Modified versions of the Mamdani inference are applied in this system, which can reduce computational complexity, while they retain the advantages of the original method.
基于模糊的评价方法由于其自身的特点,在患者监护中具有很好的应用前景。这种方法可以处理输入因素,因为输入因素的限制是无法明确的,它可以处理数据中的不确定性、主观性以及评估过程。传统的Mamdani推理是最合适的方法,因为它有助于建立一个更接近人类思维的模型,但由于复杂的形状函数,它的计算需求非常高。本文介绍了一种灵活的病人监护系统优化,可以根据个人统计数据调整输入功能。该系统采用了改进的Mamdani推理,在保留原方法优点的同时降低了计算复杂度。
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引用次数: 0
Netfood: A Software System for Food Ordering and Delivery Netfood:一个订餐和送餐软件系统
C. Domokos, Barna Séra, Károly Simon, L. Kovács, T. Szakács
Netfood is an order management software for food delivery companies. It is a delivery-oriented system that allows clients to order from multiple restaurants at the same time, and provides the possibility to order individually or in a group. Orders can be placed by users through the web interface. The data related to restaurants, foods and orders is managed by administrators. A mobile application is used by the delivery personnel. Both client applications are served with data by a central server. The article presents the architecture and the implementation of the software system. The technologies, tools and methods used during the development process are also described.
Netfood是一款针对外卖公司的订单管理软件。这是一个面向交付的系统,允许客户同时从多个餐厅订购,并提供单独订购或团体订购的可能性。用户可以通过web界面下单。与餐厅、食品和订单相关的数据由管理员管理。配送人员使用移动应用程序。两个客户机应用程序都由中央服务器提供数据。文章介绍了软件系统的体系结构和实现。在开发过程中使用的技术、工具和方法也进行了描述。
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引用次数: 4
Comparing Sentiment Analysis and Document Representation Methods of Amazon Reviews 亚马逊评论的情感分析和文档表示方法比较
Katic Tamara, Nemanja Milićević
In the last few years sentiment analysis has made much progress. Sentiment analysis has been used in several applications to identify the opinions of people, products, brands, services, etc., which can, for example, improve a company's business. Some of these applications claim to have more effective document representation models than merely Information Retrieval approaches like the bag-of-words representation. Document representation models have increased interest to solve some of the limitations that bag-of-words representation has. In this paper, the several sentiment analysis and document representation methods of Amazon reviews are compared. In this paper, traditional models such as a bag-of-words, bag-of-ngrams and their TF-IDF variants combined with linear classifiers such as Logistic Regression and SVM, and deep learning models such as word-based convolutional neural networks (ConvNets) and the simple long short-term memory (LSTM) recurrent neural network were used. Various document representation techniques such as Paragraph Vector or using pre-trained Word2Vec and Glove word embeddings to compute the vector for each word in the document were tested, and word vectors are aggregated using the element-wise mean. It is shown that deep learning models perform better on our large dataset than traditional models. LSTM resulted with the best accuracy of 95.55%. Deep learning models generally work better than traditional models as training set size increases. Our best performing model can be used for automatic sentiment classification for future product reviews in retail stores.
在过去的几年里,情绪分析取得了很大的进展。情感分析已经在几个应用程序中用于识别人、产品、品牌、服务等的意见,例如,可以改善公司的业务。其中一些应用程序声称具有比诸如词袋表示之类的信息检索方法更有效的文档表示模型。文档表示模型对解决词袋表示的一些限制越来越感兴趣。本文对亚马逊评论的几种情感分析和文档表示方法进行了比较。本文将传统的词袋、图袋及其TF-IDF变体模型与线性分类器(如Logistic回归和SVM)和深度学习模型(如基于词的卷积神经网络(ConvNets)和简单长短期记忆(LSTM)递归神经网络)相结合。测试了各种文档表示技术,如段落向量或使用预训练的Word2Vec和Glove词嵌入来计算文档中每个词的向量,并使用元素平均聚合词向量。研究表明,深度学习模型在我们的大数据集上比传统模型表现得更好。LSTM的准确率最高,为95.55%。随着训练集规模的增加,深度学习模型通常比传统模型工作得更好。我们表现最好的模型可以用于未来零售商店产品评论的自动情感分类。
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引用次数: 12
The Influence of the Mesh Element Size on the Natural Frequencies of Beam 网格单元尺寸对梁固有频率的影响
I. Crâstiu, Calin Pop-Gozman, S. Deac, Costel Berce, D. Simoiu, L. Bereteu
Mechanical engineering software products such as ANSYS, Catia, SolidWorks and others offer both modules for designing different components or technological processes as well as modules for simulating their dynamic behavior. Therefore, a calculation of the vibration modes and frequencies of a structure through an analytical approach is very complicated, but the numerical approach is not so complex. However, in Finite Element Analysis the mesh size of the mesh elements is closely related to the calculation speed and the required precision. The paper aims to track the effect of the size of the finite element on the natural frequencies of a beam.
机械工程软件产品,如ANSYS, Catia, SolidWorks等提供设计不同组件或技术过程的模块以及模拟其动态行为的模块。因此,通过解析方法计算结构的振动模态和频率是非常复杂的,而数值方法则不那么复杂。然而,在有限元分析中,网格单元的网格尺寸与计算速度和所需的精度密切相关。本文旨在跟踪有限元尺寸对梁固有频率的影响。
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引用次数: 2
A Model is Worth a Thousand Words? 一个模型胜过千言万语?
S. Ristić
An information system's (IS) design and implementation, beyond others, involve understanding of the social and organizational context of the system and making decisions according to the limitations of environment and technology. The open, dynamic and almost unbounded nature of contemporary environment of the ISs poses many new challenges. The need for reengineering of information systems has dramatically increased as legacy ISs are migrated to new platforms. Reengineering of an IS has the objective of extracting the contents, data structures, and flow of data and processes contained within existing legacy IS in order to reconstitute them into a new form for subsequent implementation. Inability of traditional information system (re)engineering approaches, methodologies and tools to cope with ever increasing complexity of contemporary information systems leads towards paradigm shift. Here we discuss an approach to IS (re)engineering that is based on Model-driven (MD) and Domain Specific Language paradigms. MD paradigm assumes orientation on models at all stages of system development and addresses complexity through abstraction. It promotes the idea of abstracting implementation details by focusing on: models as first class entities and automated generation of models or code from other models. MD software development approaches usually rely on Domain-Specific Languages (DSLs) that are specific to the certain domain of application. MD and DSL paradigms applied in information system (re)engineering projects increase: the development speed through automation and single point of system definition, the software quality, and component reuse. Their application reduces conceptual gap between problem domains and software implementation, improves manageability of complexity through abstraction, enables greater domain expert inclusion in the development process, and supports better communication between different stakeholders. The role of MD and DSL paradigms in information system (re)engineering is illustrated on the example of IIS*Studio development environment aimed at MD information system (re)engineering.
信息系统(IS)的设计和实现,除了其他方面,还包括对系统的社会和组织背景的理解,并根据环境和技术的限制做出决策。国际空间站当代环境的开放、动态和几乎不受限制的性质带来了许多新的挑战。随着遗留的信息系统迁移到新的平台,对信息系统重新设计的需求急剧增加。信息系统再造的目标是提取现有遗留信息系统中包含的内容、数据结构、数据流和流程,以便将它们重新构造为新的形式,以供后续实现。传统的信息系统(再)工程方法、方法和工具无法应对日益复杂的当代信息系统,这导致了范式的转变。在这里,我们讨论了一种基于模型驱动(MD)和领域特定语言范例的IS (re)工程方法。MD范式在系统开发的所有阶段都以模型为导向,并通过抽象来解决复杂性。它通过关注:作为第一类实体的模型,以及从其他模型自动生成模型或代码,促进了抽象实现细节的思想。MD软件开发方法通常依赖于特定于某个应用领域的领域特定语言(dsl)。在信息系统(再)工程项目中应用的MD和DSL范例增加了:通过自动化和单点系统定义的开发速度,软件质量和组件重用。它们的应用减少了问题域和软件实现之间的概念差距,通过抽象提高了复杂性的可管理性,支持在开发过程中包含更多的领域专家,并支持不同涉众之间更好的沟通。以针对MD信息系统(再)工程的IIS*Studio开发环境为例,说明了MD和DSL范式在信息系统(再)工程中的作用。
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引用次数: 0
Dog Breed Identification Using Deep Learning 利用深度学习识别狗的品种
Zalán Ráduly, Csaba Sulyok, Zsolt Vadászi, Attila Zolde
The current paper presents a fine-grained image recognition problem, one of multi-class classification, namely determining the breed of a dog in a given image. The presented system employs innovative methods in deep learning, including convolutional neural networks. Two different networks are trained and evaluated on the Stanford Dogs dataset. The usage/evaluation of convolutional neural networks is presented through a software system. It contains a central server and a mobile client, which includes components and libraries for evaluating on a neural network in both online and offline environments.
本文提出了一个细粒度图像识别问题,即多类分类问题之一,即在给定图像中确定狗的品种。该系统采用了深度学习的创新方法,包括卷积神经网络。在斯坦福狗的数据集上训练和评估了两个不同的网络。通过一个软件系统介绍了卷积神经网络的使用和评价。它包含一个中央服务器和一个移动客户端,其中包括用于在线和离线环境下对神经网络进行评估的组件和库。
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引用次数: 15
期刊
2018 IEEE 16th International Symposium on Intelligent Systems and Informatics (SISY)
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