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29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Abadía, José Joaquín Peralta Barrenechea, Felix Larrinaga Zabaljauregui, Mikel Cuesta Aiestaran, Xabier Badiola Zubiaurre, Aitor Duo Mendia, Gorka Olalde Lázare, Txema Pérez Mondragon Goi Eskola Politeknikoa Software and System Engineering Research Group Arrasate Spain Mondragon Goi Eskola Politeknikoa High Performance Machining Research Group Arrasate Spain Mondragon Goi Eskola Politeknikoa Electronic Power Systems Applied to the Control Electric Energy Research Group Arrasate Spain Mondragon Goi Eskola Politeknikoa Data Analysis and Cybersecurity Research Group Arrasate Spain

ISBN: (纸本)9798350361230

The manufacturing industry is constantly seeking innovative solutions to optimize machining processes. However, there is a lack of efficient digital platforms that fully meet the flexibility, service composition, and affordability needs of the manufacturing industry, in particular for small and mediumsized enterprises (SMEs). This paper introduces the OptiTwin platform, a novel data-driven system designed to enhance machining process optimization for SMEs. The OptiTwin platform was developed with a focus on data acquisition, management, and analysis based on data driven models. The functionalities of the platform were validated through a drilling use case at Mondragon University's high-performance machining laboratory, demonstrating its effectiveness in real-time tool condition monitoring. The results showcase the potential of OptiTwin in optimizing machining processes and empowering SMEs with data-driven insights for enhanced productivity and quality assurance. © 2024 IEEE.

关键词： Machining centers

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Fault management based on peer-to-peer paradigms

Fault management based on peer-to-peer paradigms

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10th IFIP/IEEE International Symposium on Integrated Network Management 2007, IM '07

作者： Leitner, Markus Leitner, Philipp Zach, Martin Collins, Sandra Fahy, Claire PSE-Program and System Engineering Siemens AG Austria Vienna Austria Ericsson RandD Ireland Network Management Research Centre Dublin Ireland TSSG-Telecommunications Software and Systems Group Waterford Institute of Technology Waterford Ireland

ISBN: (纸本)1424407990

We present an approach to fault management based on an architecture for distributed and collaborative network management as developed in the CELTIC project Madeira. It uses peer-to-peer communication facilities and a logical overlay network facilitating decentralized and iterative alarm processing and correlation. We argue that such an approach might help to overcome key challenges that are posed by NGN scenarios to traditional centralized network management systems. Its feasibility is demonstrated by means of a case study from the area of wireless mesh networks, where an application prototype has been developed. © 2007 IEEE.

关键词： Distributed computer systems

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Automatic Chest Radiology Report Generation Using Reinforcement Learning 7th

Automatic Chest Radiology Report Generation Using Reinforcem...

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7th International Conference on Intelligent Technologies, ICIT 2022

作者： Kourav, Mohit Agarwal, Saurabh Arya, K.V. Petrlik, Ivan Rodriguez, Ciro Multimedia and Information Security Research Group ABV-Indian Institute of Information Technology & Management Gwalior India Faculty of System Engineering Universidad Nacional Federico Villarreal Lima Peru Faculty of Software Engineering Universidad Nacional Mayor de San Marcos Lima Peru

ISBN: (纸本)9789819919116

Radiology report generation is the manual task assigned to radiologists which analyze the given chest image (x-ray) of patient and generates the report based on that analysis. Many of the research is undergoing in this field to make this process automatic. However, there are a large number of difficulties which have been faced by the researchers while developing the efficient automatic report generation model. The main difficulties include the generation of clinically inaccurate reports when analyzed with the reports of the expert radiologist. The introduction of deep learning based approaches achieved tremendous advancement in these areas and can produce chest X-ray reports in a more accurate manner. BY further optimizing the deep learning based approaches, we proposed a reinforcement learning-based model that generates automated X-ray reports based on input chest X-ray images. We also developed a lookahead inference mechanism to overcome the limitation of beam search, which selects words based on policy and value networks at each particular step of time. The proposed model achieved 0.454, 0.546, 0.466, 0.410, and 0.424 for the Bleu-1, Bleu-2, Bleu-3, Bleu-4, and Rouge evaluation metrics, respectively, surpassing all available state-of-the-art algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Reinforcement learning

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Fighting class name clashes in Java component systems

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2003年 2789卷 106-109页

作者： Hnětynka, Petr Tůma, Petr Distributed System Research Group Department of Software Engineering Charles University Malostranske namesti 25 118 00 Prague 1 Czech Republic

This paper deals with class and interface name clashes in Java component systems that occur because of evolutionary changes during the lifecycle of a component application. We show that the standard facilities of the Java type system do not provide a satisfactory way to deal with the name clashes, and present a solution based on administering the names of classes and interfaces with a version identifier using a byte code manipulation tool. We provide a proof of concept implementation. © Springer-Verlag Berlin Heidelberg 2003.

关键词： Java programming language

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ROUGH CLUSTERING FOR CANCER DATASETS

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International Journal of Modern Physics: Conference Series 2012年第9期ijmpcs卷 240-258页

作者： TUTUT HERAWAN Database and Knowledge Management Research Group Faculty of Computer System and Software Engineering Universiti Malaysia Pahang Lebuh Raya Tun Razak Gambang 26300 Pahang Malaysia

Cancer is becoming a leading cause of death among people in the whole world. It is confirmed that the early detection and accurate diagnosis of this disease can ensure a long survival of the patients. Expert systems and machine learning techniques are gaining popularity in this field because of the effective classification and high diagnostic capability. This paper presents the application of rough set theory for clustering two cancer datasets. These datasets are taken from UCI ML repository. The method is based on MDA technique proposed by [11]. To select a clustering attribute, the maximal degree of the rough attributes dependencies in categorical-valued information systems is used. Further, we use a divide-and-conquer method to partition/cluster the objects. The results show that MDA technique can be used to cluster to the data. Further, we present clusters visualization using two dimensional plot. The plot results provide user friendly navigation to understand the cluster obtained.

关键词： Clustering rough set MDA technique cancer datasets

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Finding Database Contention Hotspots under Large-Scale Workloads——A Big Data Approach

Finding Database Contention Hotspots under Large-Scale Workl...

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2016 IEEE International Conference on Big Data Analysis

作者： An Lei Ping Sun Weixiong Rao Hong Min Gong Su Zhenhua Dong School of Software Engineering Tongji University IBM T.J.Watson Research Center IBM System and Technology Group

Database plays an important role in transactional information systems. One significant performance impacting factor is data lock contention in transaction processing. In order to guide betterdatabase design, we propose a novel solution to identify contention hotspots displayed in DBMS transaction logs. To analyze the large volume of data collected in the transaction log, our solution employees bigdata engine Spark for better computation performance and scalability. A novel algorithm is also introduced to optimize computation for analyzing hotspots in the distributed cluster. The experimental results from a benchmark OLTP workload demonstrate the effectiveness and high scalability of our solution.

关键词： database contention relation database system transaction log Spark

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SOFT SET-BASED DECISION MAKING FOR PATIENTS SUSPECTED INFLUENZA-LIKE ILLNESS

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International Journal of Modern Physics: Conference Series 2012年第9期ijmpcs卷 259-270页

In previous work, we presented an applicability of soft set theory for decision making of patients suspected influenza. The proposed technique is based on maximal supported objects by parameters. At this stage of the research, results are presented and discussed from a qualitative point of view against recent soft decision making techniques through an artificial dataset. In this paper, we present an extended application of our soft set-based decision making through a Boolean valued information system from a dataset of patients suspected ILI (Influenza-Like Illness). Using soft set theory and maximal symptoms co-occurences in patients, we explore how soft set-based decision making technique can be used to reduce the number of dispensable symptoms and further make a correct and fast decision. The result of this work can be used for recommendation of decision making based on the clusters decision captured. Finally, this technique may potentially contribute to lowering the complexity of medical decision making without loss of original information.

关键词： Decision making soft set theory ILI dataset

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LIR-OSGi: Extends OSGi to support distributed and heterogeneous ubiquitous computing system

LIR-OSGi: Extends OSGi to support distributed and heterogene...

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2011 6th International Conference on Pervasive Computing and Applications, ICPCA 2011

作者： Liu, Jinzhao Lu, Xiaojuan Wang, Dan Liu, Xin Lu, Yongqiang Chen, Yu Dept. of Computer Science and Technology Beijing University of Technology Beijing China General Hospital PLA Second Artillery China Research Institute of Information Technology Key Laboratory of Pervasive Computing Ministry of Education Beijing China System Software and Software Engineering Group Laboratory of Pervasive Computing Dept. of Computer Science and Technology Beijing 100084 China

ISBN: (纸本)9781457702082

As an emerging portable service platform, OSGi is now taking a more and more important role in Ubiquitous Computing environment. As a module management framework, OSGi provides the functions of dynamic loading and unloading software modules at runtime. But its use is limited because it is centralized and single programming language supported. In this paper we present LIR-OSGi, an extended framework of OSGi, which is designed to add the distribution and programming language independence to OSGi. Meanwhile it is easy to use for developers because of the transparence of service invocation and automation of distribution. Not like OSGi which can be applied only on the Java platform, LIR-OSGi makes programs which may be written in different programming languages be able to call each other transparently so that it can be applied in many different platforms such as DotNet Framework and so on. This brings much convenience to the program development in a distributed and heterogeneous environment. © 2011 IEEE.

关键词： Middleware

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Teaching software engineering from a collaborative perspective: Some Latin-American experiences

Teaching software engineering from a collaborative perspecti...

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21st International Workshop on Database and Expert systems Applications, DEXA 2010

作者： Giraldo, Fáber D. Collazos, César A. Ochoa, Sergio F. Zapata, Sergio De Clunie, Gisela Torres System and Computer Engineering Department University of Quindío Armenia IDIS Research Group University of Cauca Popayan Colombia Computer Science Department University of Chile Santiago Chile Informatics Institute National University of San Juan San Juan Argentina Software Engineering Department Technological University of Panama Panama City Panama

ISBN: (纸本)9780769541747

Teaching software engineering has been recognized as an important challenge for computer science undergraduate programs. Instruction in such area requires not only to deliver theoretical knowledge, but also to perform practical experiences that allow students to assimilate and apply such knowledge. This paper presents some results of two Computer-Supported Collaborative Learning (CSCL) experiences that involved students of software engineering courses from four Latin American Universities. The obtained results were satisfactory and indicate the reported collaborative activity could be appropriate to address teaching software engineering. © 2010 IEEE.

关键词： E-learning

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Application-level security for ROS-based applications

Application-level security for ROS-based applications

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Bernhard Dieber Severin Kacianka Stefan Rass Peter Schartner ROBOTICS institute at JOANNEUM RESEARCH Austria Software Engineering Group at the Technical University of Munich Germany System Security Group in the Institute of Applied Informatics at the Alpen-Adria-University Klagenfurt Austria

ISBN: (纸本)9781509037636

While the topic of security in industrial applications has gained some momentum in recent years, there are still severe security vulnerabilities which are actively exploited for attacks. The robot operating system (ROS) is expected to further grow in usage and to be used in many industrial applications. Analysis, however, shows that it lacks several security enhancements in order to make it suitable for industrial use. In its current state, false data and commands can be injected posing a possible safety risk for the resulting product and humans in the production. In addition, data may be eavesdropped and used by outsiders to gain insight into the production process. In this paper we propose a security architecture intended for use on top of ROS on the application level. We use a dedicated authorization server to ensure that only valid nodes are part of the application. Cryptographic methods ensure data confidentiality and integrity. We show in a demonstration with a collaborative robot how our architecture can be used to secure a ROS-based application.

关键词： Cryptography Authentication Production Digital signatures Service robots

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