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Dragonfly: linking conceptual and implementation architectures of multiuser interactive systems 00

Dragonfly: linking conceptual and implementation architectur...

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proceedings of the 22nd international conference on Software engineering

作者： Gary E. Anderson T. C. Nicholas Graham Timothy N. Wright Department of Computing and Information Science Queen's University Kingston Ontario Canada Department of Computer Science University of Canterbury Private Bag 4800 Christchurch New Zealand

ISBN: (纸本)9781581132069

Software architecture styles for developing multiuser applications are usually defined at a conceptual level, abstracting such low-level issues of distributed implementation as code replication, caching strategies and concurrency control policies. Ultimately, such conceptual architectures must be cast into code. The iterative design inherent in interactive systems implies that significant evolution will take place at the conceptual level. Equally, however, evolution occurs at the implementation level in order to tune performance. This paper introduces Dragonfly, a software architecture style that maintains a tight, bidirectional link between conceptual and implementation software architectures, allowing evolution to be performed at either level. Dragonfly has been implemented in the Java-based Telecomputing Developer (TCD) toolkit.

关键词： software architecture user interface development toolkits groupware

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A Large-scale Non-standard English Database and Transformer-based Translation System

A Large-scale Non-standard English Database and Transformer-...

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IEEE international conference on Trust, Security and Privacy in computing and Communications (TrustCom)

作者： Arghya Kundu Uyen Trang Nguyen York University Toronto Canada

ISBN: (数字)9798350381993

ISBN: (纸本)9798350382006

Natural language processing (NLP) applications face challenges in understanding and processing region or industry specific language. In real-world scenarios, conversational language used in blogs and social media platforms often contains slang and non-standard words (SNSW). These unconventional terms are not typically present in curated datasets used to train NLP models. As a consequence, the performance of these models is negatively affected when they encounter such real-world linguistic variations. In this paper, we introduce SNSW-DB, an automatically curated, regularly updated, large-scale lexical database from crowdsourced dictionaries. The database contains SNSW terms, example sentences, and their standard English synonyms generated by our synonym generator module. We also propose a transformer-based translation system that converts articles with SNSW to standard English. Translated documents enhance readability and utility for human readers, and can improve the performance of downstream NLP tasks.

关键词： Dictionaries Databases Social networking (online) Predictive models Linguistics Transformers Natural language processing

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Building NLP Tools to Process Sinhala Text Data Written using English Letters

Building NLP Tools to Process Sinhala Text Data Written usin...

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international conference on Advances in ICT for Emerging Regions

作者： W.S.A. Kurera R.K. Rajapaksha H.A.P. Rupasinghe K.L.D.U.B. Liyanage Sanvitha Kasthuriarachchi Samantha Rajapakshe Faculty of Computing SLIIT Malabe Sri Lanka

Sri Lanka is a country where the Sinhala and English languages take a prominent place, but most people are not so fluent in the two languages when using digital platforms like social media. Although most of the Sri Lankans use Singlish there is no proper application to translate the relevant language into the main two languages, Sinhala or *** purpose of this research is to bring more attention of the researchers towards the sub varieties of Sinhala language, especially Singlish by bridging the gap between NLP tools available for processing textual data of main languages and their varieties. And each component focuses on translating Singlish text data into English, translating Singlish into Sinhala, sentiment analysis for Singlish text data and mapping emojis for Singlish *** are language translation tools to translate many languages like Russian, Italian, Japanese into the English Language but there are no proper tools to translate the mainly used sublanguage in Sri Lanka; that is Singlish. Therefore, the proposed solution for the above problem is developing a Singlish to English Language Translation Model and removing slang words to allow NLP technologies created for English to be utilized to handle Singlish textual *** NLP model shall have the capacity of translating Singlish words that are used on social media into English and if there are any slang words found during the translation, those words will be identified and removed. Translating the Singlish textual data into English would help the users to use other tools built to plagiarize, tools that are used to summarize and tools that are used to paraphrase English text.

关键词： Sentiment analysis Social networking (online) Buildings Data models

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Scalable and Efficient Data Streaming Algorithms for Detecting Common Content in Internet Traffic

Scalable and Efficient Data Streaming Algorithms for Detecti...

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international conference on Data Engineering Workshops

作者： Minho Sung A. Kumar Li Li Jia Wang Jun Xu College of Computing Georgia Institute of Technology USA Bell Laboratories Lucent Technologies Inc. USA AT and T Research Laboratories USA

Recent research on data streaming algorithms has provided powerful tools to efficiently monitor various characteristics of traffic passing through a single network link or node. However, it is often desirable to perform data streaming analysis on the traffic aggregated over hundreds or even thousands of links/nodes, which will provide network operators with a holistic view of the network operation. Shipping raw traffic data to a centralized location (i.e., “raw aggregation”) for streaming analysis is clearly not a feasible approach for a large network. In this paper, we propose a set of novel distributed data streaming algorithms that allow scalable and efficient monitoring of aggregated traffic without the need for raw aggregation. Our algorithms target the specific network monitoring problem of finding common content in the Internet traffic traversing several nodes/links, which has applications in network-wide intrusion detection, early warning for fast propagating worms, and detection of hot objects and spam traffic. We evaluate our algorithms through extensive simulations and experiments on traffic traces collected from a tier-1 ISP. The experimental results demonstrate that our algorithms can effectively detect common content in the traffic traversing across a large network.

关键词： Internet Telecommunication traffic Traffic control Signal processing algorithms Aggregates IP networks Event detection Intrusion detection Condition monitoring Data processing

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Line selection strategy for a beneficial DLR system based on international project experience

Line selection strategy for a beneficial DLR system based on...

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22nd international Symposium on High Voltage Engineering (ISH 2021)

作者： D. Szabó L. Rácz G. Göcsei B. Németh Department of Electric Power Engineering Faculty of Electrical Engineering and Informatics Budapest University of Technology and Economics Budapest Hungary

System operators have to face several technical, economic, and system-level control challenges during the operation of high voltage distribution- and transmission lines. The progressively increasing energy demand, the spread of distributed generation, aspiration for an integrated energy market (IEM) formation, intermittent generation of renewable energy sources, continuous supply constraint of the consumers or the capital-intensive and prolonged investments in case of new infrastructure constructions also belong to this challenging problem area. Dynamic line rating (DLR) is a state-of-the-art methodology for uprating power lines, as this technique monitors the thermal behaviour of the overhead lines' phase conductors. On the other hand, a complex line monitoring expert system can be established based on the infrastructural and computational background required for the implementation of a DLR system. In this way, not only the real-time ampacity of the power lines can be calculated, but a DLR-based expert system also provides an opportunity for predetermined transmission capacity calculation, tracking of conductor temperature, monitoring of sag-clearance variation of the conductors, or forecast icing events with the determination of anti-icing current. Implementing a DLR-based expert system is preceded by different preparatory processes, which are essential during the system-level approach. The first phase of any internal or international DLR project is selecting power lines, on whose line monitoring system can be applied effectively. One purpose of this article is to present a complex line selection strategy including the specialties of the investigated network such as historical load duration curves, load limiting machinery in the substations, archive icing events, or different strategic aspects that highly affect the economic return, efficiency and operational safety of such a system. Another important aspect in the preparatory process of a DLR system implementatio

关键词： distributed power generation expert systems ice investment overhead line conductors power engineering computing power generation economics power grids power markets power overhead lines power transmission economics renewable energy sources substations

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Big Data Processing and Artificial Intelligence at the Network Edge

Big Data Processing and Artificial Intelligence at the Netwo...

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international conference on Transparent Optical Networks

作者： J. J. Vegas Olmos Filippo Cugini Fred Buining Niamh O'Mahony Thuy Truong Liran Liss Tzahi Oved Zac Binshtock Dror Goldenberg Mellanox Technologies Hakidma 23 Yokneam Israel Conzorcio Nazionale Interuniversitario per le Telecommunicazione (CNIT) National Lab of Photonic Networks via G. Moruzzi 1 Pisa Italy Hiro MicroDataCenter Voorburg The Netherlands Dell EMC Cork Ireland

ISBN: (数字)9781728184234

ISBN: (纸本)9781728184241

The delivery of computing services - including storage, databases, networking, software, analytics, intelligence and more is moving from the cloud towards the edge; among all technical requirements, the edge needs to be able to natively support artificial intelligence processes to enable new technological paradigms, such as smart Factory 4.0, healthcare assisted living, smart cities and advanced robotics, for example. In this paper, we will present the enabling technologies to will be developed within the “Big data processing and artificial intelligence at the network edge” (BRAINE) project, one of the largest joint activities in Europe in the area of edge computing enabling artificial intelligence. BRAINE covers the full stack of a system solution, from subsystem integration up to artificial intelligence service provisioning, and includes four use cases of direct impact in the European ecosystem.

关键词： Edge computing Artificial intelligence Switches Hardware Software Cooling Europe

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Performance evaluation of Apache Hadoop and Apache Spark for parallelization of compute-intensive tasks 20

Performance evaluation of Apache Hadoop and Apache Spark for...

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proceedings of the 22nd international conference on Information Integration and Web-based Applications & Services

作者： Alexander Döschl Max-Emanuel Keller Peter Mandl HM Hochschule München University of Applied Sciences Munich Germany

ISBN: (纸本)9781450389228

There have been numerous studies that have examined the performance of distribution frameworks. Most of these studies deal with the processing of large amounts of data. This work compares two of these frameworks for their ability to implement CPU-intensive distributed algorithms. As a case study for our experiments we used a simple but computationally intensive puzzle. To find all solutions using brute-force search, 15! permutations had to be calculated and tested against the solution rules. Our experimental application was implemented in the Java programming language using a simple algorithm and having two distributed solutions with the paradigms MapReduce (Apache Hadoop) and RDD (Apache Spark). The implementations were benchmarked in Amazon-EC2/EMR clusters for performance and scalability measurements, where the processing time of both solutions scaled approximately linearly. However, according to our experiments, the number of tasks, hardware utilization and other aspects should also be taken into consideration when assessing scalability. The comparison of the solutions with MapReduce (Apache Hadoop) and RDD (Apache Spark) under Amazon EMR showed that the processing time measured in CPU minutes with Spark was up to 30 % lower, while the performance of Spark especially benefits from an increasing number of tasks. Considering the efficiency of using the EC2 resources, the implementation via Apache Spark was even more powerful than a comparable multithreaded Java solution.

关键词： Cluster computing Apache Hadoop distributed Systems Apache Spark Cloud computing

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Optimal distributed generation allocation in MV distribution networks

Optimal distributed generation allocation in MV distribution...

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Power Industry Computer Application conference (PICA)

作者： G. Celli F. Pilo Department of Electric and Electronic Engineering University of Cagliari Cagliari Italy

ISBN: (纸本)0780366816

The necessity for flexible electric systems, changing regulatory and economic scenarios, energy savings and environmental impact are providing impetus to the development of distributed generation (DG), which is predicted to play an increasing role in the electric power system of the future. With so much new distributed generation being installed, it is critical that the power system impacts be assessed accurately so that DG can be applied in a manner that avoids causing degradation of power quality, reliability and control of the utility system. For these reasons, the paper proposes a new software procedure, based on a genetic algorithm, capable of establishing the optimal distributed generation allocation on an existing MV distribution network, considering all the technical constraints, like feeder capacity limits, feeder voltage profile and three-phase short circuit current in the network nodes.

关键词： distributed control Power system reliability Power system economics Power generation economics Economic forecasting Environmental economics Power system control Power systems Degradation Power quality

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Secure, Global Quantum Communications Networks

Secure, Global Quantum Communications Networks

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international conference on Transparent Optical Networks

作者： Ivan B. Djordjevic University of Arizona Tucson USA

ISBN: (数字)9781728184234

ISBN: (纸本)9781728184241

The research in quantum communications networks (QCNs), where multiple users desire to generate a common quantum-secured key, is still in its beginning stage. To solve for the problems of both discrete variable (DV)-and continuous variable (CV)-QKD schemes in a simultaneous manner and enable the next generation of quantum communication networking, in this invited paper we describe a scenario where disconnected terrestrial QCNs are coupled through LEO satellite quantum network forming heterogeneous satellite-terrestrial QCN. This concept will provide an important step in enabling ultimate security for future network infrastructure in the world. The proposed QCNs will be robust against channel impairments, over heterogeneous links. Moreover, the proposed QCNs will provide an unprecedented security level for beyond 5G wireless networks, Internet-of-Things (IoT), optical networks, and autonomous vehicles, to mention few.

关键词： Security Quantum computing Quantum entanglement Low earth orbit satellites Optical fiber networks

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The New UPC++ DepSpawn High Performance Library for Data-Flow computing with Hybrid Parallelism 22nd

The New UPC++ DepSpawn High Performance Library for Data-Fl...

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22nd Annual international conference on Computational Science, ICCS 2022

作者： Fraguela, Basilio B. Andrade, Diego Universidade da Coruña CITIC Grupo de Arquitectura de Computadores. Facultade de Informática Campus de Elviña S/N. 15071 A Coruña Spain

ISBN: (纸本)9783031087509

Data-flow computing is a natural and convenient paradigm for expressing parallelism. This is particularly true for tools that automatically extract the data dependencies among the tasks while allowing to exploit both distributed and shared memory parallelism. This is the case of UPC++ DepSpawn, a new task-based library developed on UPC++ (Unified Parallel C++), a library for parallel computing on a Partitioned Global Address Space (PGAS) environment, and the well-known Intel TBB (Threading Building Blocks) library for multithreading. In this paper we present and evaluate the evolution of this library after changing its engine for shared memory parallelism and adapting it to the newest version of UPC++, which differs very strongly from the original version on which UPC++ DepSpawn was developed. As we will see, while keeping the same high level of programmability, the new version is on average 9.3% faster than the old one, the maximum speedup being 66.3%. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Data transfer

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