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IEEE international conference on intelligent Data Acquisition and Advanced computing Systems

作者： Vladimir Oleshchuk University of Agder

ISBN: (纸本)9781728140704

Given two strings: pattern p of length m and text t of length n. The string matching problem is to find all (or some) occurrences of the pattern p in the text t. We introduce a new simple data structure, called index arrays, and design fast privacy-preserving matching algorithm for string matching. The motivation behind introducing index arrays is determined by the need for pattern matching on distributed cloud-based datasets with semi-trusted cloud providers. It is intended to use encrypted index arrays both to improve performance and protect confidentiality and privacy of user data.

关键词： Pattern matching Cloud computing Privacy preserving Text searching Pattern matching Cloud computing Data storage Secure Privacy string matching user data

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Design and Vehicle Implementation of Autonomous Lane Change Algorithm based on Probabilistic Prediction 21

Design and Vehicle Implementation of Autonomous Lane Change ...

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21st IEEE international conference on intelligent Transportation Systems (ITSC)

作者： Chae, Heungseok Jeong, Yonghwan Kim, Seonwook Lee, Hojun Park, Jongcherl Yi, Kyongsu Seoul Natl Univ Seoul South Korea

ISBN: (纸本)9781728103235

This paper describes design, vehicle implementation and validation of a motion planning and control algorithm of autonomous driving vehicle for lane change. Autonomous lane change is necessary for high-level autonomous driving. A vehicle equipped with diverse devices like sensors and computer is introduced for implementation and validation of autonomous driving. The autonomous driving system consists of three parts: perception, motion planning and control. In a perception part, surrounding vehicles' states and lane information are estimated. In motion planning part, using these information and chassis information, probabilistic prediction is conducted for ego vehicle and surrounding vehicle separately. And then, driving mode are decided among three modes: lane keeping, lane change and traffic pressure. Driving mode is determined based on a safety distance by predicting states of surrounding vehicles and ego vehicle. If the ego vehicle cannot perform lane change when the lane change is required, the most proper space is selected considering the probabilistic prediction information and the safety distance. Target states are defined based on driving mode and information of surrounding vehicles behaviors. In control part, the distributed control architecture for real time implementation to the vehicle. A linear quadratic regulator (LQR) optimal control and a model predictive control (MPC) are used to obtain the longitudinal acceleration and the desired steering angle. The proposed automated driving algorithm has been evaluated via vehicle test, which has used one autonomous vehicle and two normal vehicles.

关键词： conferences intelligent transportation systems

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Migration of big data analysis from Hadoop’s mapreduce to spark 1st

Migration of big data analysis from Hadoop’s mapreduce to s...

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1st international conference on Artificial Intelligence and Cognitive computing, AICC 2018

作者： Pradeep Kumar, J. Gouse, Sheikh Amarendra Reddy, P. Department of Information Technology MLR Institute of Technology Dundigal HyderabadTelangana India

ISBN: (纸本)9789811315794

Hadoop was the first major platform for big data, later leading to the development of the better known Spark by the Apache Software Foundation. For a long time of use the inquires about experienced which concentrated on Hadoop empower examines to have a decent review of its points of interest, disadvantages and confinements keeping in mind the end goal to enhance the arrangement started presented. Despite the fact that in 2012 Hadoop 2.0 introduced a number of improvements, particularly in regards to accessibility of the Hadoop distributed File System (HDFS) and bunch asset administration amid MapReduce work execution through the YARN design, the impacts of these changes are yet to be investigated. This paper aims to address the disadvantages and limitations of Hadoop and what these residual extents of enhancements. Spark has outperformed Hadoop to become the most powerful open source software for dealing with big data. It handles most of its operations in-memory, copying them from the passed on physical limited into the far speedier and more reliable RAM memory. This decreases the amount of dull composed work and scrutinizing to and from direct, clumsy mechanical hard drives that occurred under Hadoop’s MapReduce structure. Spark provides a number of innovations that increase the estimation of huge information and allows new utilize cases. Spark gives us a complete structure for constructing, overseeing, and actualizing enormous information preparing necessities. © Springer Nature Singapore Pte Ltd. 2019.

关键词： File organization

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Bag-of-words, bag-of-topics and word-to-vec based subject classification of text documents in Polish - A comparative study 13th

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13th international conference on Dependability and Complex Systems, DepCoS-RELCOMEX 2018

作者： Walkowiak, Tomasz Datko, Szymon Maciejewski, Henryk Faculty of Electronics Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (纸本)9783319914459

This paper deals with the problem of classification of Polish language documents in terms of a subject category. We compare four state-of-the-art approaches to this task which differ primarily in the way the documents are represented by feature vectors. Two methods considered in the study use frequency-of-words or frequency-of-topics representation of the documents and rely on the Natural Language Processing (NLP) technology to pre-process the raw text. Two alternative methods do not involve the NLP technology. They construct feature vectors using vector representation of words (Word2Vec method) or using a frequency of topics derived from the raw text. These four approaches are evaluated using 3 corpora with 5, 34 and 25 subject categories respectively and with a different level of class discrimination. Results suggest that no single method outperforms other method in all tests, however tests with large number of training observations seem to favour the NLP-free Word2Vec methods. © Springer international Publishing AG, part of Springer Nature 2019.

关键词： Text processing

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Performance of the Large-Sized Telescope prototype of the Cherenkov Telescope Array 38

Performance of the Large-Sized Telescope prototype of the Ch...

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38th international Cosmic Ray conference, ICRC 2023

作者： Morcuende, D. López-Coto, R. Moralejo, A. Nozaki, S. Vuillaume, T. Abe, K. Abe, S. Aguasca-Cabot, A. Agudo, I. Alvarez Crespo, N. Antonelli, L.A. Aramo, C. Arbet-Engels, A. Arcaro, C. Artero, M. Asano, K. Aubert, P. Baktash, A. Bamba, A. Baquero Larriva, A. Baroncelli, L. Barres de Almeida, U. Barrio, J.A. Batkovic, I. Baxter, J. Becerra González, J. Bernardini, E. Bernardos, M.I. Bernete Medrano, J. Berti, A. Bhattacharjee, P. Biederbeck, N. Bigongiari, C. Bissaldi, E. Blanch, O. Bonnoli, G. Bordas, P. Bulgarelli, A. Burelli, I. Burmistrov, L. Buscemi, M. Cardillo, M. Caroff, S. Carosi, A. Carrasco, M.S. Cassol, F. Cauz, D. Cerasole, D. Ceribella, G. Chai, Y. Cheng, K. Chiavassa, A. Chikawa, M. Chytka, L. Cifuentes, A. Contreras, J.L. Cortina, J. Costantini, H. Dalchenko, M. Dazzi, F. De Angelis, A. de Bony de Lavergne, M. De Lotto, B. De Lucia, M. de Menezes, R. Del Peral, L. Deleglise, G. Delgado, C. Delgado Mengual, J. della Volpe, D. Dellaiera, M. Di Piano, A. Di Pierro, F. Di Pilato, A. Di Tria, R. Di Venere, L. Díaz, C. Dominik, R.M. Dominis Prester, D. Donini, A. Dorner, D. Doro, M. Eisenberger, L. Elsässer, D. Emery, G. Escudero, J. Fallah Ramazani, V. Ferrara, G. Ferrarotto, F. Fiasson, A. Foffano, L. Freixas Coromina, L. Fröse, S. Fukami, S. Fukazawa, Y. Garcia, E. Garcia López, R. Gasbarra, C. Gasparrini, D. Geyer, D. Giesbrecht Paiva, J. Giglietto, N. Giordano, F. Gliwny, P. Godinovic, N. Grau, R. Green, J. Green, D. Gunji, S. Günther, P. Hackfeld, J. Hadasch, D. Hahn, A. Hashiyama, K. Hassan, T. Hayashi, K. Heckmann, L. Heller, M. Herrera Llorente, J. Hirotani, K. Hoffmann, D. Horns, D. Houles, J. Hrabovsky, M. Hrupec, D. Hui, D. Hütten, M. Iarlori, M. Imazawa, R. Inada, T. Inome, Y. Ioka, K. Iori, M. Ishio, K. Jimenez Martinez, I. Jurysek, J. Kagaya, M. Karas, V. Katagiri, H. Kataoka, J. Kerszberg, D. Kobayashi, Y. Kohri, K. Kong, A. Kubo, H. Kushida, J. Lainez, M. Lamanna, G. Lamastra, A. Le Flour, T. Linhoff, M. Longo, F. López-Oramas, A. IPARCOS-UCM Instituto de Física de Partículas y del Cosmos EMFTEL Department Universidad Complutense de Madrid MadridE-28040 Spain Instituto de Astrofísica de Andalucía-CSIC Glorieta de la Astronomía s/n Granada18008 Spain The Barcelona Institute of Science and Technology Campus UAB Bellaterra Barcelona08193 Spain Max-Planck-Institut für Physik Föhringer Ring 6 München80805 Germany Univ. Savoie Mont Blanc CNRS Laboratoire d’Annecy de Physique des Particules IN2P3 Annecy74000 France Department of Physics Tokai University Japan Institute for Cosmic Ray Research University of Tokyo Japan Departament de Física Quàntica i Astrofísica Institut de Ciències del Cosmos Universitat de Barcelona IEEC-UB Spain EMFTEL department IPARCOS Universidad Complutense de Madrid Spain INAF Osservatorio Astronomico di Roma Italy INFN Sezione di Napoli Italy INFN Sezione di Padova Università degli Studi di Padova Italy Universität Hamburg Institut für Experimentalphysik Germany Graduate School of Science University of Tokyo Japan Universidad del Azuay Ecuador INAF Osservatorio di Astrofisica e Scienza dello spazio di Bologna Italy Centro Brasileiro de Pesquisas Físicas Brazil Instituto de Astrofísica de Canarias Departamento de Astrofísica Universidad de La Laguna Spain CIEMAT Spain Department of Physics TU Dortmund University Germany INFN Sezione di Bari Politecnico di Bari Italy INAF Osservatorio Astronomico di Brera Italy INFN Sezione di Trieste Università degli Studi di Udine Italy University of Geneva Département de physique nucléaire et corpusculaire Switzerland INFN Sezione di Catania Italy Italy Aix Marseille Univ CNRS IN2P3 CPPM France INFN Sezione di Bari Università di Bari Italy INFN Sezione di Torino Italy Palacky University Olomouc Faculty of Science Czech Republic University of Alcalá UAH Spain Port d’Informació Científica Spain University of Rijeka Department of Physics Croatia Institute for Theoretical Physics and Astrophysics Universität W

The next-generation ground-based gamma-ray Cherenkov Telescope Array Observatory (CTAO) will consist of imaging atmospheric Cherenkov telescopes (IACTs) of three different sizes distributed in two sites. The Large-Sized Telescopes will cover the low-energy end of the CTA energy range, starting at about 20 GeV. After its first years of operation at the CTA northern site, the Large-Sized Telescope prototype (Lst-1) is in the final stage of its commissioning phase, having collected a significant amount of scientific data to date. In this contribution, we present the physics performance of the telescope using low-zenith Crab Nebula observations and Monte Carlo simulations fine-tuned accordingly. We show performance figures of merit such as the energy threshold, effective area, energy and angular resolution, and sensitivity based on the standard Hillas-parameters approach and following the source-independent and dependent analysis methods. The analysis threshold is estimated at 30 GeV. The energy resolution is around 30%, and the angular resolution is 0.3 degrees at 100 GeV. The best integral sensitivity of Lst-1 is about 1.1% of the Crab Nebula flux above 250 GeV for 50 hours of observations. We also show the spectral energy distribution and light curve from Crab Nebula observations, which agree with results from other IACTs and link smoothly with Fermi-LAT when considering statistical and systematic uncertainties near the energy threshold. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Shellfish

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Smart Garbage Bin: An IoT Platform for Smart Waste Management System in Pakistan

Smart Garbage Bin: An IoT Platform for Smart Waste Managemen...

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international conference on computing, Mathematics and Engineering Technologies (iCoMET)

作者： Saadia Kulsoom Memon Abdul Rauf Memon Abdul Aziz Memon Department of Electronics Engineering Technology Benazir Bhutto Shaheed University of Technology & Skill Development Khairpur Pakistan Department of Electronic Engineering Mehran University of Engineering and Technology Jamshoro Pakistan Department of Electrical Engineering Sukkur IBA University Sukkur Pakistan

ISBN: (数字)9781728149707

ISBN: (纸本)9781728149714

Internet of things (IoT) is an emerging field which is increasingly becoming influential instrument in daily life. It endeavors to provide comfort and easiness in doing day to day activities in life. Moreover, it has increased the effectiveness of tasks by reducing the time span of the activity and augmenting its accuracy. It is being done with the help of internet service. IoT connects the activities with internet where it becomes easier to watch and monitor the process and the progress of the activity. Internet, the most important phenomenon of the 21 st century, has become a common norm in the society. Thus, IoT is making use of this dynamic feature of human innovation to add more innovative techniques to human lives. Besides all these innovation, human race has been subject to daunting and detrimental challenges which are putting its survival at risk. The problem of accumulating garbage is the most important one. The gigantic amount of waste material is also a big threat to climate of the earth. It is sine qua non to have a special mechanism to deal with the hectic task of collecting and transporting garbage in cities, however, recycling is another dimension of this huge problem. The focus of this research is to come up with a remedy for the problem of ever-increasing garbage. Here, an IoT based costeffective system has been developed. It has the capability to monitor the garbage in real time by using smart technology with the help of WeMos and Ultrasonic sensors. This system makes use of electronic devices and ThingSpeak platform to minimize the expenditures and time duration in the collection and transportation of the waste. This concept is unique in itself as it makes garbage bins able to communicate their status, periodically, to the authorities. This data can be seen on internet and it is not bounded by any specific location as internet is a global phenomenon and so do the proposed system.

关键词： Monitoring Waste management Acoustics Real-time systems intelligent sensors Mathematics

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ThingNet: A Micro-Service based IoT Macro-Programming Platform over Edges and Cloud 21

ThingNet: A Micro-Service based IoT Macro-Programming Platfo...

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21st international conference on Innovation in Clouds, Internet and Networks and Workshops (ICIN)

作者： Qiao, Yuansong Nolan, Robert Gill, Saul Fang, Guiming Lee, Brian Athlone Inst Technol Software Res Inst Athlone Ireland Chinese Acad Sci Inst Software Beijing Peoples R China

ISBN: (纸本)9781538634585

The enormous number of things connected to the Internet requires a flexible macro-programming platform to efficiently organize functions and process data. Fog or Edge computing is an emerging architecture to fill the gaps between things and cloud through providing computing, storage and forwarding services close to the end devices. This paper presents ThingNet - a micro-service based macro-programming platform to enable distributed data routing and processing across IoT devices, edges and central cloud. Application providers can deploy, modify, migrate and scale application logic over underlying infrastructures. An application level service function chaining is designed to enable data flow programming. The service functions can be shared by multiple data flows to reduce resource utilisation. The platform is implemented based on open source platforms including Kubernetes and MiNifi. ThingNet has been verified through a proof of concept testbed including Raspberry Pis, Intel NUCs, and Openstack VMs.

关键词： IoT Macro-programming Micro-service Fog computing Edge computing

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Research and development of intelligent cutting database cloud platform system

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international JOURNAL OF ADVANCED MANUFACTURING technology 2018年第9-12期94卷 3131-3143页

作者： Wang, Zhao Jiao, Li Yan, Pei Wang, Xibin Yi, Jie Shi, Xuechun Beijing Inst Technol Dept Sch Mech Engn 5 Zhongguancun South St Beijing 100081 Peoples R China

In order to promote the integrated application of the Internet of Things and cloud platform computing technology in intelligent manufacturing system, a cloud platform of cutting database was established in this paper. With the help of multi-sensor and distributed storage technology, mathematics model and data mining algorithm, functions of fast accessing and storing cutting data, intelligent modeling and analysis, efficient mining and optimizing processing parameters can be realized in the system, solving the key problems of analyzing cutting force and controlling surface quality in turning difficult-to-cut materials. Data equipment and users in the system were connected as a whole through wireless network, which can provide intelligent service of data querying, modeling, and optimizing through the cloud server. The study made up for the drawbacks in current intelligent database system such as oversimplified platform architecture, low level of intelligence, and low utilization of historical data, providing an efficient method of managing and applying big data in cutting process for the production system.

关键词： intelligent manufacturing Cutting database Cloud platform Internet of Things

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Sensor Virtualization for Enabling Novel Services

Sensor Virtualization for Enabling Novel Services

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IEEE international conference on intelligent Data Acquisition and Advanced computing Systems

作者： Oana Chenaru Cristina Elena Hanganu Dan Popescu Loretta Ichim University POLITEHNICA of Bucharest

ISBN: (纸本)9781728140704

The paper presents a model for the virtualization of a wireless sensor network in a smart home application for energy consumption monitoring. By correlating physical sensor data with information on home's design, sunrise and sunset time according to day of year, time of day and weather data, novel services for consumed power statistics and efficiency of use of natural light were developed in the virtualized environment. Based on this model, distributed applications were developed to implement analysis of energy consumption over large scale areas. We detail the solution implementation based on the OpenSHS simulator and NodeRed.

关键词： distributed applications Energy consumption monitoring Smart home application Sensor virtualization energy consumption analysis Virtualization Wireless sensor networks SUNRISE Sunlight Legal Services Homes Power consumption physical sensor smart dust application energy consumption Enabling

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Data mining approach for traffic hotspots management: Case of Madrid metropolitan area 21

Data mining approach for traffic hotspots management: Case o...

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21st IEEE international conference on intelligent Transportation Systems, ITSC 2018

作者： Cuenca, Laura Garcia Aliane, Nourdine Puertas, Enrique Femandez, Javier Department of Science Computing and Technology Universidad Europea de Madrid Villaviciosa de Odon Madrid Spain Department of Industrial and Aeroespace Engineering Universidad Europea de Madrid Villaviciosa de Odon Madrid Spain

ISBN: (纸本)9781728103235

This article presents the development of an application (App) for mobile devices to visualize hotspots in the road network of Madrid metropolitan area, which is also aimed at warning drivers when approaching those hotspots. The paper describes, firstly, the nature of data used and their provenance, and then puts the focus on the Extraction, Transformation and Loading Process (or ETL Process) carried out for the generation of the structured data used by the App. Afterwards, the main features and functionalities of the developed App are also described. © 2018 IEEE.

关键词： Data mining

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