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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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Asynchronous Agent Teams for Collaborative Tasks Based on Bottom-Up Alliance Formation and Adaptive Behavioral Strategies 15

Asynchronous Agent Teams for Collaborative Tasks Based on Bo...

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15th Intl Conf on Dependable, Autonomic and Secure computing, 15th Intl Conf on Pervasive Intelligence and computing, 3rd Intl Conf on Big data Intelligence and computing and Cyber Science and Technology Congress(DASC/PiCom/dataCom/CyberSciTech)

作者： Hayano, Masashi Iijima, Naoki Sugawara, Toshiharu Waseda Univ Dept Comp Sci & Commun Engn Tokyo 1698555 Japan

ISBN: (纸本)9781538619568

This paper proposes a method to efficiently form teams for tasks that can be executed by multiple agents with different capabilities in a distributed network environment. Recent growing information and networking technologies have been realizing new types of computerized services that have been achieved by appropriately combining data from networked sensing devices and actuators controlled by intelligent programs in decentralized environments. Because these types of services can be realized by a team of agents acting using their own capabilities, how such teams can be formed effectively and efficiently in a distributed environment in a bottom-up manner is a key issue for autonomic computing. Our proposed method can autonomously recognize the dependable agents based on past successful cooperative behaviors, and they generate a tight alliance structure to execute the given tasks. Such an alliance structure avoids some conflicts by preventing many tasks being allocated to a few capable agents. We experimentally show that the proposed method can stably exhibit good performance and can adapt to environmental changes where task structure varies.

关键词： Task analysis Collaboration Resource management Performance evaluation Actuators Robot sensing systems Manipulator sensing systems task analysis actuators management of resources Teams Performance Evaluation Religious Missions Agents bottom-up Fault tolerant computing

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Real-Time Incident Clearance Time Prediction Using Traffic data from Internet of Mobility Sensors 15

Real-Time Incident Clearance Time Prediction Using Traffic D...

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作者： Al Najada, Hamzah Mahgoub, Imad Florida Atlantic Univ Comp & Elect Engn & Comp Sci Dept 777 Glades Rd Boca Raton FL 33431 USA

ISBN: (纸本)9781538619568

The time wasted in traffic congestion especially the non-recurring (unexpected) is priceless. intelligent Transportation systems (ITS) technologies aim at improving transportation safety and mobility, reduce environmental impacts, and enhance productivity by utilizing the current available infrastructure. Providing the drivers with an accurate clearance time will help them manage their trips efficiently. Existing studies attempted to predict the clearance time of highway incidents through statistical modeling by fitting the incident features to their models. Unfortunately, the incident features are not available at the beginning of the incident. In this study, we develop efficient prediction models by training millions of real-time traffic and weather data from Florida Department of Transportation District 4 (FDOT-D4), in conjunction with the crash data reported for the same period. Our models can predict the incident clearance time in real-time once the accident happens by using the real-time traffic data. In this paper, we mainly use Deep Leaning (DL) to build the clearance time prediction model. In addition, we build two other models, Distributed Random Forests (DRF)and Generalized Linear Model (GLM) then, we compare the results of all these models. Traffic Management Centers (TMCs) will use the predicted results to display them on Dynamic Message Signs (DMSs) and broadcast them on the Highway Advisory Radio (HAR). The models performances are validated with the actual clearance times provided by the incidents respondents. DL outperforms both DRF and GLM in predicting the clearance time, reflected in the lowest root mean squared error (RMSE) of 0.99 and the lowest mean absolute error (MAE) of 0.6.

关键词： intelligent Transportation System (ITS) Vehicular Ad-hoc Network (VANET) Traffic Engineering Big data Stream Mining Real-Time Smart data Deep Learning

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Visual Servoing and Obstacle Avoidance Method based Control Autonomous Robotic systems Servicing a Mechatronics Manufacturing Line 9

Visual Servoing and Obstacle Avoidance Method based Control ...

引用

9th ieee International Conference on intelligent data acquisition and advanced computing systems - Technology and Applications (IDAACS)

作者： Ciubucciu, George Solea, Razvan Filipescu, Adrian Filipescu, Adriana Dunarea de Jos Univ Galati Fac Automat Control Comp Elect & Elect Engn Galati Romania

ISBN: (纸本)9781538606971

In this paper is intended to control the entire flexible line using two wheeled mobile robot and two robotic manipulators. The mechatronics manufacturing line has no possibility of automatic feed with pieces and no automatic pickup of the scrap pieces from the storage station. The robotic manipulators are used for charging the buffer of the flexible line as well as emptying the storage station. These tasks are achieved through several algorithms proposed in the present paper (accomplished in Matlab) using image processing with the help of two video cameras synchronized with the grippers of the two robotic manipulators. One of the robotic manipulator (Pioneer 5-DOF Arm), takes with the gripper the pieces stored, is mounted on a mobile robot (Pioneer P3-DX two driving wheels). The Pioneer P3-DX wheeled mobile robot transfer the pieces one by one to another wheeled mobile robot -PeopleBot used to transport the processed piece in the storeroom or at the first station of the flexible line. The second robotic manipulator (Cyton 1500 7-DOF Arm) is fixed and it is used to take the pieces from the PeopleBot mobile robot and to transfer them to the handling work station of the flexible line. PeopleBot mobile robot used to transport the pieces is controlled using new control techniques (trajectory tracking control) with the possibility of obstacle avoidance. Sliding-mode control method is used to control nonlinear processes (the mobile robots). The algorithms proposed in this paper were first tested in simulation and after were implemented in real time on existing mechatronic system, making it completely autonomous.

关键词： flexible manufacturing line wheeled mobile robot robotic manipulator sliding-mode controller image processing

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A Framework for Big data analytics in Secure Network of Video surveillance systems Based on Images Indexation 3

A Framework for Big Data analytics in Secure Network of Vide...

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3rd International Conference of Cloud computing Technologies and Applications (CloudTech)

作者： Ez-Zahout, Abderrahmane Oubaha, Jawad Mohammed V Univ Rabat Higher Natl Sch IT ENSIAS Coll Engn Rabat Morocco

ISBN: (纸本)9781538611159

In recent years, the video data has very massive volume. Digitals cameras are capturing innumerable amounts of video data, the majority of which is unused and analyzed. However, image indexation is necessary to retrieve in time the most significant information. Our proposed framework is based on images indexation to advance a big data analysis in very secure video surveillance system. This framework is based on images indexation. In our work, we have studies the most important methods of indexing in the literature and we have classified them in a taxonomical scenario. Then, we have explains the function of each step in the proposed framework. The strength of this work lies in the fact that it gathers between Big data analytics, Network security, intelligent video surveillance protection and image and video indexing. All this constitutes a diversified field of research area.

关键词： Big data Analysis Image indexing Information retrieval Video surveillance System Cloud computing Public Security

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An advanced Inventory data Mining System for Business Intelligence 3

An Advanced Inventory Data Mining System for Business Intell...

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3rd ieee International Conference on Big data computing Service and Applications (BigdataService)

作者： Zhou, Qifeng Xia, Bin Xue, Wei Zeng, Chunqiu Han, Ruyuan Li, Tao Xiamen Univ Automat Dept Xiamen 361005 Fujian Peoples R China Florida Int Univ Sch Comp & Informat Sci Miami FL 33199 USA Nanjing Univ Posts & Telecommun Sch Comp Sci Nanjing 210023 Jiangsu Peoples R China Nanjing Univ Sci & Technol Sch Comp Sci Technol & Engn Nanjing 210094 Jiangsu Peoples R China

ISBN: (纸本)9781509063185

Inventory management plays a critical role to track inventory levels, orders, and sales of the retailing business. Effective inventory management is a capability necessary to lead in the global marketplace. In the current retailing market, a huge amount of data regarding stocked items in inventory is generated and collected every day. Due to the increasing volume of transaction data and their correlated relations, it is often a non-trivial task to efficiently manage stocked goods, yet it is imperative to explore the underlying dependencies of the inventory items and give insights into implementing intelligent management systems. However, existing inventory management systems rely on statistical analysis of the historical inventory data, and have a limited capability of intelligent management. For example, they usually do not have the ability to forecast item demand and detect anomalous patterns of item inventory transactions. There is little work reported in implementing intelligent inventory management solutions to reveal hidden relations with integrated data-driven analysis. In this paper, we present an intelligent system, called iMiner, to facilitate managing enormous inventory data. We utilize distributed computing resources to process the huge volume of inventory data and incorporate the latest advances in data mining technologies. iMiner provides comprehensive support for conducting many inventory management tasks, such as forecasting inventory, detecting anomalous items, and analyzing inventory aging.

关键词： intelligent systems

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Portable Parallel Design of Weighted Multi-Dimensional Scaling for Real-Time data Analysis 19

Portable Parallel Design of Weighted Multi-Dimensional Scali...

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19th ieee International Conference on High Performance computing and Communications (HPCC) / 15th ieee International Conference on Smart City (SmartCity) / 3rd ieee International Conference on data Science and systems (DSS)

作者： Dash, Sajal Verma, Anshuman North, Chris Feng, Wu-chun Virginia Tech Dept Comp Sci Blacksburg VA 24061 USA Virginia Tech Dept Elect & Comp Engn Blacksburg VA USA

ISBN: (纸本)9781538625880

Projecting a high-dimensional dataset onto a lower dimensional space can improve the efficiency of knowledge discovery and facilitate real-time data analysis. One technique for dimension reduction, weighted multi-dimensional scaling (WMDS), approximately preserves pairwise weighted distances during the transformation;but its O(f (n)d) algorithm impedes real-time performance on large datasets. Thus, we present CLARET, our fast and portable parallel WMDS tool that combines algorithmic concepts adapted and extended from the stochastic force-based MDS (SF-MDS) and Glimmer. To further improve CLARET'S performance for real-time data analysis, we propose a preprocessing step that computes approximate weighted Euclidean distances by combining a novel data mapping called stretching and Johnson Lindestrauss' lemma in O(log d) time in place of the original O(d) time. This preprocessing step reduces the complexity of WMDS from O(f (n)d) to O(f (n) log d), which for large d is a significant computational gain. Finally, we present a case study of CLARET by integrating it into an interactive visualization tool called V2PI to facilitate real-time analytics. To ensure the quality of the projections, we propose a geometric shape matching-based alignment process and a quality metric.

关键词： multi-dimensional scaling (MDS) weighted multi-dimensional scaling (WMDS) OpenCL visual analytics

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The Real-time Implementation for the Parking Line Departure Warning System

The Real-time Implementation for the Parking Line Departure ...

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ieee International Conference on intelligent Transportation Engineering (ICITE)

作者： Dongkyu Lee Jae-Seol Lee Sinjae Lee Seok-Cheol Kee Smart Car Research Center Chungbuk National University Cheongju Korea

The PLDWS (Parking Line Departure Warning System) is one of the important ADAS (advanced Driving Assistance System) functions when a driver recognizes the parking situations. We proposed the new real-time PLDWS algorithm and its real-time implementation based on the NVIDIA Jetson TX2, which is an embedded board environment. We showed the processing speed that is applicable to actual production vehicle and the same performance result as PC environment. A wide-angle camera is mounted on the front, rear, left and right sides of the vehicle, AVM (Around View Monitoring) images are obtained by synthesizing one Top-View image using four camera input images that have been calibrated. Considering that the visible range of the AVM system varies depending on the mounting position of the vehicle, the actual distance of the AVM image is measured and designated as ROI (Region of Interest) to the front and rear, right and left 2 meters from the vehicle. The whole ROI was partitioned into 3×3 grid regions, and the algorithm determined whether the parking line is crossed for each partitioned region by trained deep learning classifier, and finally a warning signal generated for the system. We also discussed the issue of porting to NVIDIA Jetson TX2 board to enable implementation of the parking line departure warning system into the vehicle.

关键词： Machine learning Graphics processing units Monitoring Cameras Real-time systems data models Alarm systems

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Electromagnetic Warfare and the Cybersecurity Threat 15

Electromagnetic Warfare and the Cybersecurity Threat

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作者： Pinou, Damianos (Tom) Chy, Rien Hayajneh, Thaier Fordham Univ Fordham Ctr Cybersecur New York NY 10023 USA

ISBN: (纸本)9781538619568

Society's 21st century existence is completely reliant on our modern-day electronics, our networks and the electrical backbone of our power grid. Over a decade ago in 2001, the Hollywood action movie Ocean's eleven introduced and depicted an ultra-modern, high-tech Electro-Magnetic Pulse (EMP) device as an EM weapon. For the purposes of a criminal heist, a mobile van delivered an EMP attack on a massive scale to inject a damaging blackout on the casinos of the Las Vegas strip. In this paper, we attempt to describe and explore the possibilities of designing, fabricating and deploying a portable EMP device for destructive purposes. We were successful in fabricating an EMP prototype weapon while all the needed components for our device were acquired from electrical supply stores, hobby shops or easily over the internet with no restrictions. We effectively demonstrated how our prototype can destroy small scale electronic devices. Understanding the larger threat is a targeted and transportable high capacity EMP weapon, which has the ultimate power to terminate many sectors of our modern-day technology.

关键词： Amplitude Modulated (AM) Electro-Magnetic Pulse (EMP) Gigahertz (GHz) Microfarads (uF) Megahertz (MHz) Supervisory Control and data acquisition (SCADA) systems Volts per meter (V/m)

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From Myths to Norms: Demystifying data Mining Models with Instance-based Transparency 3

From Myths to Norms: Demystifying Data Mining Models with In...

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3rd ieee International Conference on Collaboration and Internet computing (CIC)

作者： Alufaisan, Yasmeen Zhou, Yan Kantarcioglu, Murat Thuraisingham, Bhavani Univ Texas Dallas Richardson TX 75083 USA

ISBN: (纸本)9781538625651

The desire of moving from data to intelligence has become a trend that pushes the world we live in today fast forward. Machine learning and data mining techniques are being used as important tools to unlock the wealth of voluminous amounts of data owned by organizations. Despite the existing effort of explaining their underlying machinery in layman's terms, data mining models and their output remain as esoteric, discipline-based black boxes viable only to experts with years of training and development experiences. As data mining techniques gain growing popularity in the real world, the ability to understand their intelligent decision-making artifacts has become increasingly important and critical, especially in areas such as criminal justice and law enforcement where transparency of decision-making is vital for ensuring fairness, justice, and equality. In this paper, we present a transparency model to help unmask the incomprehensible reasoning many data mining techniques are deservedly taking the blame for. Our transparency model substitutes a comprehensible, rule-based counterpart for the complex, black-box output of any data mining technique using a novel rule selection technique. The rule-based substitute explains the decision made for each instance with a tiny set of rules, resulting in a significant reduction in model complexity. Besides model simplicity and comprehensibility, we also assess the quality of our rule set by measuring its similarity to the output of the original data mining algorithm. Furthermore, we compute its accuracy on unseen test data as a complementary assessment criteria. We empirically demonstrate the effectiveness of our transparency model by experimenting on eight real datasets that deal with predicting important personal attributes ranging from credit worthiness to criminal recidivism. Our transparency model demonstrates a high degree of consistency with the original data mining algorithms in nearly all cases. We also compare our resul

关键词： Conferences Collaboration Internet

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Smart City Service Acceleration on FPGAs 3

Smart City Service Acceleration on FPGAs

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3rd ieee International Conference on Big data computing Service and Applications (BigdataService)

作者： Kim, Youngsoo Garcia, Marcus Chen, Alan Wong, Nathan Jadhav, Shrikant Gloster, Clay S. San Jose State Univ Dept Elect Engn San Jose CA 95192 USA North Carolina A&T State Univ Dept Comp Syst Technol Greensboro NC USA

ISBN: (纸本)9781509063185

Today's cyber-physical systems (CPS) for the emerging Smart cities includes hardware and software with intelligent sensing and controls. In Smart cities, the use of high definition images, videos, and context information has become a requirement for urban street data collection and processing. Field Programmable Gate Array enabled data centers and processing shows the great potential for its high computation needs. In this paper, we developed embedded controls, and FPGA design accelerating many Smart city server side programs. Those CPS futuristic applications includes illegal dumping detection, pedestrian detection and car plate recognition and performed an Urban Information systems project for the Smart City of San Jose.

关键词： Cyber Physical systems FPGA data analytics

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