Toward Efficient Navigation of Massive-Scale Geo-Textual Streams

With the popularization of portable devices, numerous applications continuously produce huge streams of geo-tagged textual data, thus posing challenges to index geo-textual streaming data efficiently, which is an important task in both data management and AI applications, e.g., real-time data streams mining and targeted advertising. This, however, is not possible with the state-of-the-art indexing methods as they focus on search optimizations of static datasets, and have high index maintenance cost. In this paper, we present NQ-tree, which combines new structure designs and self-tuning methods to navigate between update and search efficiency. Our contributions include: (1) the design of multiple stores each with a different emphasis on write-friendness and read-friendness; (2) utilizing data compression techniques to reduce the I/O cost; (3) exploiting both spatial and keyword information to improve the pruning efficiency; (4) proposing an analytical cost model, and using an online self-tuning method to achieve efficient accesses to different workloads. Experiments on two real-world datasets show that NQ-tree outperforms two well designed baselines by up to 10×.

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Microsense

International Journal of Handheld Computing Research ◽

10.4018/ijhcr.2016070104 ◽

2016 ◽

Vol 7 (3) ◽

pp. 38-55

Author(s):

Srinivasa K.G. ◽

Ganesh Hegde ◽

Kushagra Mishra ◽

Mohammad Nabeel Siddiqui ◽

Abhishek Kumar ◽

...

Keyword(s):

Real Time ◽

Nodal Point ◽

System On Chip ◽

Streaming Data ◽

Portable Devices ◽

Time Data ◽

Unified Framework ◽

Real Time Data ◽

Varied Degree ◽

On Chip

With the advancement of portable devices and sensors, there has been a need to build a universal framework, which can serve as a nodal point to aggregate data from different kinds of devices and sensors. We propose a unified framework that will provide a robust set of guidelines for sensors with varied degree of complexities connected to common set of System-on-Chip (SoC). These will help to monitor, control and visualize real time data coming from different type of sensors connected to these SoCs. We have defined a set of APIs, which will help the sensors to register with the server. These APIs will be the standard to which the sensors will comply while streaming data when connected to the client platforms.

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Microsense

Securing the Internet of Things ◽

10.4018/978-1-5225-9866-4.ch010 ◽

2020 ◽

pp. 170-189

Author(s):

Srinivasa K.G. ◽

Ganesh Hegde ◽

Kushagra Mishra ◽

Mohammad Nabeel Siddiqui ◽

Abhishek Kumar ◽

...

Keyword(s):

Real Time ◽

Nodal Point ◽

Aggregate Data ◽

System On Chip ◽

Streaming Data ◽

Portable Devices ◽

Time Data ◽

Unified Framework ◽

Real Time Data ◽

On Chip

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Research on Typical Methods of S Surface Controller Parameter Self-Tuning for Underwater Vehicles

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.365-366.897 ◽

2013 ◽

Vol 365-366 ◽

pp. 897-904 ◽

Cited By ~ 1

Author(s):

Bin He ◽

Da Peng Jiang ◽

Guo Cheng Zhang ◽

Ying Hao Zhang

Keyword(s):

Moving Average ◽

Response Speed ◽

Underwater Vehicles ◽

Theory Model ◽

Elman Neural Network ◽

Controller Parameter ◽

Tuning Method ◽

Autoregressive Moving Average Model ◽

Self Tuning ◽

Tuning Methods

S surface control is a simple and operative motion control algorithm for underwater vehicles, but it has two parameters requiring to be adjusted manually. In order to enhance the adaptability of S surface controller, the research of S surface controller parameter self-tuning methods based on rules and models is carried out. Firstly, combined with fuzzy control, parameter self-tuning method based on fuzzy rules is presented. Then by means of predictive control theory, model-based parameter self-tuning method is proposed. By introducing the nonlinear autoregressive moving average model, the prediction model of underwater vehicles is established using parallel Elman neural network, and the optimal parameters of S surface controller is obtained by constructing quadratic performance index function. The results of simulation experiments show that the response speed of S surface controller with parameter self-tuning modules is improved, and the parameter self-tuning methods is demonstrated feasible and effective.

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High-Order Filtered PID Controller Tuning Based on Magnitude Optimum

Mathematics ◽

10.3390/math9121340 ◽

2021 ◽

Vol 9 (12) ◽

pp. 1340

Author(s):

Damir Vrančić ◽

Mikuláš Huba

Keyword(s):

A Priori ◽

Higher Order ◽

Process Models ◽

Pid Controllers ◽

Tuning Method ◽

Output Noise ◽

Pid Controller Tuning ◽

Output Time ◽

Tuning Methods ◽

Measured Input

The paper presents a tuning method for PID controllers with higher-order derivatives and higher-order controller filters (HO-PID), where the controller and filter orders can be arbitrarily chosen by the user. The controller and filter parameters are tuned according to the magnitude optimum criteria and the specified noise gain of the controller. The advantages of the proposed approach are twofold. First, all parameters can be obtained from the process transfer function or from the measured input and output time responses of the process as the steady-state changes. Second, the a priori defined controller noise gain limits the amount of HO-PID output noise. Therefore, the method can be successfully applied in practice. The work shows that the HO-PID controllers can significantly improve the control performance of various process models compared to the standard PID controllers. Of course, the increased efficiency is limited by the selected noise gain. The proposed tuning method is illustrated on several process models and compared with two other tuning methods for higher-order controllers.

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Analysis of the Soft-Switching Tuning Effect on the Figures of Merit Involved in the Design of a Class-E Amplifier with Finite DC-Feed Inductance

Electronics ◽

10.3390/electronics10141705 ◽

2021 ◽

Vol 10 (14) ◽

pp. 1705

Author(s):

Ingrid Casallas ◽

Robert Urbina ◽

Carlos-Ivan Paez-Rueda ◽

Gabriel Perilla ◽

Manuel Pérez ◽

...

Keyword(s):

Case Studies ◽

Output Power ◽

Soft Switching ◽

Figures Of Merit ◽

Tuning Method ◽

Tuning Process ◽

Tuning Methods ◽

Zero Voltage ◽

Voltage Switching ◽

Class E

This paper explores the design of a Class-E amplifier with finite DC-feed inductance using three tuning methods. Furthermore, this work quantifies the impacts of the tuning process (referred to in this paper as the tuning effect) on the main figures of merit (FoMs) of this amplifier. The tuning goals were to guarantee two conditions: zero voltage and zero voltage derivative switching (i.e., soft-switching tuning). To the best of the authors’ knowledge, systematic tuning methods have not been analyzed before for this amplifier topology. Two of them are based on the iterative component tuning process, and they have been explored previously in the design of the conventional class-E amplifier with an RF choke inductance. The last tuning method explores the simultaneous adjustment of the control signal period and one amplifier capacitor. The analyzed tuning methods were validated by extensive simulations of case studies, which were designed following the power specifications of the Qi standard. In 100% and 96% of the case studies, zero voltage switching (ZVS) and zero-derivative voltage switching (ZDS) were achieved, respectively. Furthermore, we identified an unexpected behavior in the tuning process (referred to in this paper as the turning point), which consisted of a change of the expected trend of the soft-switching (i.e., ZVS and ZDS) point, and it occurred in 21% of the case studies. When this behavior occurred and converged to at least ZVS, the tuning process required more iterations and a large number of tuning variables. Additionally, after the tuning process, the total harmonic distortion and output power capacity were improved (i.e., in 78% and 61% of the case studies, respectively), whereas the output power, drain and added power efficiencies deteriorated (i.e., in 83%, 61% and 65% of the case studies, respectively) in the overall case studies. However, we could not identify an improvement in the overall FoMs related to the soft-switching tuning. Furthermore, the tuning impact was significant and produced some improvements and some deleterious effects for the FoMs in each case study, without a clear trend by FoMs or by tuning method. Therefore, the amplifier designer may choose the more favorable tuning method and the related FoM trade-offs for the required design specifications.

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A Variable Prediction Horizon Self-tuning Method for Nonlinear Model Predictive Speed Control on PMSM Rotor Position System

IEEE Access ◽

10.1109/access.2021.3084321 ◽

2021 ◽

pp. 1-1

Author(s):

Yao Wei ◽

Yanjun Wei ◽

Yang Gao ◽

Hanhong Qi ◽

Xiaoqiang Guo ◽

...

Keyword(s):

Nonlinear Model ◽

Speed Control ◽

Position System ◽

Rotor Position ◽

Tuning Method ◽

Prediction Horizon ◽

Self Tuning

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Development of a New KPI for the Economic Quantification of Six Big Losses and Its Implementation in a Cyber Physical System

Applied Sciences ◽

10.3390/app10249154 ◽

2020 ◽

Vol 10 (24) ◽

pp. 9154

Author(s):

Paula Morella ◽

María Pilar Lambán ◽

Jesús Royo ◽

Juan Carlos Sánchez ◽

Jaime Latapia

Keyword(s):

Real Time ◽

Physical System ◽

Performance Indicator ◽

Cost Model ◽

Relevant Information ◽

Cyber Physical System ◽

Time Data ◽

Real Time Data ◽

Different Dimensions ◽

The Cost

The purpose of this work is to develop a new Key Performance Indicator (KPI) that can quantify the cost of Six Big Losses developed by Nakajima and implements it in a Cyber Physical System (CPS), achieving a real-time monitorization of the KPI. This paper follows the methodology explained below. A cost model has been used to accurately develop this indicator together with the Six Big Losses description. At the same time, the machine tool has been integrated into a CPS, enhancing the real-time data acquisition, using the Industry 4.0 technologies. Once the KPI has been defined, we have developed the software that can turn these real-time data into relevant information (using Python) through the calculation of our indicator. Finally, we have carried out a case of study showing our new KPI results and comparing them to other indicators related with the Six Big Losses but in different dimensions. As a result, our research quantifies economically the Six Big Losses, enhances the detection of the bigger ones to improve them, and enlightens the importance of paying attention to different dimensions, mainly, the productive, sustainable, and economic at the same time.

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Key Strategies to Overcome Cost Overruns Issues in Building Maintenance Management

International Journal of Engineering & Technology ◽

10.14419/ijet.v7i2.29.13330 ◽

2018 ◽

Vol 7 (2.29) ◽

pp. 269 ◽

Cited By ~ 1

Author(s):

Sylvia Gala Mong ◽

Sarajul Fikri Mohamed ◽

Mohd Saidin Misnan

Keyword(s):

Planning Process ◽

Cost Model ◽

Spare Parts ◽

Maintenance Management ◽

Maintenance Cost ◽

Push Factors ◽

Cost Overruns ◽

Sustainable Building ◽

Maintenance Strategies ◽

Building Maintenance

The building maintenance is a crucial part of the life cycle of the building. The maintenance strategies are planned to maintain the condition of the building for specified functions. The maintenance planning requires a comprehensive assessment in determining the effectiveness of building performance, especially in the maintenance budgets planning process. The effective budget preparation will reduce the risk of cost overruns and help the organization to execute the repair works efficiently with sufficient resources. This study attempts to identify the issues related to maintenance cost and proposed the key strategies for improving the sustainable building maintenance budgeting in dealing with the cost overruns. This paper utilizes a qualitative approach through a literature review of secondary data from previous studies. The proposed cost model of maintenance strategies will be used as a basis for further investigation and validation towards promoting the sustainable building maintenance management. The studies identified the push factors that influence the maintenance cost; human factors, tools and equipment, spare parts and materials, funds allocation and available information. Each of the push factors needs to be well-considered to ensure that the maintenance activities can be done efficiently and to avoid the issues of cost overruns.

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Heterogeneous data-processing optimization with CLARA’s adaptive workflow orchestrator

EPJ Web of Conferences ◽

10.1051/epjconf/202024505020 ◽

2020 ◽

Vol 245 ◽

pp. 05020

Author(s):

Vardan Gyurjyan ◽

Sebastian Mancilla

Keyword(s):

Data Processing ◽

Heterogeneous Systems ◽

Optimal Solution ◽

Heterogeneous Data ◽

Streaming Data ◽

Time Data ◽

Maximum Performance ◽

Adaptive Workflow ◽

Main Challenge ◽

The Right

The hardware landscape used in HEP and NP is changing from homogeneous multi-core systems towards heterogeneous systems with many different computing units, each with their own characteristics. To achieve maximum performance with data processing, the main challenge is to place the right computing on the right hardware. In this paper, we discuss CLAS12 charge particle tracking workflow orchestration that allows us to utilize both CPU and GPU to improve the performance. The tracking application algorithm was decomposed into micro-services that are deployed on CPU and GPU processing units, where the best features of both are intelligently combined to achieve maximum performance. In this heterogeneous environment, CLARA aims to match the requirements of each micro-service to the strength of a CPU or a GPU architecture. A predefined execution of a micro-service on a CPU or a GPU may not be the most optimal solution due to the streaming data-quantum size and the data-quantum transfer latency between CPU and GPU. So, the CLARA workflow orchestrator is designed to dynamically assign micro-service execution to a CPU or a GPU, based on the online benchmark results analyzed for a period of real-time data-processing.

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Tuning of Nacelle Feedback Gains for Floating Wind Turbine Controllers Using a Two-DOF Model

Volume 9: Ocean Renewable Energy ◽

10.1115/omae2020-18770 ◽

2020 ◽

Author(s):

Eben Lenfest ◽

Andrew J. Goupee ◽

Alan Wright ◽

Nikhar Abbas

Keyword(s):

Production Performance ◽

Offshore Wind ◽

Feedback Gain ◽

Tuning Method ◽

Floating Offshore Wind Turbines ◽

Integral Controller ◽

Proportional Integral Controller ◽

Angular Displacements ◽

Tuning Methods ◽

Tuning Strategy

Abstract Designing a collective blade pitch controller for floating offshore wind turbines (FOWTs) poses unique challenges due to the interaction of the controller with the dynamics of the platform. The controller must also handle the competing objectives of power production performance and fatigue load management. Existing solutions either detune the controller with the result of slowed response, make use of complicated tuning methods, or incorporate a nacelle velocity feedback gain. With the goal of developing a simple control tuning method for the general FOWT researcher that is easily extensible to a wide array of turbine and hull configurations, this last idea is built upon by proposing a simple tuning strategy for the feedback gain. This strategy uses a two degree-of-freedom (DoF) turbine model that considers tower-top fore-aft and rotor angular displacements. For evaluation, the nacelle velocity term is added to an existing gain scheduled proportional-integral controller as a proportional gain. The modified controller is then compared to baseline land-based and detuned controllers on an example system for several load cases. First-pass results are favorable, demonstrating how researchers can use the proposed tuning method to efficiently schedule gains for adequate controller performance as they investigate new FOWT configurations.

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