the proceedings contain 143 papers. the topics discussed include: parallel processing of frequent itemset based on MapReduce programming model;fire rescue system for high rise building;performance evaluation of differ...
ISBN:
(纸本)9781728140421
the proceedings contain 143 papers. the topics discussed include: parallel processing of frequent itemset based on MapReduce programming model;fire rescue system for high rise building;performance evaluation of different machine learning based algorithms for flood prediction and model for real time flood prediction;language independent multi-class sentiment analysis;face video super resolution using deep convolutional neural network;impact of interference on LoRaWAN link performance;geo-encryption: a location based encryption technique for data security;and design and evaluation of scalable intrusion detection system using machine learning and apache spark.
this paper presents an innovative approach to maximize cell coverage and capacity in a private LTE network by optimizing resource block (RB) and power allocation. the proposed method decomposes the cell into sub-cells...
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the proceedings contains 118 papers from the 1996 IEEE internationalconference on Fuzzy Systems. Topics discussed include fuzzy logic and human reasoning, fuzzy neural network training, fuzzy mobile robot navigation ...
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the proceedings contains 118 papers from the 1996 IEEE internationalconference on Fuzzy Systems. Topics discussed include fuzzy logic and human reasoning, fuzzy neural network training, fuzzy mobile robot navigation and sensor integration, fuzzy controller for manipulators, fuzzy logic controllers, adaptive fuzzy sliding mode controller, learning algorithms, gradient descent method, fuzzy systems for imprecision and uncertainty in databases, fuzziness in pattern recognition, fuzzy modeling, fuzzy operations research, genetic algorithms, autonomous vehicle navigation by fuzzy reasoning, fuzzy decision analysis and support, process control, neurofuzzy approach, defuzzification methods, control system analysis, and computational linguistics.
Nowadays many machines and robots are programmed to perform the same task repeatedly. the Iterative Learning Control (ILC) paradigm is based on the idea that the performance of a system that executes the same trial mu...
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ISBN:
(纸本)9781538650653
Nowadays many machines and robots are programmed to perform the same task repeatedly. the Iterative Learning Control (ILC) paradigm is based on the idea that the performance of a system that executes the same trial multiple times can be improved by learning from the previous iterations. the objective of ILC is to improve the batch process performance by incorporating past trials error information into the control reference signal for the subsequent iteration. the ILC algorithms are categorized with respect to the number of past iterations considered to compute the next control signal and the first order ILC includes those algorithms considering only information about the last trial. In this paper different first order ILC update laws have been considered and compared controlling a Single-Input Single-Output (SISO) micro-positioning piezostage system. the proposed comparison allows to evaluate the performance of different first order ILC algorithms tested on the considered real world case study.
Determination of state of charge (SOC) and state of health (SOH) in today's world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC and SOH is a...
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ISBN:
(纸本)9781538663929
Determination of state of charge (SOC) and state of health (SOH) in today's world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC and SOH is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the estimation algorithms are expected to be precise and easy to implement. this paper presents an online method for the estimation of the SOC and SOH of Valve-Regulated Lead Acid (VRLA) batteries. the proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and for SOH estimation uses Augmented Kalman Filter (AKF). All of the simulations have been done with MATLAB software. the NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. the aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate.
this volume 63 of the conference proceedings contains 19 papers. Topics discussed include computer aided design for steel constructions, topological transformation, structural mechanics, combinatorial and algebraic fo...
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this volume 63 of the conference proceedings contains 19 papers. Topics discussed include computer aided design for steel constructions, topological transformation, structural mechanics, combinatorial and algebraic force methods, nonlinear first yield analysis, Newton algorithms, finite element modeling and load-displacement behavior of anchor walls.
Separating the vocal and background parts of a piece of music is a very difficult task. In the literature, the process of separating vocal and background parts from musical pieces usually utilizes music repetition fea...
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this paper presents a handheld mobile game, Grocery Hunter that encourages children to take on healthy eating habits. Children can use a pocket PC to play the Grocery Hunter game to learn about food nutrition and heal...
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ISBN:
(纸本)9781450306287
this paper presents a handheld mobile game, Grocery Hunter that encourages children to take on healthy eating habits. Children can use a pocket PC to play the Grocery Hunter game to learn about food nutrition and healthy food choices. Childhood obesity in the United States has already reached epidemic proportions. the best way to help children attain and maintain healthy weight is through physical activity and nutritious eating. Our design addresses nutrition directly by teaching children healthy eating habits using an interactive game in the grocery store.
the proceedings contain 93 papers. the topics discussed include: a comprehensive analysis of cloud service models: IaaS, PaaS, and SaaS in the context of emerging technologies and trend;machine learning algorithms for...
ISBN:
(纸本)9798331529437
the proceedings contain 93 papers. the topics discussed include: a comprehensive analysis of cloud service models: IaaS, PaaS, and SaaS in the context of emerging technologies and trend;machine learning algorithms for producing equations in physics;development of a CNN approach classification model for soybean (Glycine max., L.) and its common weeds to support precision agriculture;classifying 5G encrypted packet traces;enhancing short-term load forecasting accuracy in the power systems using a hybrid CNN-GRU model;harnessing the power of quantum feature representation for leveraging fused descriptor definition in breast cancer diagnosis;and development and evaluation of new visible index on remote sensing for estimating house damage.
Use of high-level scripting languages to solve big data problems has become a mainstream approach for sophisticated machine learning data analysis. Often data must be used in several steps of a computation to complete...
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ISBN:
(纸本)9781479970346
Use of high-level scripting languages to solve big data problems has become a mainstream approach for sophisticated machine learning data analysis. Often data must be used in several steps of a computation to complete a full task. Composing default data transformation operators withthe standard Hadoop MapReduce runtime is very convenient. However, the current strategy of using high-level languages to support iterative applications with Hadoop MapReduce relies on an external wrapper script in other languages such as Python and Groovy, which causes significant performance loss when restarting mappers and reducers between jobs. In this paper, we reduce the extra job startup overheads by integrating Apache Pig withthe high-performance Hadoop plug-in Harp developed at Indiana University. this provides fast data caching and customized communication patterns among iterations for data analysis. the results show performance improvements of factors from 2 to 5.
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