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Generalized analytic expressions for the b matrix of twice-refocused spin echo pulse sequence

Generalized analytic expressions for the b matrix of twice-r...

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Medical Imaging 2009 - Image Processing

作者： Zhuang, Qi Liang, Xuwei Cao, Ning Zhang, Jun Laboratory for Computational Medical Imaging and Data Analysis Department of Computer Science University of Kentucky Lexington KY 40506-0046 United States

ISBN: (纸本)9780819475107

Diffusion weighted imaging (DWI) technique has been used to help understand the human brain white matter fiber structures in vivo. Currently used standard diffusion tensor magnetic resonance imaging (DTI) tractography based on the second order diffusion tensor model has limitations in its ability to resolve complex fiber tracts. The generalized diffusion tensor (GDT) imaging technique has been proposed to overcome these limitations associated with the standard second order tensor model. Based on the GDT model, a generalized partial differential equation (PDE) governing the anisotropic diffusion process can be derived. For the purpose of solving the PDE and computing the generalized diffusion tensor, we derive a generalized analytic expression for the high order b matrix in the case of twice-refocused spin echo (TRSE) pulse sequence which is used in the DWI data acquisition. The TRSE pulse sequence is considered because of its ability to null the eddy current effect generated during the scanning. The b matrix was computed by integrating the transverse precessing magnetization between the excitation time and the echo time (TE). In our experiments, we show some computational results of the generalized b matrix based on the new analytic expression. In addition, comparisons between the generalized b matrix computed using our formula and the second order b matrix given by the MRI machine are presented. The characteristics of the fomula and the data are discussed at last. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： data acquisition

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Online scheduling of trafic diversion and cloud scrubbing with uncertainty in current inputs 20

Online scheduling of trafic diversion and cloud scrubbing wi...

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20th ACM International Symposium on Mobile Ad Hoc Networking and Computing, MobiHoc 2019

作者： Jiao, Lei Zhou, Ruiting Lin, Xiaojun Chen, Xu Department of Computer and Information Science University of Oregon EugeneOR United States School of Cyber Science and Engineering Wuhan University Wuhan China School of Electrical and Computer Engineering Purdue University West LafayetteIN United States School of Data and Computer Science Sun Yat-sen University Guangzhou China

ISBN: (纸本)9781450367646

Operating distributed Scrubbing Centers (SCs) to mitigate massive Distributed Denial of Service (DDoS) traic in large-scale networks faces critical challenges. The operator needs to determine the diversion rule installation and elimination in the networks, as well as the scrubbing resource activation and revocation in the SCs, while minimizing the long-term cost and the cumulative decision-switching penalty without knowing the exact amount of the malicious trafic. We model and formulate this problem as an online nonlinear integer program. In contrast to many other online problems where future inputs are unknown but at least current inputs are known, a key new challenge here is that even part of the current inputs are unknown when decisions are made. To llearnž the best decisions online, we transform our problem via a gap-preserving approximation into an online optimization problem with only the known inputs, which is further relaxed and decoupled into a series of one-shot convex programs solvable in individual time slots. To overcome the intractability, we design a progressive rounding algorithm to convert fractional decisions into integral ones without violating the constraints. We characterize the competitive ratio of our approach as a function of the key parameters of our problem. We conduct evaluations using real-world data and conirm our algorithms’ superiority over de facto practices and state-of-the-art methods. © 2019 Association for Computing Machinery.

关键词： Uncertainty analysis

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A novel aircraft and missile accurate positioning and tracking system for military and intelligence using global satellite networks

A novel aircraft and missile accurate positioning and tracki...

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AIAA Information Systems-AIAA Infotech at Aerospace, 2018

作者： Chyad, Hayder Jabbar Al-Saedi, Firas Abdullah Thweny Data and Applications Security Branch Ministry of Science and Technology Baghdad Iraq Computer Engineering Department Al-Nahrain University Baghdad Iraq

ISBN: (数字)9781624105272

ISBN: (纸本)9781624105272

Our novel real time system is based on gathering aircrafts and missiles information from various Radar stations all over the world to a single or multi operation centers. Also, the data gathered by each Radar station can be sent to all other Radar stations, and this will result in extending the range from where information of targets can be obtained even that they are not detected by that specific Radar station itself. These data are tracked by the military and intelligence parties to make the analysis and take the proper decisions on this information. Then all/some of these data are retransmitted to a large and far areas all over the world that does not have a nearby Radar systems, so that the special forces troops on these areas, and by using any commercial Direct Broadcast Satellite TV receiver, can have all the important targets information in their areas shown on their anti-aircraft/anti-missile system’s display, so that they can track or even destroy these targets without being vulnerable till they react on that target. These data are transmitted using commercial satellites using their audio channel of the TV broadcasted channel. The transmitted data will contain all the targets information like speed, range, altitude, geolocation and type after being encrypted. The system was tested in reality and its performance was excellent. © 2018 American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Real time systems

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Detecting Faulty Machinery of Waste Water Treatment Plant Using Statistical Analysis & Machine Learning 25

Detecting Faulty Machinery of Waste Water Treatment Plant Us...

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25th International Conference on computer and Information Technology, ICCIT 2022

作者： Ul Islam, Md. Mazed Mondal, Joyanta Jyoti Shihab, Ibne Farabi Brac University School of Data and Sciences Dhaka Bangladesh Iowa State University Department of Computer Science AmesIA United States

ISBN: (纸本)9798350346022

The goal of wastewater treatment is to eliminate contaminants from wastewater and convert them into effluent/discharge that can be reintroduced into the water cycle. In order to monitor, analyze plant performance, and decrease environmental pollution in wastewater treatment facilities, a model for fault detection must be developed. In this study, we examine different time and cost-efficient machine learning approaches to monitor the operation of a Waste Water Treatment Plant (WWTP) and identify plant faults as an alternative to human, laboratory-based time consuming, costly, and challenging techniques. This will allow us to develop a time and cost-efficient approach to detect such problems. To discover plant defects, we collect one year of unsupervised WWTP data and convert the data into supervised data. Using several machine learning algorithms based on water quality standard measurements (pH, BOD, COD, and suspended solid), we establish whether or not the data is valid. © 2022 IEEE.

关键词： Fault detection

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Evolutionary Dynamic Optimization-Based Calibration Framework for Agent-Based Financial Market Simulators 13

Evolutionary Dynamic Optimization-Based Calibration Framewor...

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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Yang, Zhenhua Zhong, Muyao Yang, Peng Southern University of Science and Technology Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation Department of Computer Science and Engineering Shenzhen518055 China Research Institute of Trustworthy Autonomous Systems Southern University of Science and Technology Department of Statistics and Data Science Shenzhen518055 China

ISBN: (纸本)9798350308365

The agent-based financial market simulators serve as an important validation tool for trading strategies. For high-fidelity simulation, it is pivotal to calibrate the parameters of a simulator so that the generated simulation data resembles the observed real market data of interest. In traditional calibration methods, it is typical that the parameters of the simulator are set to be time-invariant. However, the dynamic nature of the real financial market introduces various variability into the behaviors of the market participants over different time intervals, posing in-herent limitations to the traditional methods. A more reasonable approach might involve employing a simulator with time-variant parameters. This suggests that the model parameters can be dynamically adjusted at different stages of the simulation to adapt to the evolving market. Consequently, the calibration problem of the financial market simulators can be treated as a dynamic optimization problem. To dynamically calibrate the simulators, we introduce an Evolutionary Dynamic Optimization (EDO) framework. By monitoring the changes of the best fitness, the whole simulation time interval is adaptively divided into multiple stages. Then the Negatively Correlated Search (NCS) algorithm is employed to effectively adjust the parameters at different simulation stages to better simulate the real financial market. Empirical results on both synthetic and real data verify that our dynamic calibration framework significantly outperforms traditional calibration methods that fixing a parameter for the whole simulation interval. The proposed strategy of detecting dynamic changes is also shown to be more reliable than the naive method of manually segmenting stages. In terms of calibration time, our proposed method significantly improves by nearly 93% compared to the fixed parameter setting, and approximately 61% compared to manual segmentation calibration. © 2024 IEEE.

关键词： Financial markets

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Musical Analysis of a computer Music Project, by computer-Assistance, for computer Music Applications 26

Musical Analysis of a Computer Music Project, by Computer-As...

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26th International computer Music Conference, ICMC 2000

作者： Liu, Jian-Li Hiraga, Rumi Igarashi, Shigeru Doctoral Program in Engineering University of Tsukuba Japan Bunkyo University Japan Department of Computer Science University of Tsukuba Japan

Daphne is a computer-assisted musical analysis system that analyzes musical structure and other information necessary for computer music applications, especially for performance synthesis. The obtained analysis results are stored in a style which extends the information of a note event so that application systems can share analysis information. Providing sheets of real musical scores, Daphne’s design includes a unique function of analysis database which stores analysis result of multiple editions of a piece. Users can make use of the database to consider how performance is generated based on the interpretation of each edition. In this paper, we describe how analysis information is stored and shared among computer music applications — performance synthesis with rules, performance visualization, and automated accompaniment. © 2000 ICMC. All Rights Reserved.

关键词： computer music

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Solving factored MDPs with continuous and discrete variables

Solving factored MDPs with continuous and discrete variables

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19th National Conference on Artificial Intelligence

作者： Guestrin, Carlos Hauskrecht, Milos Kveton, Branislav Berkeley Research Center Intel Corporation Department of Computer Science University of Pittsburgh Intelligent Systems Program University of Pittsburgh

Although many real-world stochastic planning problems are more naturally formulated by hybrid models with both discrete and continuous variables, current state-of-the-art methods cannot adequately address these problems. We present the first framework that can exploit problem structure for modeling and solving hybrid problems efficiently. We formulate these problems as hybrid Markov decision processes (MDPs with continuous and discrete state and action variables), which we assume can be represented in a factored way using a hybrid dynamic Bayesian network (hybrid DBN). We present a new linear program approximation method that exploits the structure of the hybrid MDP and lets us compute approximate value functions more efficiently. In particular, we describe a new factored discretization of continuous variables that avoids the exponential blow-up of traditional approaches. We provide theoretical bounds on the quality of such an approximation and on its scale-up potential. We support our theoretical arguments with experiments on a set of control problems with up to 28-dimensional continuous state space and 22-dimensional action space. Copyright © 2004, American Association for Artificial Intelligence. All rights reserved.

关键词： Markov processes

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Extended Finite State Machine based Fault Tolerance in WSN 7

Extended Finite State Machine based Fault Tolerance in WSN

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7th International Conference on Computing Methodologies and Communication, ICCMC 2023

作者： Lekha, D. Ahsan Shariff, M. Lakshmi, S. Venkata Anwar Basha, H. Department of Computer Science and Engineering RMK College of Engineering and Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Aalim Muhammed Salegh College of Engineering Tamil Nadu Chennai India Artificial Intelligence and Data Science Sri Krishna College of Engineering and Technology Tamil Nadu Coimbatore India School of Computer Science and Engineering REVA University Karnataka Bengaluru India

ISBN: (纸本)9781665464086

Wireless Sensor Network (WSN) suffers from different malware attacks. Several traditional approaches are proposed for detecting fault nodes in WSN. It is necessary to redistribute the nodes and detect the fault nodes while modifying the WSN parameters. Faults can occur in the nodes interrupting the continuous communication process of the nodes in the WSN. The main reason for a fault is also the induction of the energy drain in a node to the maximum possible level, failure of links in communicating nodes due to bandwidth constraints, and attacks induced by the malicious nodes. To solve this problems, Extended Finite State Machine based Fault Tolerance (EFSM_FT) in the WSN is used to detect the fault sensor nodes in the WSN. In this approach, called the finite state machine (FSM), state prompted is modified while a set of situations are true. Every node can be absolutely to be faulty or not establishing on the sensor node states. Using sensor energy, drop rate, forward sensor rate, sensor obtained rate, bandwidth, and transmission delay, this method finds the node with the fault. As a result, this approach accurately detects the faulty nodes in the WSN. The simulation outcomes illustrate the proposed method has a better fault detection ratio and minimizes the false negative ratio in the WSN. © 2023 IEEE.

关键词： Finite automata

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Preliminary Research Design on Sensor data Gathering for Air Quality Text Generation 4

Preliminary Research Design on Sensor Data Gathering for Air...

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4th International Conference on Computing and Applied Informatics 2019, ICCAI 2019

作者： Aulia, Indra Hizriadi, Ainul Seniman Muhibuddin Department of Information Technology Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan20155 Indonesia Data Science and Intelligent System Research Group Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan20155 Indonesia Computer System Research Group Faculty of Computer Science and Information Technology Universitas Sumatera Utara Medan20155 Indonesia

Air pollution is one of the environmental problems faced by many countries (i.n. the developing countries). It often harms the health of people, plants, and animals as well as our environment. To decrease the risks, e ective and e cient technology for air quality monitoring is indispensable. In Indonesia, it is still limited in the case of the number of devices and the dissemination of air quality information. This paper describes the preliminary research design of air quality monitoring technology based on the Internet of Things (IoT) and Natural Language Generation (NLG) for solving these limitations. It de nes air quality knowledge in the form of a set of rules and presents the architecture design for data gathering and text generation. data gathering uses the related sensors which are able to collect the values of parameters as air quality indicators. Then, the collected values are identi ed to be used for generating the textual information in Indonesian language to social media, such as twitter. So, in this research, the proposed solutions are able to solve the problems properly. © Published under licence by IOP Publishing Ltd.

关键词： Air quality

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Utilization of data Warehouse in Business Intelligence with Kimball Method at Company XYZ

Utilization of Data Warehouse in Business Intelligence with ...

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2021 International Conference on Artificial Intelligence and Big data Analytics, ICAIBDA 2021

作者： Himami, Muhammad Abdullah, Atje Setiawan Nurma Yulita, Intan Suryani, Mira Universitas Padjadjaran Department of Computer Science Sumedang Indonesia Research Center for Artificial Intelligence and Big Data Universitas Padjadjaran Bandun Indonesia

ISBN: (纸本)9781665408905

For a large company the speed of processing and distribution of data is very important. However, at Company XYZ, this has not yet been implemented in its entirety. This hinders the progress of the company. To be able to solve these problems, a storage system is needed that can access data more quickly and effectively by using a data warehouse system. This study discusses the design and construction of a data warehouse using the Kimball method. The data warehouse schema is created using SQL Server Management Studio and Microsoft SQL Server Integration Service. The analysis results from the data warehouse are displayed in the form of a dashboard using Microsoft PowerBI and a web-based application. Judging from the dashboard display that has been made, the production environment at PT Bio Farma is stable so it does not interfere with production quality. The data is entered into a web-based application, with the percentage of application feasibility of 84% after testing. © 2021 IEEE.

关键词： data warehouses

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