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computing Transition Paths in Multiple-Basin Proteins with a Probabilistic Roadmap Algorithm Guided by Structure data

Computing Transition Paths in Multiple-Basin Proteins with a...

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ieee international conference on Bioinformatics and Biomedicine - Medical Informatics and Decision Making

作者： Maximova, Tatiana Plaku, Erion Shehu, Amarda George Mason Univ Dept Comp Sci Fairfax VA 22030 USA Catholic Univ Amer Dept Comp Sci Washington DC 20064 USA George Mason Univ Dept Bioengn Fairfax VA 22030 USA George Mason Univ Sch Syst Biol Fairfax VA 22030 USA

ISBN: (纸本)9781467367981

Proteins are macromolecules in perpetual motion, switching between structural states to modulate their function. A detailed characterization of the precise yet complex relationship between protein structure, dynamics, and function requires elucidating transitions between functionally-relevant states. Doing so challenges both wet and dry laboratories, as protein dynamics involves disparate temporal scales. In this paper we present a novel, sampling-based algorithm to compute transition paths. The algorithm exploits two main ideas. First, it leverages known structures to initialize its search and define a reduced conformation space for rapid sampling. This is key to address the insufficient sampling issue suffered by sampling-based algorithms. Second, the algorithm embeds samples in a nearest-neighbor graph where transition paths can be efficiently computed via queries. The algorithm adapts the probabilistic road map framework that is popular in robot motion planning. In addition to efficiently computing lowestcost paths between any given structures, the algorithm allows investigating hypotheses regarding the order of experimentally-known structures in a transition event. This novel contribution is likely to open up new venues of research. Detailed analysis is presented on multiple-basin proteins of relevance to human disease. Multiscaling and the AMBER fll2SB force field are used to obtain energetically-credible paths at atomistic detail.

关键词： Switches Yttrium

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Design of Signal acquisition System Based on Earthquake Precursor Electromagnetic Disturbance 4

Design of Signal Acquisition System Based on Earthquake Prec...

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4th international conference on intelligent Control, Measurement and Signal Processing, ICMSP 2022

作者： Zhou, Zhijian Sun, Weijie Wang, Yihang Li, Wenduo College of Instrumentation and Electrical Engineering Jilin University China

ISBN: (数字)9781665486583

ISBN: (纸本)9781665486583

The seismic precursory data collecting system, which includes short-circuit noise, frequency band, and dynamic range, is an important link in the digitalization of seismic monitoring systems. The digital requirements of electromagnetic sensors for seismic precursor detection are met in this study by a high accuracy, low noise, and powerful embedding acquisition method. The low noise signal conditioning circuit is constructed based on the sensor's output voltage and bandwidth, and 1kHz sampling is achieved using a 24-bit high-precision ADS1256 analog-to-digital conversion chip, and the data is then communicated to the PC through the 485 bus. Finally, the acquisition system's noise level in the 0.5Hz60Hz region is around -120dB, with a dynamic range of 133dB. The acquisition system is compared to the NI Company's 4431 acquisition system in order to validate its correctness. The findings reveal that the two systems work similarly, and the self-made acquisition system is significantly less expensive than the 4431 acquisition system. © 2022 ieee.

关键词： Seismology

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A Scalable Reconfigurable computing systems with Distributed Memory for the Analysis of Large Amounts of data 11

A Scalable Reconfigurable Computing Systems with Distributed...

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11th international conference "Management of Large-Scale System Development", MLSD 2018

作者： Alyushin, A.V. Arkhangelsky, V.G. Alyushin, S.A. Dept. Electronic Measuring Systems National Research Nuclear University MEPHi Moscow Russia CITiC Moscow Russia LLC GlowByte Consulting Moscow Russia

ISBN: (纸本)9781538649244

Reconfigurable computing systems with internal distributed memory are a promising element base for the creation of scalable systems of 'intelligent' processing of large amounts of both structured and unstructured data with a short decision-making time and adaptation to new conditions in the process of its development. © 2018 ieee.

关键词： Application specific integrated circuits

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A comparative analysis of data distribution methods in an agent-based neural system for classification tasks

A comparative analysis of data distribution methods in an ag...

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6th international conference on Hybrid intelligent systems and 4th conference on Neuro-computing and Evolving Intelligence, HIS-NCEI 2006

作者： Santana, Laura Emmanuella A. Canuto, Anne M.P. Xavier Jr., João Carlos Campos, André M.C.

ISBN: (纸本)0769526624

The NeurAge (Neural agents) system has been proposed as an alternative to transform the centralized decision making process of a multi-classifier system into a distributed, flexible and incremental one. This system has presented good results in some conventional (centralized) classification tasks. Nevertheless, in some classification tasks, relevant features might be distributed over a set of agent. These applications can be classified as distributed classification tasks. In this paper, a comparative investigation of the NeurAge system using some methods for data distribution will be performed. In addition, the performance of the NeurAge system will be compared with some existing multi-classifier systems. © 2006 ieee.

关键词： intelligent agents

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Short-time Fourier transform covariance and selection, a feature extraction method for binary motor imagery classification

Short-time Fourier transform covariance and selection, a fea...

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2021 ieee international conference on Real-Time computing and Robotics, RCAR 2021

作者： Ma, Yue Zheng, Liangsheng Yi, Zhengkun Xiao, Yang Wang, Can Wu, Xinyu Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong Provincial Key Lab of Robotics and Intelligent System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Chongqing University of Posts and Telecommunications

ISBN: (纸本)9781665436786

The brain-computer interfaces (BCI) technology is able to help dysfunctional people recover their motor functions. Electroencephalography (EEG) is an effective noninvasive method to construct BCI. Motor imagery (MI) paradigm can directly reflect the motor intention of user without additional stimulation equipment in EEG-BCI. The feature extraction methods are the key components to improve the accuracy of MI classification. Traditional feature extraction methods like CSP that only extract features in a single domain or two domains. In this study, we propose two novel feature selection method, short-time Fourier transform covariance and its selection method, which are aiming to extract spatial-time-frequency features simultaneously. In order to evaluate the proposed features, the BCI Competition IV data Set IIb is employed to test the classification accuracy. By comparing the average accuracy of novel TSGSP method, the proposed method is more stable than TSGSP about 6% and the accuracy is just decrease about 0.5% at the same time. The average accuracy of 83.8% over all subjects is obtained. Superior classification performance results show that our proposed method has great potential, which is helpful for the further development and application of BCI technology for motor imaging in the field of neurorehabilitation. © 2021 ieee.

关键词： Electroencephalography

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Lateral Walking Gait Phase Detection with data Optimization for a Hip Exoskeleton in Resistance Exercise 20

Lateral Walking Gait Phase Detection with Data Optimization ...

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international conference on advanced Robotics and Its Social Impacts (ARSO)

作者： Cao, Wujing Zhu, Xinbo Xu, Rui Li, Changyu Yu, Hongliu Zhang, Mingming Yu, Haoyong Kobsiriphat, Worawarit Wu, Xinyu Chinese Acad Sci Shenzhen Inst Adv Technol Guangdong Prov Key Lab Robot & Intelligent Syst Shenzhen 518005 Peoples R China Shenzhen Inst Artificial Intelligence & Robot Soc SIAT Branch Shenzhen Peoples R China SIAT CUHK Joint Lab Robot & Intelligent Syst Shenzhen Peoples R China Nanjing Univ Aeronaut & Astronaut Coll Automat Engn Nanjing Peoples R China Jining Zhongke Intelligent Technol Co Ltd Jining Peoples R China Univ Shanghai Sci & Technol Shanghai Peoples R China Southern Univ Sci & Technol Shenzhen Peoples R China Natl Univ Singapore Dept Biomed Engn Singapore Singapore Natl Met & Mat Technol Ctr Khlong Nueng Thailand

ISBN: (纸本)9798350344646;9798350344639

The accurate detection of lateral walking gait phases is essential for the effective implementation of hip exoskeleton systems in lateral resistance walking exercises. However, limitations in hardware, such as memory and computing power, in the microcontrollers of wearable devices, significantly impact the size and training speed of the lateral walking gait phase detection model, thus affecting the exoskeleton system. This study proposes a data optimization algorithm that utilizes K-means clustering combined with commonly used machine learning algorithms, including Random Forests (RF), Support Vector Machines (SVM), and k-Nearest Neighbors (KNN), to reduce both the training time and size of the model. With the implementation of this algorithm, the training time and model size of RF, SVM, and KNN-based models are reduced by 89.6%, 99.8%, and 97.9%, and 89.6%, 92.7%, and 95.2% respectively. The corresponding gait phase prediction accuracy experiences only a slight decrease of 1.6%, 1.7%, and 2.8% respectively. This method ensures a sufficiently high accuracy in detecting lateral walking gait phases while simultaneously achieving higher efficiency and a smaller model size.

关键词： Support vector machines

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data centric adaptive in-network aggregation for wireless sensor networks

Data centric adaptive in-network aggregation for wireless se...

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2007 ieee/ASME international conference on advanced intelligent Mechatronics, AIM

作者： Weerasinghe, Hesiri Elhajj, Imad H. Krsteva, Aleksandra Najm, Mazen Abou Computer Science and Engineering Department Oakland University Rochester United States Electrical and Computer Engineering Department American University of Beirut Beirut Lebanon

ISBN: (纸本)1424412641

This paper presents and evaluates a data centric adaptive in-network aggregation algorithm for wireless sensor networks. In-Network data aggregation is used in wireless sensor networks to reduce the power consumption of sensor nodes. The accuracy of the aggregated results is highly sensitive to delays in the measurements. All existing methods use fixed time limit to accept delayed information for aggregation. The proposed method dynamically calculates the delay limit by using the historical behavior of each sensor. The presented simulation results illustrate the advantage of the developed algorithm. ©2007 ieee.

关键词： Sensor nodes

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Integrated Control and Monitoring systems in Urban Sewage Treatment Plants Using advanced Process system 2

Integrated Control and Monitoring Systems in Urban Sewage Tr...

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2nd international conference on Next Generation intelligent systems, ICNGIS 2022

作者： Deepa, R. Kumaresan, K. Carolin Monisha, C. Pravinkumar, R. Janani, M. Gopala Krishnan, V. Electronics and Instrumentation Engineering Bannari Amman Institute of Technology Tamilnadu Sathyamangalam India

ISBN: (纸本)9781665467926

The continuous improvement of the manufacturing sector and the quick development of metropolitan areas, a substantial amount of manufacturing and household sewage is discharged untreated into water resources. The increasing shortage of water resources means efficient and reliable sewage treatment has become an important link in realizing sustainable development, and the intelligent upgrading of sewage monitoring systems has become essential in the control of sewage treatment. The standardization of computerization control for urban sewage treatment plants, such as industrial waste and home waste, is a major challenge. Sewage treatment plants that use activated sludge treatment are frequently used to purify sewage water. The Siemens PCS7 control platform is produced by the primary research object and is a fundamental monitoring tool for detecting the PH and COD levels in treated sewage. The S7-400 series controller applies the closed loop PID control system and the model predictive control system. An enhanced sewage monitoring impact has been obtained with the appropriate development of PCS structure and Profinet network level in sewage treatment systems with Supervisory Control and data acquisition as the platform. systems management for process automation pushed techniques that allowed access to field device, controller, and SCADA system operations and data. Optimize the functioning of a sewage treatment facility in terms of process stability, energy consumption, and environmental compliance. © 2022 ieee.

关键词： Controllers

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Skills Development of Professional Ethics in Engineering Degrees in the European Higher Education Area

Skills Development of Professional Ethics in Engineering Deg...

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Int Joint Conf on Int conference on Soft Comp Models in Ind and Environm Applicat / Int Conf on Computat Intelligence in Secur Informat Syst / Int Conf on European Transnat Educ

作者： Sanchez, Lidia Alfonso-Cendon, Javier Perez, Hilde Quintian, Hector Corchado, Emilio Univ Leon Dept Mech Comp & Aerosp Engn Campus Vegazana S-N E-24071 Leon Spain Univ Salamanca Dept Informat & Automat Salamanca Spain

ISBN: (纸本)9783319473642;9783319473635

In this paper, an experience to approach the competence about ethical aspects of the profession is presented. Following an existing methodology, several cases are presented to the students in order to determine if people involved have had a professional or ethical behaviour. Codes of professional ethics or conduct have been also discussed with the students. The experience has been successful since students have actively participated and valued the methodology positively. This solves the lack of prior training in these ethical aspects.

关键词： Skills acquisition Competence development Professional ethics Professional conduct

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A Toolkit for Modeling and Simulation of Dynamic Virtual Machine Consolidation Approach

A Toolkit for Modeling and Simulation of Dynamic Virtual Mac...

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ieee international Workshop on intelligent data acquisition and advanced computing systems: Technology and Applications

作者： Eduard Zharikov Sergii Telenyk Yevhenii Serdiuk National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” Kyiv Ukraine Cracow University of Technology Krakow Poland

ISBN: (纸本)9781665426060

Conducting realistic cloud experiments to evaluate new management strategies is very expensive and risky. In recent years, the research community proposes various simulation software toolkits and frameworks to provide a platform and the necessary building blocks for modeling an optimized virtual machine consolidation in cloud data centers. The models proposed by these frameworks are usually not exhaustive and address a specific management problem or task. The proposed simulation toolkit addresses the dynamic virtual machine consolidation problem, provides various types of simulation, ensures a wide range of logging and debugging information such as performance indicators and charts, and allows to determine optimal model parameters for various modes of operation minimizing the number of active physical machines and decreasing the number of SLA violations.

关键词： Cloud computing data centers Instruments Debugging Predictive models Virtual machining Software

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