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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Park, Chan-Hoon Kim, Soo-Jin Kim, Sun Cho, Dong-Yeon Zhang, Byoung-Tak School of Computer Science and Engineering Seoul National University Seoul 151-742 Korea Republic of Graduate Program in Bioinformatics Seoul National University Seoul 151-742 Korea Republic of

ISBN: (纸本)1424415098

High-throughput data such as microarrays make it possible to investigate the molecular-level mechanism of cancer more efficiently. Computational methods boost the microarray analysis by managing large and complex data systematically. However, combinatorial interactions among genes have not been considered as a unit of the analysis since previous methods mainly focus on a whole gene or a single isolated gene. Here, we introduce a molecular evolutionary algorithm called probabilistic library model (PLM). In the PLM, library elements are generated from gene combinations. An evolutionary procedure is adopted to learn the probabilistic distribution of training samples. We apply the PLM to prostate cancer microarray data. The experimental results show that the PLM classifiers perform better than conventional methods such as neural networks and decision trees in accuracy. We also examine the evolved library to find cancer-related gene combinations. ©2007 IEEE.

关键词： Microarrays

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Bilevel optimization for machine learning: Algorithm design and convergence analysis

arXiv

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arXiv 2021年

作者： Ji, Kaiyi Graduate Program in Department of Electrical and Computer Engineering Ohio State University

Bilevel optimization has become a powerful framework in a variety of machine learning applications including signal processing, meta-learning, hyperparameter optimization, reinforcement learning and network architecture search. There are generally two classes of bilevel optimization formulations for modern machine learning: 1) problem-based bilevel optimization, whose inner-level problem is formulated as finding a minimizer of a given loss function;and 2) algorithm-based bilevel optimization, whose inner-level solution is an output of a fixed algorithm. For the first problem class, two popular types of gradient-based algorithms have been proposed to estimate the gradient of the outer-level objective (hypergradient) via approximate implicit differentiation (AID) and iterative differentiation (ITD). Algorithms for the second problem class include the popular model-agnostic meta-learning (MAML) and almost no inner loop (ANIL). Although bilevel optimization algorithms have been widely used, their convergence rate and fundamental limitations have not been well explored. Copyright © 2021, The Authors. All rights reserved.

关键词： Network architecture

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Optically-generated focused ultrasound for noninvasive brain stimulation with ultrahigh precision

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Light(Science & Applications) 2022年第11期11卷 2817-2831页

作者： Yueming Li Ying Jiang Lu Lan Xiaowei Ge Ran Cheng Yuewei Zhan Guo Chen Linli Shi Runyu Wang Nan Zheng Chen Yang Ji-Xin Cheng Department of Mechanical Engineering Boston UniversityBostonMA 02215USA Graduate Program for Neuroscience Boston UniversityBostonMA 02215USA Department of Electrical and Computer Engineering Boston UniversityBostonMA 02215USA Department of Chemistry Boston UniversitBostonMA 02215USA Department of Biomedical Engineering Boston UniversityBostonMA 02215USA Division of Materials Science and Engineering Boston UniversityBostonMA 02215USA Department of Biological Engineering Massachusetts Institute of TechnologyCambridgeMA 02142USA

High precision neuromodulation is a powerful tool to decipher neurocircuits and treat neurological *** non-invasive neuromodulation methods offer limited precision at the milimeter ***,we report opticallygenerated focused ultrasound(OFUS)for non-invasive brain stimulation with ultrahigh *** is generated by a soft optoacoustic pad(SOAP)fabricated through embedding candle soot nanoparticles in a curved polydimethylsiloxane *** generates a transcranial ultrasound focus at 15 MHz with an ultrahigh lateral resolution of 83μm,which is two orders of magnitude smaller than that of conventional transcranial-focused ultrasound(tFUS).Here,we show effective OFUS neurostimulation in vitro with a single ultrasound *** demonstrate submillimeter transcranial stimulation of the mouse motor cortex in *** acoustic energy of 0.6 mJ/cm?,four orders of magnitude less than that of tFUS,is suffcient for successful OFUS *** offers new capabilities for neuroscience studies and disease treatments by delivering a focus with ultrahigh precision noninvasively.

关键词： SOAP stimulation precision

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Curriculum-based Reinforcement Learning for an Effective Multi-Agent Path Planning Algorithm in Warehouse Scenarios 15

Curriculum-based Reinforcement Learning for an Effective Mul...

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15th IEEE International Conference on Industry Applications, INDUSCON 2023

作者： de Oliveira, Iure Rosa L. de Carvalho, Kevin B. Brandão, Alexandre S. Graduate Program in Computer Science Universidade Federal de Viçosa Viçosa Brazil Electrical Engineering Department Universidade Federal de Viçosa Viçosa Brazil

ISBN: (纸本)9798350314182

Multi-robot systems can provide substantial increase in efficiency and/or flexibility in different scenarios. Applications in various settings have been studied in the literature, such as disaster management, surveillance, object transportation as well as search-and-rescue. A particular case that can highly benefit from the employment of multiple agents is the logistics in a warehouse scenario. This work proposes an multi-agent Q-learning based algorithm with curriculum learning and transfer learning to perform the path planning process. With progressively more complex stages of training as well as knowledge transfer from one stage to another, the algorithm is capable of achieve high success rates. In order to validate the proposed method, simulations were done to compare it to other combinations of the used techniques, as well as using Q-learning only. Scalability tests were also performed. The proposed method achieved up to 94% success rate after training. © 2023 IEEE.

关键词： Curriculum Learning Mobile Robotics Multi-Agent System Reinforcement Learning Transfer Learning

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A novel approach for ensuring high end-to-end availability: The spine concept

A novel approach for ensuring high end-to-end availability: ...

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10th International Conference on Design of Reliable Communication Networks, DRCN 2014

作者： Gomes, Teresa Tipper, David Alashaikh, Abdulaziz Department of Electrical and Computer Engineering University of Coimbra / INESC Coimbra 3030-290 Coimbra Portugal Graduate Telecommunications and Networking Program University of Pittsburgh Pittsburgh PA 15260 United States

ISBN: (纸本)9781479940097

Telecommunications networks need to guarantee that all node pairs involved in critical service communications are highly available. Typically only a small fraction of traffic and users needs high levels of availability but this traffic often drives the network design to over engineering. In this paper we adopt a novel approach to the problem of how to provide high levels of availability in an efficient manner. The basic idea is to embed a high availability set of links and nodes (termed the spine) in the network topology and leverage protection and routing to provide differentiated classes of resilience with varying levels of availability. In this paper we first explore the spine concept through a simple example illustrating the potential benefits of the approach. Then we study how the structural properties of a network topology can be used to determine heuristics to select a suitable spine and compare this with the case where all network components have the same availability. This is followed by a numerical based study comparing the heuristics with all possible spanning tree based spines for sample topologies. Our results are a step along the path of how to best design a physical network to support protection methods in achieving high levels of availability cost efficiently. © 2014 IEEE.

关键词： Availability

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Domain Adaptation in Color-Shifted Datasets Through Adversarial Learning Balancing 4

Domain Adaptation in Color-Shifted Datasets Through Adversar...

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4th International Conference on Artificial Intelligence and Data Sciences, AiDAS 2023

作者： Hidayaturrahman Trisetyarso, Agung Kartowisastro, Iman Herwidiana Budiharto, Widodo School of Computer Science Bina Nusatara University Mathematics Department Jakarta11480 Indonesia Bina Nusatara University Binus Graduate Program-Doctor of Computer Science Computer Science Department Jakarta11480 Indonesia Bina Nusantara University Faculty of Engineering Computer Engineering Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia

ISBN: (纸本)9798350318432

Due to the disparity in the levels of difficulty presented by the several tasks, doing domain adaptation in an adversarial way may result in an imbalanced learning process. In the MNIST dataset, this phenomenon also manifests itself in the form of domain adaptation for color-shifted distribution. In this particular situation, the domain classifier has a higher tendency to fit more quickly, but the category classifier fits quite poorly in the learning process. In order to address this problem, a new hyper-parameter has been added to the loss function in order to strike a compromise between the learning speed of the domain and the categorical classifier. By using this technique, the categorical classifier may better match the data while still maintaining the same level of performance as the domain classifier. In order to determine whether or not making use of this hyper-parameter is useful, the phenomena in question is examined using three distinct color-shifted settings. Following the evaluations, it was discovered that the newly introduced hyper-parameter is capable of coping with imbalanced learning while simultaneously engaging in domain adaptation. © 2023 IEEE.

关键词： Color

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Capacity Planning of Access Point Deployment for Indoor Positioning System

Capacity Planning of Access Point Deployment for Indoor Posi...

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2021 International Conference on Power, Energy and Innovations, ICPEI 2021

作者： Thitinaruemit, Aphirak Sitjongsatapom, Suchada Prongnuch, Sethakarn Mahanakorn University of Technology The Electrical Engineering Graduate Program Faculty of Engineering and Technology Bangkok Thailand Faculty of Engineering and Technology Dept. of Electronic Engineering Bangkok Thailand Suan Sunandha Rajabhat University Faculty of Industrial Technology Dept. of Computer Engineering Bangkok Thailand

ISBN: (纸本)9781665402163

This paper present the network design and capacity planning of access point (AP) deployment for indoor positioning system. The estimation of WiFi distance is described briefly how to measure the signal strength of AP. Co-channel interference is a key for network design of access point installation for network capacity. The objective function for network capacity planning of AP deployment is to optimize the number of access point and location for indoor positioning system concerning with the minimized co-channel interference. Simulations are tested to install AP for lecture hall in university. Capacity planning design of wireless AP deployment is proposed for indoor position systems in terms of the received signal strength indications (RSSI). We assume the situation is supported for the crowded conference. The requirement of the results of wireless AP positioning in crowded conference rooms are placing the wireless AP in forms of overlap the signal in order to get the strong signal. Experimental results have been tested their received signal of WiFi APs with the 2.4GHz frequency using the receiver installed in laptops to check the signal. The empirical results shown that the strength of RSSI will be received a signal of -44 dBm at a distance of approximately 20 meters. © 2021 IEEE.

关键词： Signal receivers

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The keyword-based and semantic-driven data matching approach for assisting structuralizing the textual clinical documents

The keyword-based and semantic-driven data matching approach...

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International Conference on Biomedical engineering and Informatics

作者： Chen, Chi-Huang Ping, Xiao-Ou Wang, Zi-Jun Hsieh, Sheau-Ling Chen, Li-Chin Tseng, Yi-Ju Hsu, Ching-Wei Lai, Feipei Department of Electrical Engineering National Taiwan University Taipei Taiwan Graduate Institute of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Graduate Institute of Biomedical Electronic and Bioinformatics National Taiwan University Taipei Taiwan EECS International Graduate Program Institute/IT Center National Chiao Tung University Hsinchu Taiwan

ISBN: (纸本)9781424464968

The clinical data stored in the health information system can be categorized as two types including structuralized data and non-structuralized ones. In the paper, a data extraction system is developed to assist data retrieval from the non-structuralized textual clinical documents such as radiology reports, pathology reports, etc. The system provides keyword-based and semantic-driven data matching methodology to extract the specific information from the textual clinical documents. The matching methodology provides the capabilities to recognize the selected keywords and the related semantics in the documents. Through the extraction verification interface, clinicians can extract and verify the matched information semi-automatically. The extracted data can be filled into predefined case-oriented templates. The structuralized data can be stored back into the clinical data warehouse for further analyzing. Moreover, the case-oriented templates can support collecting corresponding extracted data for various researches. ©2010 IEEE.

关键词： Semantics

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Ultrafast photonic PCR

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Light(Science & Applications) 2015年第1期4卷 267-273页

作者： Jun Ho Son Byungrae Cho SoonGweon Hong Sang Hun Lee Ori Hoxha Amanda J Haack Luke P Lee Department of Bioengineering University of CaliforniaBerkeleyCA 94720USA Berkeley Sensor and Actuator Center University of CaliforniaBerkeleyCA 94720USA Department of Electrical Engineering and Computer Sciences University of CaliforniaBerkeleyCA 94720USA Biophysics Graduate Program University of CaliforniaBerkeleyCA 94720USA

Nucleic acid amplification and quantification via polymerase chain reaction(PCR)is one of the most sensitive and powerful tools for clinical laboratories,precision medicine,personalized medicine,agricultural science,forensic science and environmental *** multiplex PCR,characterized by low power consumption,compact size and simple operation,is ideal for timely diagnosis at the point-of-care(POC).Although several fast/ultrafast PCR methods have been proposed,the use of a simple and robust PCR thermal cycler remains challenging for POC ***,we present an ultrafast photonic PCR method using plasmonic photothermal light-to-heat conversion via photon–electron–phonon *** demonstrate an efficient photonic heat converter using a thin gold(Au)film due to its plasmon-assisted high optical absorption(approximately 65%at 450 nm,the peak wavelength of heat source light-emitting diodes(LEDs)).The plasmon-excited Au film is capable of rapidly heating the surrounding solution to over 150℃ within 3 *** this method,ultrafast thermal cycling(30 cycles;heating and cooling rate of 12.7960.93℃ s^(-1) and 6.660.29℃ s^(-1),respectively)from 55℃(temperature of annealing)to 95℃(temperature of denaturation)is accomplished within 5 *** photonic PCR thermal cycles,we demonstrate here successful nucleic acid(λ-DNA)*** simple,robust and low cost approach to ultrafast PCR using an efficient photonic-based heating procedure could be generally integrated into a variety of devices or procedures,including on-chip thermal lysis and heating for isothermal amplifications.

关键词： genomics light-emitting diodes(LEDs) molecular diagnostics personalized medicine plasmonics point-of-care(POC)diagnostics polymerase chain reaction(PCR)

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The effect of visual advanced driver assistance systems on a following human driver in a mixed-Traffic condition 7

The effect of visual advanced driver assistance systems on a...

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7th International Conference on computer Science and Computational Intelligence, CSCI 2022

作者： Ariansyah, Dedy Pardamean, Bens Caruso, Giandomenico Bioinformatics and Data Science Research Centre Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Department of Mechanical Engineering Politecnico di Milano Milan 20156 Italy

Rapid development in vehicular technology has caused more automated vehicle control to increase on the roads. Studies showed that driving in mixed traffic with an autonomous vehicle (AV) had a negative impact on the time headway (THW) of conventional vehicles (CVs) (i.e., driven by humans). To address this issue, there is a need to equip CV with visual advanced driver assistance systems (ADASs) that helps the driver maintain safe headway when driving near AVs. This study examines the perception of drivers using visual ADAS and their associated risk while driving behind the AV at constant and varying speeds. The preliminary results showed that while visual ADAS could help drivers keep the safe THW, it could affect drivers' ability to react to emergencies. This implies that visual modality alone might not be sufficient and therefore requires some other feedback or intelligent transport systems to help drivers maintain safe driving in a mixed-Traffic condition. © 2022 Elsevier B.V.. All rights reserved.

关键词： Advanced driver assistance systems

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