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Estimating the motion of the LAD: A simulation-based study 4th

4th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2001

作者： Kakadiaris, I.A. Pednekar, A. Zouridakis, G. Grigoriadis, K. Dept. of Computer Science Univ of Houston HoustonTX77204-3010 United States Dept. of Neuroscience Univ of Texas-Medical School HoustonTX77030 United States Dept. of Mechanical Engineering Univ of Houston HoustonTX77204-4792 United States

In this paper, we present a simulation-based study of a motion analysis technique designed to intra-operatively estimate the motion parameters of the LAD coronary artery from endoscopic images. © Springer-Verlag ... 详细信息

ISBN: (纸本)3540426973

关键词： Endoscopy

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Using frequent pattern mining to identify behaviors in a naked mole rat colony

Using frequent pattern mining to identify behaviors in a nak...

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25th International Florida Artificial Intelligence Research Society Conference, FLAIRS-25

作者： Imberman, Susan P. Kress, Michael E. McCloskey, Dan P. Dept. Psychology Staten Island NY 10314 United States CSI/IBR Center for Developmental Neuroscience Staten Island NY 10314 United States Technology Systems Staten Island NY 10314 United States Dept. Computer Science College of Staten Island 2800 Victory Blvd Staten Island NY 10314 United States Doctoral Program Computer Science the Graduate Center at CUNY United States

ISBN: (纸本)9781577355588

Animal behavior analysis has, in the past, taken a very low tech approach, with direct observer surveillance and automated video surveillance as the norm. These methods are insufficient when one wants to study interactions between large numbers of animals in their housing environment. In this paper we use a housing environment that has been equipped with a system of RFID sensors. RFID transponders were implanted into the study animal, the naked mole rat. The resulting data was analyzed using principal component analysis and frequent pattern mining. Results showed that these methods can identify time periods of high behavioral activity from that of low aclivity, along with which groups of animals interacted with one another. Copyright © 2012, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Rats

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Molecular Beam Epitaxy Growth and Structural Characterization of Si/GaAs Superlattices

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MRS Online Proceedings Library 1992年第1期263卷 65-70页

作者： R.J. Matyi H.J. Gillespie G.E. Crook J.K. Wade Dept. of Materials Science and Engineering USA Materials Science Program University of Wisconsin Madison Dept. of Electrical and Computer Engineering USA

The growth of high quality Si/GaAs superlattices on GaAs substrates using molecular beam epitaxy is described. A typical superlattice structure consisted of ten periods of thin (<5Å) layers of pseudomorphic silicon alternating with thick GaAs layers; typical GaAs thicknesses range from 100Å to 1850Å. In situ reflection high energy electron diffraction analysis of the structures during growth showed the silicon layers developed a (3 × 1) reconstruction, while the GaAs exhibited a (4×)→(3×)→(3×1)→(2×4) reconstruction sequence. Both observations agree with prior studies of the growth of embedded silicon in GaAs/Si/GaAs heterostructures. X-ray diffraction using the (004) reflection showed sharp and intense satellite peaks (out to 22 orders in one case), indicating a high level of structural quality. Very good agreement has been obtained between observed diffraction patterns and those calculated via dynamical simulation.

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A Neural Network Based Modeling of Closed Room Thermal Comfort Environmental Prediction for Sensor Hub 17

A Neural Network Based Modeling of Closed Room Thermal Comfo...

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17th International Conference on Electrical Engineering/Electronics, computer, Telecommunications and Information Technology, ECTI-CON 2020

作者： Thongkhome, Pornpawee Dejdumrong, Natasha Triamudomsuksa Pattanakarn School Science-Mathematics Program Bangkok Thailand King Mongkut's University of Technology Thonburi Dept. of Computer Engineering Bangkok Thailand

ISBN: (纸本)9781728164861

Currently, environmental protection and intelligence system are topics of interest in smart homes and intelligent buildings. This work represents an environmental prediction study of the closed room which installed a split-type air-conditioning system and a newly designed sensor hub using a feed-forward back-propagation artificial neural network-based prediction for human thermal comfort and indirectly concerned to the growth or existence of diseases, contagious diseases and allergies. The RPROP algorithm was utilized to train the closed room environmental parameters that get from sensor hub especial relative humidity in the ANN model and validate the model by using cohen's kappa and ROC curve to represents the degree of accuracy and reliability. The result obtained from the ANN trained data agreed closely with those obtained from a sensor hub with the high perfect agreement. The benefit of the ANN-based strategy in this study could be utilized for the design of a sensor hub that can realize the adaptive adjustment of environmental parameters through the air conditioning system. © 2020 IEEE.

关键词： Thermal comfort

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A service platform for logging and analyzing mobile user behaviors

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Lecture Notes in computer science

作者： Chen, Po-Ming Chen, Cheng-Ho Liao, Wen-Hung Li, Tsai-Yen Dept. of Computer Science National Chengchi University Taipei Taiwan Master's Program in Digital Contents and Technologies National Chengchi University Taipei Taiwan

ISBN: (纸本)9783642234552

Quantitative analysis of user behavior calls for automated collection of large amount of log data over time. In this paper, we present a service platform for logging and analyzing mobile user behaviors. We have implemented a log collection service which records all user operations on the mobile unit. The collected data are transmitted to a remote server based on an energy-aware schedule. By providing a simple web-based interface, researchers can selectively retrieve the log according to the subject of interest. We illustrate the functionalities of the proposed service platform by several sampled logs. © 2011 Springer-Verlag.

关键词： Behavioral research

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An Approach to Detect Abnormal Submissions for CodeWorkout Dataset 8

An Approach to Detect Abnormal Submissions for CodeWorkout D...

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8th Educational Data Mining in computer science Education Workshop, CSEDM 2024

作者： Hicks, Alex Shi, Yang Lekshmi-Narayanan, Arun-Balajiee Yan, Wei Marwan, Samiha Dept of Computer Science Virginia Tech Blacksburg VA Dept of Computer Science Utah State University Logan UT Intelligent Systems Program University of Pittsburgh Pittsburgh PA School of Informatics Computing and Cyber Systems North Arizona University Flagstaff AZ Dept. of Computer Science University of Virginia wCharlottesville VA

Students’ interactions while solving problems in learning environments (i.e. log data) are often used to support students’ learning. For example, researchers use log data to develop systems that can provide students with personalized problem recommendations based on their knowledge level. However, anomalies in the students’ log data, such as cheating to solve programming problems, could introduce a hidden bias in the log data. As a result, these systems may provide inaccurate problem recommendations, and therefore, defeat their purpose. Classical cheating detection methods, such as MOSS, can be used to detect code plagiarism. However, these methods cannot detect other abnormal events such as a student gaming a system with multiple attempts of similar solutions to a particular programming problem. This paper presents a preliminary study to analyze log data with anomalies. The goal of our work is to overcome the abnormal instances when modeling personalizable recommendations in programming learning environments. © 2024 Copyright for this paper by its authors.

关键词： CS1 Dataset Cleaning Dataset Standards Educational Data Mining Introductory programming

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Merging Plans with Quantitative Temporal Constraints, Temporally Extended Actions, and Conditional Branches 5

Merging Plans with Quantitative Temporal Constraints, Tempor...

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5th International Conference on Artificial Intelligence Planning Systems, AIPS 2000

作者： Tsamardinos, Ioannis Pollack, Martha E. Horty, John F. Intelligent Systems Program University of Pittsburgh United States Dept. of Computer Science and Intelligent Systems Program University of Pittsburgh United States Philosophy Department Inst. for Adv. Computer Studies University of Maryland United States

ISBN: (纸本)1577351118

We develop an algorithm for merging plans that are represented in a richly expressive language. Specifically, we are concerned with plans that have (i) quantitative temporal constraints, (ii) actions that are not instantaneous, but rather have temporal extent, and (iii) conditional branches. Given a set S of such plans, our algorithm finds a set of constraints that jointly ensure that the plans in S are mutually consistent, if such a set of constraints exists. The algorithm has three phases. In the first, it employs a new data structure, a conditional simple temporal network (CSTN), to identify conflicts between the plans. Next, it uses an approach developed by Yang (1997) to suggest a potential resolution of the identified conflicts. Finally, the CSTN is again used to check whether the proposed resolution observes all the temporal constraints. We have implemented our approach, and we present preliminary experimental evidence about domain factors that influence its performance. Copyright © 2000, AAAI (***). All rights reserved.

关键词： Merging

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Efficient Self-Supervision using Patch-based Contrastive Learning for Histopathology Image Segmentation

arXiv

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arXiv 2022年

作者： Boserup, Nicklas Selvan, Raghavendra Dept. of Computer Science University of Copenhagen Denmark Dept. of Neuroscience University of Copenhagen Denmark

Learning discriminative representations of unlabelled data is a challenging task. Contrastive self-supervised learning provides a framework to learn meaningful representations using learned notions of similarity measures from simple pretext tasks. In this work, we propose a simple and efficient framework for self-supervised image segmentation using contrastive learning on image patches, without using explicit pretext tasks or any further labeled fine-tuning. A fully convolutional neural network (FCNN) is trained in a self-supervised manner to discern features in the input images and obtain confidence maps which capture the network’s belief about the objects belonging to the same class. Positive- and negative- patches are sampled based on the average entropy in the confidence maps for contrastive learning. Convergence is assumed when the information separation between the positive patches is small, and the positive-negative pairs is large. The proposed model only consists of a simple FCNN with 10.8k parameters and requires about 5 minutes to converge on the high resolution microscopy datasets, which is orders of magnitude smaller than the relevant self-supervised methods to attain similar performance. We evaluate the proposed method for the task of segmenting nuclei from two histopathology datasets, and show comparable performance with relevant self-supervised and supervised methods. 1 © 2022, CC BY.

关键词： Image segmentation

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Effectiveness of subject specific instruction on mu-based brain-computer interface training

Effectiveness of subject specific instruction on mu-based br...

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Annual Northeast Bioengineering Conference

作者： Alexandria Battison Maura Schlussel Tom Fuller Yih-Choung Yu Lisa Gabel Neuroscience Program Dept. of Electrical and Computer Engineering Dept. of Psychology Lafayette College Easton PA USA

Brain-computer interface (BCI) technology is a growing field, becoming a more viable aid for individuals who have lost voluntary motor control. The mu rhythm, a sensorimotor rhythm that is suppressed when one imagines motor activity (Event Related Desychronization [ERD]), has been particularly utilized in BCIs because of its potential for diverse applications. This study aimed to improve participants' BCI performance by giving them specific instructions for imagine motor behavior to improve their control over sustained mu power. Participants were provided with instructions that were either non-specific (NS), specific (SP), or participant specific (PS) to imagine motor behavior. The ability to control the strength of the mu rhythm was studied by using a simple feedback based paradigm and a novel BCI targeting game. The results showed that utilizing specific instructions for mu-based BCI systems can lead to decreased training time, increased BCI literacy, and enhanced control over mu-based BCI devices. These results suggest that instruction type can make mu-based BCI devices more accessible to individuals with impaired motor behavior.

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GLAC net: Glocal attention cascading networks for multi-image cued story generation

arXiv

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arXiv 2018年

作者： Kim, Taehyeong Heo, Min-Oh Son, Seonil Park, Kyoung-Wha Zhang, Byoung-Tak Program in Cognitive Science Dept. of Computer Sci. and Eng. Program in Neuroscience Seoul National University Seoul08826 Korea Republic of

The task of multi-image cued story generation, such as visual storytelling dataset (VIST) challenge, is to compose multiple coherent sentences from a given sequence of images. The main difficulty is how to generate imagespecific sentences within the context of overall images. Here we propose a deep learning network model, GLAC Net, that generates visual stories by combining global-local (glocal) attention and context cascading mechanisms. The model incorporates two levels of attention, i.e., overall encoding level and image feature level, to construct image-dependent sentences. While standard attention configuration needs a large number of parameters, the GLAC Net implements them in a very simple way via hard connections from the outputs of encoders or image features onto the sentence generators. The coherency of the generated story is further improved by conveying (cascading) the information of the previous sentence to the next sentence *** evaluate the performance of the GLAC Net on the visual storytelling dataset (VIST) and achieve very competitive results compared to the state-of-the-art techniques. Our code and pre-trained models are available here. Copyright © 2018, The Authors. All rights reserved.

关键词： Signal encoding

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