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Design of a guide vane for improving inside flow uniformity of electrostatic precipitator

Transactions of the Korean Institute of Electrical Engineers 2013年第4期62卷 523-528页

作者： Noh, Wook Bae, Seong-Jun Park, Sookhee Kang, Sunkyun Lee, Jangmyung Dept. of Interdisciplinary Program in Robotics Pusan National University Korea Republic of Dept of Electrical and Electronic Engineering Pusan National University Korea Republic of

In recent years, many efforts are increasingly being made to conserve the natural environment with enhanced emission standards and air quality standards. Also there are various methods necessary to be researched to minimize the emission of air pollutants. In particular, boilers of industrial facilities are major portions of the air pollution. The front duct which needs to be designed to reduce the gases to the electrostatic precipitator requires a bent tube, a reduction/extend tube and an auxiliary equipment, that is, a guide vane. This paper proposes an optimum design of the guide vane by a case study for electrostatic precipitator's flow uniformity. The operating conditions of this study are as follows: BMCR (Boiler Maximum Continuous Rate) and MGR (Maximum Guaranteed Rate) are 75%, 50%, and 30%;turbulent fluid dynamics model is based upon K- Ε formulation. Presentation of the computed motion of particles is found to be quite useful to predict the precipitator performance by use CFD (Computational Fluid Dynamics).

关键词： Electrostatic precipitators

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Screening for pre-diabetes using support vector machine model

Screening for pre-diabetes using support vector machine mode...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Jai Won Chung Won Jae Kim Soo Beom Choi Jee Soo Park Deok Won Kim Graduate Program in Biomedical Engineering Yonsei University Dept. of Medicine Yonsei University College of Medicine Brain Korea 21 PLUS Project for Medical Science Yonsei University Department of Medical Engineering Yonsei University College of Medicine

ISBN: (纸本)9781424479276

The global prevalence of diabetes is rapidly increasing. Studies support screening and interventions for pre-diabetes, which results in serious complications and diabetes. This study aimed at developing an intelligence-based screening model for pre-diabetes that could assist with decreasing the prevalence of diabetes through early identification and subsequent interventions. Data from the Korean National Health and Nutrition Examination Survey (KNHANES) were used, excluding subjects with diabetes. The KNHANES 2010 data (n = 4,685) were used for training and internal validation, while data from KNHANES 2011 (n = 4,566) were used for external validation. We developed a model to screen for pre-diabetes using support vector machine (SVM), and performed a systematic evaluation of the SVM model using internal and external validation. We compared the performance of the SVM model with that of a screening score model based on logistic regression analysis for pre-diabetes that had been developed previously. Backward elimination logistic regression resulted in associations between pre-diabetes and age, sex, waist circumference, body mass index, alcohol intake, family history of diabetes, and hypertension. The areas under the curves (AUCs) for the SVM model in the internal and external datasets were 0.761 and 0.731, respectively, while the AUCs for the screening score model were 0.734 and 0.712, respectively. The SVM model developed in this study performed better than the screening score model that had been developed previously and may be more effective for pre-diabetes screening.

关键词： Delays Stability criteria Numerical stability Time-varying systems Asymptotic stability Discrete-time systems

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Extraction of a reward expectation signal from cortical units following ballistic movements generated by a brain machine interface

Extraction of a reward expectation signal from cortical unit...

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IEEE Signal Processing in Medicine and Biology Symposium (SPMB)

作者： David McNiel Marib Akanda Aditya Tarigoppula Pratik Y. Chhatbar Joseph Francis Dept. of Phys. & Pharm. State University of New York Downstate Med. Center Brooklyn NY Graduate Program in Biomedical Engineering New York University Polytechnic School of Engineering MUSC Stroke Center Dept. of Neurology & Neurosurgery Med. Univ. of SC Charleston SC

Movement decoding algorithms used in today's brain-machine interface (BMI) technologies require movement-related neural activity in large quantities as training data to decode with sufficient accuracy the intended movements of the user. Because of physical disability the end users of BMI systems may be unable to readily provide such training data. Moreover, variability in the neural control of movements across patients with disability may result in individually unique training data. These issues limit the generalizability of movement decoding algorithms across BMI users. One potential method of circumventing this generalizability limitation and individualizing BMI technology is the use of reinforcement learning, a group of techniques that require minimal feedback in order to find solutions to an arbitrary problem. One promising means of providing feedback to a reinforcement learning-based BMI is via a neural reward signal found in multiple cortical and subcortical areas. Particularly attractive is the idea of parallel extraction of both the movement control signal and the reward signal from the same electrode array. We examined the neural signal underlying the expectation of reward depending on the probability of successfully reaching a target given the initial ballistic movement generated by a BMI. The real-time extraction of such signal could be used to determine if the user expects a movement generated by a BMI to succeed or fail. This information could then be used to update the control architecture of the BMI to generate an output more in line with the user's intention.

关键词： Educational institutions Training data Decoding biomedical engineering Nervous system Neurosurgery Accuracy

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Processing of a directionally dependent reward signal in motor and somatosensory units

Processing of a directionally dependent reward signal in mot...

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IEEE Signal Processing in Medicine and Biology Symposium (SPMB)

作者： Marib Akanda David McNiel Aditya Tarigoppula Pratik Y. Chhatbar Joseph Francis Dept. of Phys. & Pharm. State University of New York Downstate Med. Center Brooklyn NY Graduate Program in Biomedical Engineering New York University Polytechnic School of Engineering MUSC Stroke Center Dept. of Neurology & Neurosurgery Med. Univ. of SC Charleston SC

Improving the control of neuroprosthetics to achieve biomimetic movements would significantly increase their utility and greatly improve the quality of life of their users. One potential addition to today's neuroprosthetics control systems would be an inclusion of the reward-based signal from motor or somatosensory cortex. The reward signal present in these cortices could indicate if a movement goal, such as reaching to and grasping a cup of coffee, was successful or not. Such a signal could be used as a component in reinforcement learning algorithms employed in brain-machine interfaces. This study seeks to determine the movement direction dependence of the reward signal. To accomplish this goal, we examined data recorded from the units of one bonnet macaque as it performed a center-out reaching task that has a fixed-probability reward assignment at the completion of a successful trial. By comparing the spiking neural activity with the actual receipt of reward, we examined if the change in firing activity can be attributed to the reward signal, and if this signal is also tied to the directionality of the movement. Including this information for reinforcement learning in brain-machine interfaces would bolster current efforts and lead to more realistic movement of neuroprosthetics.

关键词： Educational institutions Learning (artificial intelligence) biomedical engineering Nervous system Neurosurgery Control systems Grasping

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Reconfigurable Nanostructures-New Designs for Medicine

Reconfigurable Nanostructures-New Designs for Medicine

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中国微米纳米技术学会纳米科学技术分会第三届年会暨2014全国纳米生物与医学学术会议

作者： Haiqing Dong Yongyong Li Dong Qian Donglu Shi Shanghai East Hospital Institute for biomedical engineering & Nano science School of MedicineTongji UniversityShanghai 200092 Dept. of Mechanical Engineering the University of Texas at DallasRichardsonTX 75080 The Materials Science and Engineering Program Department of Mechanical and Materials EngineeringCollege of Engineering and Applied ScienceUniversity of CincinnatiCincinnatiOH 45221USA

A key challenge in nanomaterials development is the control and manipulation of the structure at the *** are able to meet this challenge through reconfigurable arrays configured on graphene nano-sheets(GNS).Our approach is a new paradigm in materials *** synthesis relies on identification of thermodynamically stable phases and synthesis via chemical *** conventional approach targets a specific functionality,which is fixed once synthesis is *** seek to circumvent the restrictions of conventional synthesis through reconfigurable nanostructural assembly.

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NUE: NanoTRA- Texas regional alliance to foster nanotechnology environment, health, and safety awareness in tomorrow's engineering and technology leaders

NUE: NanoTRA- Texas regional alliance to foster nanotechnolo...

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121st ASEE Annual Conference and Exposition: 360 Degrees of engineering Education

作者： Tate, Jitendra S. Fazarro, Dominick Esperanza Hanks, Craig Trybula, Walt Dutta, Satyajit McLean, Robert Allhoff, Fritz Texas State University San Marcos United States Department of Human Resource Development and Technology University of Texas Tyler United States Interdisciplinary Program in Sustainability Studies Texas State University San Marcos United States Texas State University and Trybula Foundation Ingram School of Engineering Texas State University-San Marcos United States Dept. Biology Texas State University San Marcos TX 1993-98 United States Western Michigan University United States

This Nanotechnology Undergraduate Education (NUE) in engineering program entitled, "NUE: NanoTRA-Texas Regional Alliance to foster 'Nanotechnology Environment, Health, and Safety Awareness' in tomorrow's engineering and Technology Leaders", at Texas State University-San Marcos (Texas State) is a collaborative project with the University of Texas (UT) at Tyler to develop introductory and advanced curricula that address the 'nanotechnology safety issues' that include social, ethical, environmental, health, and safety issues of nanotechnology. The curricula will be modular in nature, suitable for use either as two full semester courses that will be taught online at the UT at Tyler or for insertion as separate modules into undergraduate engineering, engineering technology, and industrial technology courses at Texas State. © American Society for engineering Education, 2014.

关键词： Nanotechnology

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Classification of Serous Ovarian Tumors Based on Microarray Data Using Multicategory Support Vector Machines

Classification of Serous Ovarian Tumors Based on Microarray ...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Jee Soo Park Soo Beom Choi Jai Won Chung Sung Woo Kim Deok Won Kim Dept. of Medicine Yonsei University College of Medicine Seoul Korea Brain Korea 21 PLUS Project for Medical Science Yonsei University Seoul Korea Graduate Program in Biomedical Engineering Yonsei University Seoul Korea Future IT R&D Laboratory LG Electronics Advanced Research Institute Seoul Korea Professor at Dept. of Medical Engineering Yonsei University College of Medicine Seoul Korea

Ovarian cancer, the most fatal of reproductive cancers, is the fifth leading cause of death in women in the United States. Serous borderline ovarian tumors (SBOTs) are considered to be earlier or less malignant forms of serous ovarian carcinomas (SOCs). SBOTs are asymptomatic and progression to advanced stages is common. Using DNA microarray technology, we designed multicategory classification models to discriminate ovarian cancer subclasses. To develop multicategory classification models with optimal parameters and features, we systematically evaluated three machine learning algorithms and three feature selection methods using five-fold cross validation and a grid search. The study included 22 subjects with normal ovarian surface epithelial cells, 12 with SBOTs, and 79 with SOCs according to microarray data with 54,675 probe sets obtained from the National Center for Biotechnology Information gene expression omnibus repository. Application of the optimal model of support vector machines one-versus-rest with signal-to-noise as a feature selection method gave an accuracy of 97.3%, relative classifier information of 0.916, and a kappa index of 0.941. In addition, 5 features, including the expression of putative biomarkers SNTN and AOX1, were selected to differentiate between normal, SBOT, and SOC groups. An accurate diagnosis of ovarian tumor subclasses by application of multicategory machine learning would be cost-effective and simple to perform, and would ensure more effective subclass-targeted therapy.

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Effective falls detection method using twotri-axial accelerometers

Effective falls detection method using twotri-axial accelero...

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2012 International Conference on Biomaterial and Bioengineering, ICBB 2012

作者： Jeon, Gye-Rok Kim, Young-Jae Jeon, Ah-Young Lee, Sang-hoon Kim, Jae-hyung Kim, Min-Seok Lee, Seong-Ho Kim, Ji-Hyun Dept. of Biomedical Engineering School of Medicine Pusan National Univ. Korea Republic of Dept. of Anesthesia and Pain Medicine Busan Paik Hospital College of Medicine Inje University Korea Republic of Dept. of Interdisciplinary Program in Biomedical Engineering Graduated School Pusan National University Korea Republic of Dept. of Computer Simulation Inje Univ. Korea Republic of Dept. of Honours Specialization in Medical Science University of Western ON Canada Dept. of Anesthesiology Samsung Changwon Hospital School of Medicine SungkyunKwan Univ Korea Republic of Dept. of Anesthesia and Pain Medicine School of Medicine Pusan Natl. Univ. Korea Republic of

ISBN: (纸本)9783037855973

Falls detection systems have been developed in recent years because falls are detrimental events that can have a devastating effect on health of the elderly population. Current fall detecting methods mainly employ accelerometer to discriminate falls from activities of daily living (ADL). However, this makes it difficult to distinguish real falls from certain fall-like activities such as jogging and jumping. In this paper, an accurate fall detection system was implemented using two tri-axial accelerometers. By attaching the accelerometers on the chest and the abdomen, our system can effectively differentiate between falls and non-fall *** Diff_Z and Sum_diff_Z parameter resulted in falls detection rate of 100%, respectively. © (2013) Trans Tech Publications, Switzerland.

关键词： Fall detection

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SU-E-T-280: Reconstructed Rectal Wall Dose Map-Based Verification of Rectal Dose Sparing Effect According to Rectum Definition Methods and Dose Perturbation by Air Cavity in Endo-Rectal Balloon

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Medical Physics 2014年第6PART15期41卷 288-288页

作者： J Park H Park J Lee S Kang M Lee B Lee T Suh Dept. of Pediatrics Molecular Imaging Program at Stanford Stanford University Stanford CA Research Institute of Biomedical Engineering The Catholic University of Korea Seoul Korea Dept. of Radiation Oncology Ajou University School of Medicine Suwon Korea Konkuk University Medical Center Seoul Korea Dept. of Biomedical Engineering The Catholic University of Korea Seoul Korea Dept. of Bio-Convergence Engineering Korea University Seoul Korea Dept. of Radiation Oncology Sun Medical Center Daejeon Korea

Purpose: Dosimetric effect and discrepancy according to the rectum definition methods and dose perturbation by air cavity in an endo-rectal balloon (ERB) were verified using rectal-wall (Rwall) dose maps considering systematic errors in dose optimization and calculation accuracy in intensity-modulated radiation treatment (IMRT) for prostate cancer patients. Methods: When the inflated ERB having average diameter of 4.5 cm and air volume of 100 cc is used for patient, Rwall doses were predicted by pencil-beam convolution (PBC), anisotropic analytic algorithm (AAA), and AcurosXB (AXB) with material assignment function. The errors of dose optimization and calculation by separating air cavity from the whole rectum (Rwhole) were verified with measured rectal doses. The Rwall doses affected by the dose perturbation of air cavity were evaluated using a featured rectal phantom allowing insert of rolled-up gafchromic films and glass rod detectors placed along the rectum perimeter. Inner and outer Rwall doses were verified with reconstructed predicted rectal wall dose maps. Dose errors and extent at dose levels were evaluated with estimated rectal toxicity. Results: While AXB showed insignificant difference of target dose coverage, Rwall doses underestimated by up to 20% in dose optimization for the Rwhole than Rwall at all dose range except for the maximum dose. As dose optimization for Rwall was applied, the Rwall doses presented dose error less than 3% between dose calculation algorithm except for overestimation of maximum rectal dose up to 5% in PBC. Dose optimization for Rwhole caused dose difference of Rwall especially at intermediate doses. Conclusion: Dose optimization for Rwall could be suggested for more accurate prediction of rectal wall dose prediction and dose perturbation effect by air cavity in IMRT for prostate cancer. This research was supported by the Leading Foreign Research Institute Recruitment program through the National Research Foundation of Korea (NRF

关键词： Dosimetry Perturbation methods Intensity modulated radiation therapy Cavitation Cancer Optimization Anisotropy Radiation treatment Materials analysis

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Application of 3D bioluminescent images to evaluate radiation treatment effect on mammary carcinoma cancer cells

Application of 3D bioluminescent images to evaluate radiatio...

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World Congress on Medical Physics and biomedical engineering

作者： Park, J.Y. Schmidt, T.L. Graves, E.E. Bazalova, M. Kim, M.J. Lee, J.W. Contag, C.H. Suh, T.S. Dept. of Biomedical Engineering Catholic University of Korea 505 Banpo4-dong Seocho-gu Seoul Korea Republic of Advanced Research Center for Medical Physics Catholic University of Korea Seoul Korea Republic of Dept. of Pediatrics Microbiology and Immunology and Radiology Stanford University Palo Alto CA United States Molecular Imaging Program at Stanford Stanford University Palo Alto CA United States Dept. of Radiation Oncology Stanford University Palo Alto CA United States Dept. of Radiation Oncology Konkuk University Medical Center Seoul Korea Republic of

ISBN: (纸本)9783642293047

Introduction: To monitor proliferation of metastatic breast cancer cells and to evaluate radiation treatment effect, metastasis of 4T1 cells and variation of quantitative photon radiance were evaluated using firefly luciferase-based 2D/3D bioluminescent images (BLIs). Detected deformed tumor volumes on 3D BLIs were registered with computed tomography (CT) images to explore the possibilities for adaptive radiotherapy plans. Materials and Methods: Metastatic 4T1 cells were injected into mammary glands of 8 BALB/c mice. The 2D and 3D BLIs were acquired every 2-3 days for a month and radiance (the number of photons/area/time/solid angle) variation of emitted bioluminescent light was analyzed by injecting luciferine. After 1 week, radiation dose of 20 Gy in a single fraction was delivered in an orthovoltage treatment unit. Detected cancer cells were overlaid on morphologic photographs of mice to overall figure out position and growing volumes in 2D BLIs. Specific coordinates of primary and metastasized cancer cells were slice-by-slice verified in 3D BLI. To define molecular cancer cells on CT images, 3D BLI were registered with the anatomical images using a surface matching algorithm. Results and Discussion: The 3D BLI facilitated early detection of cancer cells and evaluation of tumor progression, metastasis, and necrosis. Treated mice with only primary tumor volumes showed 67% reduction of bioluminescent signals, while mice with metastatic tumor volumes 88% reduction as compared to the control group. Registration of 3D BLIs with CT images guided molecular cancer cells on anatomical coordinates. In conclusion, 3D BLIs were useful to detect pathoformic metastasis and to define molecular cancer cells. BLIs contributed to quantify radiation response to differentiate molecular tumor volumes on CT images. Tracking of cancer cells on BLIs would be employed to reflect characteristics of cancer cells for adaptive radiation treatment. © 2013 Springer-Verlag.

关键词： Cancer cells

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