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Tissue engineering: controlling Spatial Organization of Multiple Cell Types in Defined 3D Geometries (Adv. Mater. 41/2012)

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Advanced Materials 2012年第41期24卷

作者： Halil Tekin Jefferson G. Sanchez Christian Landeros Karen Dubbin Robert Langer Ali Khademhosseini Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA 02139 USA Center for Biomedical Engineering Department of Medicine Brigham and Women's Hospital Harvard Medical School Boston MA 02139 USA David H. Koch Institute for Integrative Cancer Research Massachusetts Institute of Technology Cambridge MA 02139 USA Department of Chemical Engineering Massachusetts Institute of Technology Cambridge MA 02139 USA Department of Biological Engineering Massachusetts Institute of Technology Cambridge MA 02139 USA Department of Materials Science and Engineering Massachusetts Institute of Technology Cambridge MA 02139 USA Wyss Institute for Biologically Inspired Engineering Harvard University Boston MA 02115 USA

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An elevation map based path planning for mobile robots in a complex outdoor terrain

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ICIC Express Letters 2011年第8 B期5卷 2747-2752页

作者： Yax, Fei Zhuang, Van Wang, Wei Hu, Huosheng Research Center of Information and Control Dalian University of Technology No. 2 Linggong Road Ganjingzi District Dalian 116023 China School of Computer Science and Electronic Engineering University of Essex Wivenhoe Park Colchester CO4 3SQ United Kingdom

This paper presents a novel outdoor path planning algorithm that gives consideration to both environment constraint and nonholonomic constraint. In order to generate accurate environment constraint, an elevation map is utilized to represent outdoor terrain. The Probabilistic Roadmap Method (PRM) is improved by choosing the special units in big-sized grids to ensure a uniform distribution of nodes. In the PRM, an evaluation strategy for calculating safe ranges of units in an elevation map is applied to generate environment constraint, and the path composed of units is smoothed to satisfy the nonholonomic constraint of a mobile robot. Experiment results show the validity and practicability of the proposed approach. © 2011 ISSN 1881-803X.

关键词： Motion planning

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Multi-granularity dynamic analysis of complex software networks

Multi-granularity dynamic analysis of complex software netwo...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Bing Li Weifeng Pan Jinhu Lü State Key Laboratory Software Engineering and School Computer and Complex Network Research Center Wuhan University of China Wuhan China State Key Laboratory Software Engineering Wuhan University of China Wuhan China School Electrical Computer Engineering RMIT University Melbourne Australia Acad. Mathematics System Science Chinese Academy and Sciences Beijing China

Software systems represent one of the most complex man-made systems. In this paper, we analyze the evolution of Object-Oriented (OO) software using complex network theory from a multi-granularity perspective. First, the software net works are constructed for a multi-version software system at different levels of granularity. Then, some parameters used in complex network theory are introduced to study the topological characteristics of these software networks. By investigating the parameters' values in consecutive software networks, we have a better understanding about software evolution. A case study on an open source OO project, Azureus, is conducted as an example to illustrate our approach. It uncovers some underlying dynamic characteristics of OO systems. These results provide a different dimension to our understanding of software system dynamics and also are very useful for the design and development of OO software systems.

关键词： Logic gates Communities US Department of Defense

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Modulation of transfer characteristics of Si nanowire tunnel FET on ultra-thin-body and BOX (UTBB) SOI substrate using back-gate bias

Modulation of transfer characteristics of Si nanowire tunnel...

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International Symposium Semiconductor Device research (ISDRS)

作者： M.-C. Sun S. W. Kim G. Kim H. W. Kim H. Kim J.-H. Lee H. Shin B.-G. Park TD Team (S. LSI) Semiconductor Business Group Samsung Electronics Company Limited South Korea Inter-University Semiconductor Research Center and School of Electrical Engineering and Computer Science Seoul National University South Korea

A major shift in logic CMOS technology from planar device to multi-channel device is underway in order to continue the device scaling without degrading short-channel effect beyond 30-nm node [1]. A distinct feature of the multi-channel device is that higher channel dimensionality increases the surface-to-body-volume ratio and improves the control of channel potential by the gate. However, the limited depletion charge in the small volume of the body makes it difficult to control threshold voltage (V T ) of the device, which also challenges the implementation of the conventional multi-V T library scheme for low power circuit design [2]. A similar problem in FDSOI MOSFET can be handled by the Ground-Plane technique or back-gate scheme proposed by Wong et al. [3]. In this work, we investigate the extension of the scheme to nanowire devices using TCAD simulation. Specially, we focus on the case of Tunnel FET devices which are expected to be promising for sub 20-nm ultra-low power CMOS technology.

关键词： Logic gates Silicon Doping Substrates FETs Educational institutions Nanoscale devices

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Clustering DNA methylation expressions using nonparametric beta mixture model

Clustering DNA methylation expressions using nonparametric b...

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IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS)

作者： Lin Zhang Jia Meng Hui Liu Yufei Huang School of Information and Electrical Engineering China University of Mining and Technology Xuzhou Jiangsu China Department of Electrical and Computer Engineering University of Texas-San Antonio San Antonio TX USA Greehey Childrens Cancer Research Institute UT Health Science Center San Antonio San Antonio TX USA

The problem of defining the clustering structure in DNA methylation expressions is considered. A Dirichlet process beta mixture model (DPBMM) is proposed that models the DNA methylation data array. The model allows automatic learning of the cluster structure parameters such as the cluster mixing proportion, the models of each cluster, and especially the number of clusters. To enable the learning, we proposed a Gibbs sampling algorithm for computing the posterior distributions, hence the estimates of the parameters. We investigate the performance of the proposed clustering algorithm via simulation.

关键词： DNA Measurement Clustering algorithms Data models Computational modeling Arrays Bayesian methods

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Hydrogen gas sensors based on thermally evaporated nanostructured MoO3 Schottky diode: A comparative study

Hydrogen gas sensors based on thermally evaporated nanostruc...

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IEEE SENSORS

作者： M. Shafiei J. Yu M. Breedon N. Motta Q. Wu Z. Hu L. Qian K. Kalantar-zadeh W. Wlodarski School of Engineering Systems Queensland University of Technology Brisbane QLD Australia School of Electrical and Computer Engineering RMIT University Melbourne VIC Australia Art Science and Technology Center Cooperative Research Kyushu University Kasuya Fukuoka Japan Key Laboratory of Mesoscopic Chemistry of MOE School of Chemistry and Chemical Engineering Nanjing University Nanjing China

ISBN: (纸本)9781424492909

In this paper, a comparative study of Pt/nanostructured MoO 3 /SiC Schottky diode based hydrogen gas sensors is presented. MoO 3 nanostructured films with three different morphologies (nanoplatelets, nanoplatelets-nanowires and nano-flowers) were deposited on SiC by thermal evaporation. We compare the current-voltage characteristics and the dynamic response of these sensors as they are exposed to hydrogen gas at temperatures up to 250°C. Results indicate that the sensor based on MoO 3 nano-flowers exhibited the highest sensitivity (in terms of a 5.79V voltage shift) towards 1% hydrogen; while the sensor based on MoO 3 nanoplatelets showed the quickest response (t 90% -40s).

关键词： Schottky diodes Sensor phenomena and characterization Gas detectors Nanostructures Temperature sensors Morphology

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Spectral analysis of sEMG signals to investigate skeletal muscle fatigue

Spectral analysis of sEMG signals to investigate skeletal mu...

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IEEE Conference on Decision and control

作者： Parmod Kumar Anish Sebastian Chandrasekhar Potluri Yimesker Yihun Madhavi Anugolu Jim Creelman Alex Urfer D. Subbaram Naidu Marco P. Schoen Measurement and Control Engineering Research Center (MCERC) School of Engineering Idaho State University Pocatello ID USA MCERC School of Engineering Idaho State University Pocatello ID USA Department of Physical and Occupational Therapy Idaho State University Pocatello ID USA Department of Electrical Engineering and Computer Science MCERC Idaho State University Pocatello ID USA Department of Mechanical Engineering MCERC Idaho State University Pocatello ID USA

ISBN: (纸本)9781612848006;9781612848013

Our recent investigations are focused to develop dynamic models for skeletal muscle force and finger angles for prosthetic hand control using surface electromyographic sEMG as input. Since sEMG is temporal and spatially distributed and is influenced by various factors, muscle fatigue and its related sEMG becomes of importance. This study is an effort to spectrally analyze the sEMG signal during progression of muscle fatigue. The sEMG is captured from the arms of healthy subjects during muscle fatiguing experiments for dynamic and static force levels. Filtered sEMG signal is segmented in five parts with 75% overlap between adjacent segments. The analysis is done using different classical (fast Fourier transform, Welch's averaged modified periodogram), model-based (Yule-Walker, Burg, Covariance and Modified Covariance autoregressive (AR) method), and eigenvector methods (Multiple Signal Classification (MUSIC) and eigenvector spectral estimation method) in frequency domain. Results show that the classical and eigenvector based methods are more sensitive than the model-based methods to fatigue related changes in sEMG signals.

关键词： Muscles Fatigue Force Multiple signal classification Dynamics Estimation Electromyography

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PARTICLE SWARM OPTIMIZATION（PSO）OF POWER ALLOCATION IN COGNITIVE RADIO SYSTEMS WITH INTERFERENCE CONSTRAINTS

PARTICLE SWARM OPTIMIZATION（PSO）OF POWER ALLOCATION IN COG...

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2011 4th IEEE International Conference on Broadband Network and Multimedia Technology

作者： Saeed Motiian Mohammad Aghababaie Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Colleague of EngineeringUniversity of TehranTehran 14399-57131Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences(IPM)Tehran 19548-56316 Iran Image Analysis Laboratory Radiology DepartmentHenry Ford HospitalDetroitMichigan 48202USA

Cognitive radio is used for enhancement of spectrum *** many works have been accomplished on the power allocation of cognitive radio,limited efforts have considered evolutionary *** this paper,we study this problem in the cognitive radio networks where interference constraints are defined for protection of quality of service（QoS）for both primary and secondary *** defined as functions of the signal-to-interference-plus-noise ratio（SINR） are matched for each secondary user which meets Nash’s *** general,the region of utilities that meets the constraints is *** is possible to make simplifications,generate a convex region,and then use common convex optimization approaches to obtain a ***,Particle Swarm Optimization（PSO）does not need such simplifications and thus its results are superior to those of the convex optimization *** is an evolutionary algorithm based on social intelligence,utilized in many optimization *** is a global optimizations algorithm that does not require the objective function be differentiable as required in classic optimization methods.

关键词： Cognitive radio Power allocation Particle Swarm Optimization（PSO）.

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Novel MOSFET structure using p-n junction gate for ultra-low subthreshold-swing

Novel MOSFET structure using p-n junction gate for ultra-low...

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International Symposium Semiconductor Device research (ISDRS)

作者： Garam Kim Min-Chul Sun Sang Wan Kim Hyun Woo Kim Jang Hyun Kim Euy Hwan Park Hyungjin Kim Byung-Gook Park School of Electrical Engineering Computer Science Inter-University Semiconductor Research Center (ISRC) Seoul National University Seoul South Korea TD Team S. LSI Semiconductor Business Group Samsung Electronics Company Limited South Korea

As complementary metal oxide semiconductor (CMOS) has been scaled down and supply voltage has been reduced, it becomes important to reduce subthreshold swing (SS) in order to obtain high on/off current ratio. To decrease SS below 60 mV/dec, tunneling field effect transistor (TFET) has been reported and studied recently[1-3]. However, as TFET uses band-to-band tunneling as its current source, it is difficult to obtain high on-current. In order to solve this problem of the conventional TFET and maintain high on-current while lowering SS, novel device using p-n junction gate is proposed in this paper.

关键词： Logic gates Tunneling MOSFET circuits P-n junctions Doping Shape Educational institutions

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Voxel based treatment prediction using diffusion anisotropy indices and spatial information in Glioblastoma Multiform tumor

Voxel based treatment prediction using diffusion anisotropy ...

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Iranian Conference of Biomedical engineering (ICBME)

作者： Hadi Sabahi Hamid Soltanian-Zadeh Lisa Scarpace Tom Mikkelsen Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI USA Hermelin Brain Tumor Research Center Neurosurgery Department Henry Ford Health System Detroit MI USA

In this paper, we propose a method to predict the outcome of Bevacizumab therapy on Glioblastoma Multiform (GBM) tumors. The method uses diffusion anisotropy indices (DAI) and spatial information to predict the treatment response of each tumor voxel. These DAIs are Fractional Anisotropy, Mean Diffusivity, Relative Anisotropy, and Volume Ratio, extracted from Diffusion Tensor Imaging (DTI) data before treatment. The spatial information is considered as the distance of each tumor voxel from the tumor center, extracted from pre-treatment post-contrast T1-weighted Magnetic Resonance Images (pc-T1-MRI). DAIs and spatial information of each tumor voxel are considered as feature vector. DTI and pc-T1-MRI are gathered before and after the treatment of seven GBM patients. First, DAIs of all brain voxels and the distance of each tumor voxel from the tumor center are calculated. Second, the method registers pre-treatment DAI maps and post-treatment pc-T1-MRI to pre-treatment pc-T1-MRI. Next, the tumor is segmented using thresholding technique from pc-T1-MRI. Then, Gd-enhanced voxels of the pre- and post-treatment pc-T1-MRI are compared to label the feature vectors. Three classifiers were evaluated, including Support Vector Machine, K-Nearest Neighbor, and Artificial Neural Network. Classification results show a preference for K-Nearest Neighbor based on well-established performance measures.

关键词： Tumors Anisotropic magnetoresistance Diffusion tensor imaging Support vector machines Feature extraction Artificial neural networks

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