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Träfflista för sökning "WFRF:(Li Haibo) "

Sökning: WFRF:(Li Haibo)

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1.
  • Li, Fei, et al. (författare)
  • A quantum search based signal detection for MIMO-OFDM systems
  • 2011
  • Ingår i: 18th International Conference on Telecommunications, ICT 2011. - : IEEE. - 9781457700248 - 9781457700255 ; , s. 276-281
  • Konferensbidrag (refereegranskat)abstract
    • Multiple input multiple output-orthogonal frequency division multiplexing (MIMO-OFDM) is considered as candidates for future broadband wireless services. In this paper a novel signal detection scheme based on Grover's quantum search algorithm is proposed for MIMO-OFDM systems. Grover's quantum search algorithm is based on the concept and principles of quantum computing, such as quantum bit, quantum register and quantum parallelism. An analysis is given to the theoretical basis of Grover's algorithm and the performance of Grover's algorithm is evaluated. A novel signal detector based on Grover's algorithm (GD) for MIMO-OFDM system is proposed. The simulation results show that the proposed detector has more powerful properties in bit error rate than MMSE detector and VBLAST-MMSE detector. The performance of the proposed GD detector is close to optimal when the failure probability is 0.001. When the failure probability is 0.00001, the performance of GD detector declines. In this case, our proposed improved Grover's algorithm based detector is still close to the optimal ML detector. The complexity of GD and IGD is O(√N). It's much better than classical ML detector which complexity is O(N). 
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2.
  • Li, Sirui, et al. (författare)
  • Glioma grading, molecular feature classification, and microstructural characterization using MR diffusional variance decomposition (DIVIDE) imaging
  • 2021
  • Ingår i: European Radiology. - : Springer Science and Business Media LLC. - 0938-7994 .- 1432-1084. ; 31:11, s. 8197-8207
  • Tidskriftsartikel (refereegranskat)abstract
    • Objective: To evaluate the potential of diffusional variance decomposition (DIVIDE) for grading, molecular feature classification, and microstructural characterization of gliomas. Materials and methods: Participants with suspected gliomas underwent DIVIDE imaging, yielding parameter maps of fractional anisotropy (FA), mean diffusivity (MD), anisotropic mean kurtosis (MKA), isotropic mean kurtosis (MKI), total mean kurtosis (MKT), MKA/MKT, and microscopic fractional anisotropy (μFA). Tumor type and grade, isocitrate dehydrogenase (IDH) 1/2 mutant status, and the Ki-67 labeling index (Ki-67 LI) were determined after surgery. Statistical analysis included 33 high-grade gliomas (HGG) and 17 low-grade gliomas (LGG). Tumor diffusion metrics were compared between HGG and LGG, among grades, and between wild and mutated IDH types using appropriate tests according to normality assessment results. Receiver operating characteristic and Spearman correlation analysis were also used for statistical evaluations. Results: FA, MD, MKA, MKI, MKT, μFA, and MKA/MKT differed between HGG and LGG (FA: p = 0.047; MD: p = 0.037, others p < 0.001), and among glioma grade II, III, and IV (FA: p = 0.048; MD: p = 0.038, others p < 0.001). All diffusion metrics differed between wild-type and mutated IDH tumors (MKI: p = 0.003; others: p < 0.001). The metrics that best discriminated between HGG and LGGs and between wild-type and mutated IDH tumors were MKT and FA respectively (area under the curve 0.866 and 0.881). All diffusion metrics except FA showed significant correlation with Ki-67 LI, and MKI had the highest correlation coefficient (rs = 0.618). Conclusion: DIVIDE is a promising technique for glioma characterization and diagnosis. Key Points: • DIVIDE metrics MKIis related to cell density heterogeneity while MKAand μFA are related to cell eccentricity. • DIVIDE metrics can effectively differentiate LGG from HGG and IDH mutation from wild-type tumor, and showed significant correlation with the Ki-67 labeling index. • MKIwas larger than MKAwhich indicates predominant cell density heterogeneity in gliomas. • MKAand MKIincreased with grade or degree of malignancy, however with a relatively larger increase in the cell eccentricity metric MKAin relation to the cell density heterogeneity metric MKI.
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3.
  • Parreiras, Lucas S., et al. (författare)
  • Engineering and two-stage evolution of a lignocellulosic hydrolysate-tolerant Saccharomyces cerevisiae strain for anaerobic fermentation of xylose from AFEX pretreated corn stover
  • 2014
  • Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 9:9
  • Tidskriftsartikel (refereegranskat)abstract
    • The inability of the yeast Saccharomyces cerevisiae to ferment xylose effectively under anaerobic conditions is a major barrier to economical production of lignocellulosic biofuels. Although genetic approaches have enabled engineering of S. cerevisiae to convert xylose efficiently into ethanol in defined lab medium, few strains are able to ferment xylose from lignocellulosic hydrolysates in the absence of oxygen. This limited xylose conversion is believed to result from small molecules generated during biomass pretreatment and hydrolysis, which induce cellular stress and impair metabolism. Here, we describe the development of a xylose-fermenting S. cerevisiae strain with tolerance to a range of pretreated and hydrolyzed lignocellulose, including Ammonia Fiber Expansion (AFEX)-pretreated corn stover hydrolysate (ACSH). We genetically engineered a hydrolysate-resistant yeast strain with bacterial xylose isomerase and then applied two separate stages of aerobic and anaerobic directed evolution. The emergent S. cerevisiae strain rapidly converted xylose from lab medium and ACSH to ethanol under strict anaerobic conditions. Metabolomic, genetic and biochemical analyses suggested that a missense mutation in GRE3, which was acquired during the anaerobic evolution, contributed toward improved xylose conversion by reducing intracellular production of xylitol, an inhibitor of xylose isomerase. These results validate our combinatorial approach, which utilized phenotypic strain selection, rational engineering and directed evolution for the generation of a robust S. cerevisiae strain with the ability to ferment xylose anaerobically from ACSH.
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4.
  • Yang, Bin, et al. (författare)
  • Non-invasive (non-contact) measurements of human thermal physiology signals and thermal comfort/discomfort poses -A review
  • 2020
  • Ingår i: Energy and Buildings. - : ELSEVIER SCIENCE SA. - 0378-7788 .- 1872-6178. ; 224
  • Forskningsöversikt (refereegranskat)abstract
    • Heating, ventilation and air-conditioning (HVAC) systems have been adopted to create comfortable, healthy and safe indoor environments. In the control loop, the technical feature of the human demand-oriented supply can help operate HVAC effectively. Among many technical options, real time monitoring based on feedback signals from end users has been frequently reported as a critical technology to confirm optimizing building performance. Recent studies have incorporated human thermal physiology signals and thermal comfort/discomfort status as real-time feedback signals. A series of human subject experiments used to be conducted by primarily adopting subjective questionnaire surveys in a lab-setting study, which is limited in the application for reality. With the help of advanced technologies, physiological signals have been detected, measured and processed by using multiple technical formats, such as wearable sensors. Nevertheless, they mostly require physical contacts with the skin surface in spite of the small physical dimension and compatibility with other wearable accessories, such as goggles, and intelligent bracelets. Most recently, a low cost small infrared camera has been adopted for monitoring human facial images, which could detect the facial skin temperature and blood perfusion in a contact less way. Also, according to latest pilot studies, a conventional digital camera can generate infrared images with the help of new methods, such as the Euler video magnification technology. Human thermal comfort/discomfort poses can also be detected by video methods without contacting human bodies and be analyzed by the skeleton keypoints model. In this review, new sensing technologies were summarized, their cons and pros were discussed, and extended applications for the demand-oriented ventilation were also reviewed as potential development and applications. 
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5.
  • Abedan Kondori, Farid, et al. (författare)
  • A Direct Method for 3D Hand Pose Recovery
  • 2014
  • Ingår i: 2014 22ND INTERNATIONAL CONFERENCE ON PATTERN RECOGNITION (ICPR). - : IEEE COMPUTER SOC. - 9781479952083 ; , s. 345-350
  • Konferensbidrag (refereegranskat)abstract
    • This paper presents a novel approach for performing intuitive 3D gesture-based interaction using depth data acquired by Kinect. Unlike current depth-based systems that focus only on classical gesture recognition problem, we also consider 3D gesture pose estimation for creating immersive gestural interaction. In this paper, we formulate gesture-based interaction system as a combination of two separate problems, gesture recognition and gesture pose estimation. We focus on the second problem and propose a direct method for recovering hand motion parameters. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Our experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation. This application is intended to explore the system capabilities in real-time biomedical applications. Eventually, system usability test is conducted to evaluate the learnability, user experience and interaction quality in 3D interaction in comparison to 2D touch-screen interaction.
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6.
  • Abedan Kondori, Farid, 1983-, et al. (författare)
  • Direct hand pose estimation for immersive gestural interaction
  • 2015
  • Ingår i: Pattern Recognition Letters. - : Elsevier BV. - 0167-8655 .- 1872-7344. ; 66, s. 91-99
  • Tidskriftsartikel (refereegranskat)abstract
    • This paper presents a novel approach for performing intuitive gesture based interaction using depth data acquired by Kinect. The main challenge to enable immersive gestural interaction is dynamic gesture recognition. This problem can be formulated as a combination of two tasks; gesture recognition and gesture pose estimation. Incorporation of fast and robust pose estimation method would lessen the burden to a great extent. In this paper we propose a direct method for real-time hand pose estimation. Based on the range images, a new version of optical flow constraint equation is derived, which can be utilized to directly estimate 3D hand motion without any need of imposing other constraints. Extensive experiments illustrate that the proposed approach performs properly in real-time with high accuracy. As a proof of concept, we demonstrate the system performance in 3D object manipulation On two different setups; desktop computing, and mobile platform. This reveals the system capability to accommodate different interaction procedures. In addition, a user study is conducted to evaluate learnability, user experience and interaction quality in 3D gestural interaction in comparison to 2D touchscreen interaction.
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7.
  • Abedan Kondori, Farid, 1983-, et al. (författare)
  • Head Operated Electric Wheelchair
  • 2014
  • Ingår i: Proceedings of the IEEE Southwest Symposium on Image Analysis and Interpretation. - : IEEE Press. - 9781479940530 ; , s. 53-56
  • Konferensbidrag (refereegranskat)abstract
    • Currently, the most common way to control an electric wheelchair is to use joystick. However, there are some individuals unable to operate joystick-driven electric wheelchairs due to sever physical disabilities, like quadriplegia patients. This paper proposes a novel head pose estimation method to assist such patients. Head motion parameters are employed to control and drive an electric wheelchair. We introduce a direct method for estimating user head motion, based on a sequence of range images captured by Kinect. In this work, we derive new version of the optical flow constraint equation for range images. We show how the new equation can be used to estimate head motion directly. Experimental results reveal that the proposed system works with high accuracy in real-time. We also show simulation results for navigating the electric wheelchair by recovering user head motion.
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8.
  • Cheng, Xiaogang, et al. (författare)
  • A Contactless Measuring Method of Skin Temperature based on the Skin Sensitivity Index and Deep Learning
  • 2019
  • Ingår i: Applied Sciences. - Switzerland : MDPI. - 2076-3417 .- 1454-5101. ; 9:7
  • Tidskriftsartikel (refereegranskat)abstract
    • Featured Application The NISDL method proposed in this paper can be used for real time contactless measuring of human skin temperature, which reflects human body thermal comfort status and can be used for control HVAC devices. Abstract In human-centered intelligent building, real-time measurements of human thermal comfort play critical roles and supply feedback control signals for building heating, ventilation, and air conditioning (HVAC) systems. Due to the challenges of intra- and inter-individual differences and skin subtleness variations, there has not been any satisfactory solution for thermal comfort measurements until now. In this paper, a contactless measuring method based on a skin sensitivity index and deep learning (NISDL) was proposed to measure real-time skin temperature. A new evaluating index, named the skin sensitivity index (SSI), was defined to overcome individual differences and skin subtleness variations. To illustrate the effectiveness of SSI proposed, a two multi-layers deep learning framework (NISDL method I and II) was designed and the DenseNet201 was used for extracting features from skin images. The partly personal saturation temperature (NIPST) algorithm was use for algorithm comparisons. Another deep learning algorithm without SSI (DL) was also generated for algorithm comparisons. Finally, a total of 1.44 million image data was used for algorithm validation. The results show that 55.62% and 52.25% error values (NISDL method I, II) are scattered at (0 degrees C, 0.25 degrees C), and the same error intervals distribution of NIPST is 35.39%.
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9.
  • Fahlquist, Karin, et al. (författare)
  • Human animal machine interaction : Animal behavior awareness and digital experience
  • 2010
  • Ingår i: Proceedings of ACM Multimedia 2010 - Brave New Ideas, 25-29 October 2010, Firenze, Italy.. - New York, NY, USA : ACM. - 9781605589336 ; , s. 1269-1274
  • Konferensbidrag (refereegranskat)abstract
    • This paper proposes an intuitive wireless sensor/actuator based communication network for human animal interaction for a digital zoo. In order to enhance effective observation and control over wild life, we have built a wireless sensor network. 25 video transmitting nodes are installed for animal behavior observation and experimental vibrotactile collars have been designed for effective control in an animal park. The goal of our research is two-folded. Firstly, to provide an interaction between digital users and animals, and monitor the animal behavior for safety purposes. Secondly, we investigate how animals can be controlled or trained based on vibrotactile stimuli instead of electric stimuli. We have designed a multimedia sensor network for human animal machine interaction. We have evaluated the effect of human animal machine state communication model in field experiments.
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10.
  • Kondori, Abedan Farid, et al. (författare)
  • Direct hand pose estimation for immersive gestural interaction
  • Annan publikation (populärvet., debatt m.m.)abstract
    • This paper presents a novel approach for performing intuitive gesture-based interactionusing depth data acquired by Kinect. The main challenge to enableimmersive gestural interaction is dynamic gesture recognition. This problemcan be formulated as a combination of two tasks; gesture recognition and gesturepose estimation. Incorporation of fast and robust pose estimation methodwould lessen the burden to a great extent. In this paper we propose a directmethod for real-time hand pose estimation. Based on the range images, a newversion of optical flow constraint equation is derived, which can be utilizedto directly estimate 3D hand motion without any need of imposing other constraints.Extensive experiments illustrate that the proposed approach performsproperly in real-time with high accuracy. As a proof of concept, we demonstratethe system performance in 3D object manipulation on two dierent setups;desktop computing, and mobile platform. This reveals the system capabilityto accommodate dierent interaction procedures. In addition, user studyis conducted to evaluate learnability, user experience and interaction quality in3D gestural interaction in comparison to 2D touch-screen interaction.
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