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Institution

Mitsubishi Electric

CompanyRatingen, Germany
About: Mitsubishi Electric is a company organization based out in Ratingen, Germany. It is known for research contribution in the topics: Signal & Voltage. The organization has 23024 authors who have published 27591 publications receiving 255671 citations. The organization is also known as: Mitsubishi Electric Corporation & Mitsubishi Denki K.K..


Papers
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Journal ArticleDOI
TL;DR: It is demonstrated by computer simulation and laboratory experiments that the pilot symbol-aided fading compensation can sufficiently compensate for fast varying Rayleigh fading, and 16-QAM gives the highest spectral efficiency in the case of cellular systems.
Abstract: A pilot symbol-aided Rayleigh fading compensation is investigated for M-ary quadrature amplitude modulation (QAM) to achieve highly spectrally efficient land mobile communication systems. The optimum parameters for fading compensation, bit error rate (BER) performance against E/sub b//N/sub 0/ (energy per bit to the noise power spectrum density), adjacent channel interference, and cochannel interference for 16-QAM, 64-QAM, and 256-QAM, and the spectral efficiencies for these modulation schemes in Rayleigh fading environments are investigated by computer simulation. To further verify the effect of pilot symbol-aided fading compensation from a a practical point of view, a 16-QAM modem is implemented, laboratory experiments are executed, and the impact of the dynamic range limitation due to the resolution of the analog-to-digital (A/D) converters is evaluated, along with the imperfection of the analog circuits. It is demonstrated by computer simulation and laboratory experiments that the pilot symbol-aided fading compensation can sufficiently compensate for fast varying Rayleigh fading, and 16-QAM gives the highest spectral efficiency in the case of cellular systems. >

262 citations

Book ChapterDOI
08 Sep 2018
TL;DR: A novel weakly-supervised TAL framework called AutoLoc is developed to directly predict the temporal boundary of each action instance and a novel Outer-Inner-Contrastive (OIC) loss is proposed to automatically discover the needed segment-level supervision for training such a boundary predictor.
Abstract: Temporal Action Localization (TAL) in untrimmed video is important for many applications. But it is very expensive to annotate the segment-level ground truth (action class and temporal boundary). This raises the interest of addressing TAL with weak supervision, namely only video-level annotations are available during training). However, the state-of-the-art weakly-supervised TAL methods only focus on generating good Class Activation Sequence (CAS) over time but conduct simple thresholding on CAS to localize actions. In this paper, we first develop a novel weakly-supervised TAL framework called AutoLoc to directly predict the temporal boundary of each action instance. We propose a novel Outer-Inner-Contrastive (OIC) loss to automatically discover the needed segment-level supervision for training such a boundary predictor. Our method achieves dramatically improved performance: under the IoU threshold 0.5, our method improves mAP on THUMOS’14 from 13.7% to 21.2% and mAP on ActivityNet from 7.4% to 27.3%. It is also very encouraging to see that our weakly-supervised method achieves comparable results with some fully-supervised methods.

261 citations

Posted Content
TL;DR: The authors presented an algorithm combining variants of Winnow and weighted-majority voting, and applied it to a problem in the aforementioned class: context-sensitive spelling correction, which is the task of fixing spelling errors that happen to result in valid words, such as substituting "to" for "too", "casual" for 'causal", etc.
Abstract: A large class of machine-learning problems in natural language require the characterization of linguistic context. Two characteristic properties of such problems are that their feature space is of very high dimensionality, and their target concepts refer to only a small subset of the features in the space. Under such conditions, multiplicative weight-update algorithms such as Winnow have been shown to have exceptionally good theoretical properties. We present an algorithm combining variants of Winnow and weighted-majority voting, and apply it to a problem in the aforementioned class: context-sensitive spelling correction. This is the task of fixing spelling errors that happen to result in valid words, such as substituting "to" for "too", "casual" for "causal", etc. We evaluate our algorithm, WinSpell, by comparing it against BaySpell, a statistics-based method representing the state of the art for this task. We find: (1) When run with a full (unpruned) set of features, WinSpell achieves accuracies significantly higher than BaySpell was able to achieve in either the pruned or unpruned condition; (2) When compared with other systems in the literature, WinSpell exhibits the highest performance; (3) The primary reason that WinSpell outperforms BaySpell is that WinSpell learns a better linear separator; (4) When run on a test set drawn from a different corpus than the training set was drawn from, WinSpell is better able than BaySpell to adapt, using a strategy we will present that combines supervised learning on the training set with unsupervised learning on the (noisy) test set.

253 citations

Journal ArticleDOI
TL;DR: The mobile agent concept grows out of three earlier technologies: process migration, remote evaluation, and mobile objects—all developed to improve on remote procedure calling for distributed programming.
Abstract: The mobile agent concept grows out of three earlier technologies: process migration [5], remote evaluation [7], and mobile objects [3]—all developed to improve on remote procedure calling (RPC) for distributed programming. Early systems supporting process migration allowed an entire address space to be moved from one computer to another. One goal of this mechanism was to reduce network bandwidth (compared to RPC) when multiple RPC calls are needed to execute an application. While process migration allowed an entire process to be transferred to a remote host, this mechanism did not allow an easy way to return data back to the source node without the entire process returning as well (see Figure 1). Next came remote evaluation programming, allowing one computer to send another computer a request in the form of a program (rather than an entire process address space). The remote computer receiving such a request executes the program referenced in the request within its own local address space and returns the results to the sending computer. Remote evaluation systems improved on he Internet and the World-Wide Web have become

246 citations

Journal ArticleDOI
19 Apr 2019-Science
TL;DR: The Hayabusa2 team's study of the near-Earth carbonaceous asteroid 162173 Ryugu, at which the spacecraft arrived in June 2018, describes Ryugu's geological features and surface colors and combined results from all three papers to constrain the asteroid's formation process.
Abstract: The near-Earth asteroid 162173 Ryugu, the target of the Hayabusa2 sample-return mission, is thought to be a primitive carbonaceous object. We report reflectance spectra of Ryugu's surface acquired with the Near-Infrared Spectrometer (NIRS3) on Hayabusa2, to provide direct measurements of the surface composition and geological context for the returned samples. A weak, narrow absorption feature centered at 2.72 micrometers was detected across the entire observed surface, indicating that hydroxyl (OH)-bearing minerals are ubiquitous there. The intensity of the OH feature and low albedo are similar to thermally and/or shock-metamorphosed carbonaceous chondrite meteorites. There are few variations in the OH-band position, which is consistent with Ryugu being a compositionally homogeneous rubble-pile object generated from impact fragments of an undifferentiated aqueously altered parent body.

244 citations


Authors

Showing all 23025 results

NameH-indexPapersCitations
Ron Kikinis12668463398
William T. Freeman11343269007
Takashi Saito112104152937
Andreas F. Molisch9677747530
Markus Gross9158832881
Michael Wooldridge8754350675
Ramesh Raskar8667030675
Dan Roth8552328166
Joseph Katz8169127793
James S. Harris80115228467
Michael Mitzenmacher7942236300
Hanspeter Pfister7946623935
Dustin Anderson7860728052
Takashi Hashimoto7398324644
Masaaki Tanaka7186022443
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20224
2021327
20201,060
20191,605
20181,517
20171,090