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排序方式: 共有1811条查询结果,搜索用时 46 毫秒
51.
Tamada Tsutomu Ueda Yu Kido Ayumu Yoneyama Masami Takeuchi Mitsuru Sanai Hiroyasu Ono Kentaro Yamamoto Akira Sone Teruki 《Magma (New York, N.Y.)》2022,35(4):549-556
Magnetic Resonance Materials in Physics, Biology and Medicine - Image quality (IQ) of diffusion-weighted imaging (DWI) with single-shot echo-planar imaging (ssEPI) suffers from low signal-to-noise... 相似文献
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54.
Greedy versus social: resource-competing oscillator network as a model of amoeba-based neurocomputer
A single-celled amoeboid organism, the true slime mold Physarum polycephalum, exhibits rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. The authors previously created
a biocomputer that incorporates the organism as a computing substrate to search for solutions to combinatorial optimization
problems. With the assistance of optical feedback to implement a recurrent neural network model, the organism changes its
shape by alternately growing and withdrawing its photosensitive branches so that its body area can be maximized and the risk
of being illuminated can be minimized. In this way, the organism succeeded in finding the optimal solution to the four-city
traveling salesman problem with a high probability. However, it remains unclear how the organism collects, stores, and compares
information on light stimuli using the oscillatory dynamics. To study these points, we formulate an ordinary differential
equation model of the amoeba-based neurocomputer, considering the organism as a network of oscillators that compete for a
fixed amount of intracellular resource. The model, called the “Resource-Competing Oscillator Network (RCON) model,” reproduces
well the organism’s experimentally observed behavior, as it generates a number of spatiotemporal oscillation modes by keeping
the total sum of the resource constant. Designing the feedback rule properly, the RCON model comes to face a problem of optimizing
the allocation of the resource to its nodes. In the problem-solving process, “greedy” nodes having the highest competitiveness
are supposed to take more resource out of other nodes. However, the resource allocation pattern attained by the greedy nodes
cannot always achieve a “socially optimal” state in terms of the public cost. We prepare four test problems including a tricky
one in which the greedy pattern becomes “socially unfavorable” and investigate how the RCON model copes with these problems.
Comparing problem-solving performances of the oscillation modes, we show that there exist some modes often attain socially
favorable patterns without being trapped in the greedy one. 相似文献
55.
Kazuto Okazaki Tatsuya Ogiwara Dongshin Yang Kentaro Sakata Ken Saito Yoshifumi Sekine Fumio Uchikoba 《Artificial Life and Robotics》2011,16(2):229-233
This article presents the micro-electro-mechanical systems (MEMS) microrobot which demonstrates locomotion controlled by hardware
neural networks (HNN). The size of the microrobot fabricated by the MEMS technology is 4 × 4 × 3.5 mm. The frame of the robot
is made of silicon wafer, and it is equipped with a rotary-type actuator, a link mechanism, and six legs. The rotary-type
actuator generates rotational movement by applying an electrical current to artificial muscle wires. The locomotion of the
microrobot is obtained by the rotation of the rotary-type actuator. As in a living organism, the HNN realized robot control
without using any software programs, A/D converters, or additional driving circuits. A central pattern generator (CPG) model
was implemented as an HNN system to emulate the locomotion pattern. The MEMS microrobot emulated the locomotion method and
the neural networks of an insect with the rotary-type actuator, the link mechanism, and the HNN. The microrobot performed
forward and backward locomotion, and also changed direction by inputting an external trigger pulse. The locomotion speed was
0.325 mm/s and the step width was 1.3 mm. 相似文献
56.
We present and analyze an unsupervised method for Word Sense Disambiguation (WSD). Our work is based on the method presented
by McCarthy et al. in 2004 for finding the predominant sense of each word in the entire corpus. Their maximization algorithm allows weighted
terms (similar words) from a distributional thesaurus to accumulate a score for each ambiguous word sense, i.e., the sense
with the highest score is chosen based on votes from a weighted list of terms related to the ambiguous word. This list is
obtained using the distributional similarity method proposed by Lin Dekang to obtain a thesaurus. In the method of McCarthy
et al., every occurrence of the ambiguous word uses the same thesaurus, regardless of the context where the ambiguous word occurs.
Our method accounts for the context of a word when determining the sense of an ambiguous word by building the list of distributed
similar words based on the syntactic context of the ambiguous word. We obtain a top precision of 77.54% of accuracy versus
67.10% of the original method tested on SemCor. We also analyze the effect of the number of weighted terms in the tasks of
finding the Most Frecuent Sense (MFS) and WSD, and experiment with several corpora for building the Word Space Model. 相似文献
57.
Amoeba-based Chaotic Neurocomputing: Combinatorial Optimization by Coupled Biological Oscillators 总被引:1,自引:0,他引:1
Masashi Aono Yoshito Hirata Masahiko Hara Kazuyuki Aihara 《New Generation Computing》2009,27(2):129-157
We demonstrate a neurocomputing system incorporating an amoeboid unicellular organism, the true slime mold Physarum, known to exhibit rich spatiotemporal oscillatory behavior and sophisticated computational capabilities. Introducing optical
feedback applied according to a recurrent neural network model, we induce that the amoeba’s photosensitive branches grow or
degenerate in a network-patterned chamber in search of an optimal solution to the traveling salesman problem (TSP), where
the solution corresponds to the amoeba’s stably relaxed configuration (shape), in which its body area is maximized while the
risk of being illuminated is minimized.Our system is capable of reaching the optimal solution of the four-city TSP with a
high probability. Moreover, our system can find more than one solution, because the amoeba can coordinate its branches’ oscillatory
movements to perform transitional behavior among multiple stable configurations by spontaneously switching between the stabilizing
and destabilizing modes. We show that the optimization capability is attributable to the amoeba’s fluctuating oscillatory
movements. Applying several surrogate data analyses, we present results suggesting that the amoeba can be characterized as
a set of coupled chaotic oscillators.
相似文献
Kazuyuki AiharaEmail: |
58.
This paper presents an algebraic approach to polynomial spectral factorization, an important mathematical tool in signal processing and control. The approach exploits an intriguing relationship between the theory of Gröbner bases and polynomial spectral factorization which can be observed through the sum of roots, and allows us to perform polynomial spectral factorization in the presence of real parameters. It is discussed that parametric polynomial spectral factorization enables us to express quantities such as the optimal cost in terms of parameters and the sum of roots. Furthermore an optimization method over parameters is suggested that makes use of the results from parametric polynomial spectral factorization and also employs two quantifier elimination techniques. This proposed approach is demonstrated in a numerical example of a particular control problem. 相似文献
59.
Ram C. Sharma Ryutaro Tateishi Keitarou Hara 《International journal of remote sensing》2016,37(11):2706-2723
An up-to-date spatio-temporal change analysis of global snow cover is essential for better understanding of climate–hydrological interactions. The normalized difference snow index (NDSI) is a widely used algorithm for the detection and estimation of snow cover. However, NDSI cannot discriminate between snow cover and water bodies without use of an external water mask. A stand-alone methodology for robust detection and mapping of global snow cover is presented by avoiding external dependency on the water mask. A new spectral index called water-resistant snow index (WSI) with the capability of exhibiting significant contrast between snow cover and other cover types, including water bodies, was developed. WSI uses the normalized difference between the value and hue obtained by transforming red, green, and blue, (RGB) colour composite images comprising red, green, and near-infrared bands into a hue, saturation, and value (HSV) colour model. The superiority of WSI over NDSI is confirmed by case studies conducted in major snow regions globally. Snow cover was mapped by considering monthly variation in snow cover and availability of satellite data at the global scale. A snow cover map for the year 2013 was produced at the global scale by applying the random walker algorithm in the WSI image supported by the reference data collected from permanent snow-covered and non-snow-covered areas. The resultant snow-cover map was compared to snow cover estimated by existing maps: MODIS Land Cover Type Product (MCD12Q1 v5.1, 2012), Global Land Cover by National Mapping Organizations (GLCNMO v2.0, 2008), and European Space Agency’s GlobCover 2009. A significant variation in snow cover as estimated by different maps was noted, and was was attributed to methodological differences rather than annual variation in snow cover. The resultant map was also validated with reference data, with 89.46% overall accuracy obtained. The WSI proposed in the research is expected to be suitable for seasonal and annual change analysis of global snow cover. 相似文献
60.
Daichi Amagata Yuya Sasaki Takahiro Hara Shojiro Nishio 《Distributed and Parallel Databases》2016,34(2):259-287
A nearest neighbor (NN) query, which returns the most similar object to a user-specified query object, plays an important role in a wide range of applications and hence has received considerable attention. In many such applications, e.g., sensor data collection and location-based services, objects are inherently uncertain. Furthermore, due to the ever increasing generation of massive datasets, the importance of distributed databases, which deal with such data objects, has been growing. One emerging challenge is to efficiently process probabilistic NN queries over distributed uncertain databases. The straightforward approach, that each local site forwards its own database to the central server, is communication-expensive, so we have to minimize communication cost for the NN object retrieval. In this paper, we focus on two important queries, namely top-k probable NN queries and probabilistic star queries, and propose efficient algorithms to process them over distributed uncertain databases. Extensive experiments on both real and synthetic data have demonstrated that our algorithms significantly reduce communication cost. 相似文献