25,506 research outputs found
Word Activation Forces Map Word Networks
Words associate with each other in a manner of intricate clusters^1-3^. Yet the brain capably encodes the complex relations into workable networks^4-7^ such that the onset of a word in the brain automatically and selectively activates its associates, facilitating language understanding and generation^8-10^. One believes that the activation strength from one word to another forges and accounts for the latent structures of the word networks. This implies that mapping the word networks from brains to computers^11,12^, which is necessary for various purposes^1,2,13-15^, may be achieved through modeling the activation strengths. However, although a lot of investigations on word activation effects have been carried out^8-10,16-20^, modeling the activation strengths remains open. Consequently, huge labor is required to do the mappings^11,12^. Here we show that our found word activation forces, statistically defined by a formula in the same form of the universal gravitation, capture essential information on the word networks, leading to a superior approach to the mappings. The approach compatibly encodes syntactical and semantic information into sparse coding directed networks, comprehensively highlights the features of individual words. We find that based on the directed networks, sensible word clusters and hierarchies can be efficiently discovered. Our striking results strongly suggest that the word activation forces might reveal the encoding of word networks in the brain
Movement-efficient Sensor Deployment in Wireless Sensor Networks
We study a mobile wireless sensor network (MWSN) consisting of multiple
mobile sensors or robots. Two key issues in MWSNs - energy consumption, which
is dominated by sensor movement, and sensing coverage - have attracted plenty
of attention, but the interaction of these issues is not well studied. To take
both sensing coverage and movement energy consumption into consideration, we
model the sensor deployment problem as a constrained source coding problem. %,
which can be applied to different coverage tasks, such as area coverage, target
coverage, and barrier coverage. Our goal is to find an optimal sensor
deployment to maximize the sensing coverage with specific energy constraints.
We derive necessary conditions to the optimal sensor deployment with (i) total
energy constraint and (ii) network lifetime constraint. Using these necessary
conditions, we design Lloyd-like algorithms to provide a trade-off between
sensing coverage and energy consumption. Simulation results show that our
algorithms outperform the existing relocation algorithms.Comment: 18 pages, 10 figure
Development of Novel Calibrations for FT-NIR Analysis of Protein, Oil, Carbohydrates and Isoflavones in Foods
The development of calibration methodology for novel FT-NIRS analysis of soybean-based foods is presented together with high-precision NIRS spectra and composition measurements in terms of proteins, oil and carbohydrates in soybean-based foods/soy foods.

A construction of pooling designs with surprisingly high degree of error correction
It is well-known that many famous pooling designs are constructed from
mathematical structures by the "containment matrix" method. In this paper, we
propose another method and obtain a family of pooling designs with surprisingly
high degree of error correction based on a finite set. Given the numbers of
items and pools, the error-tolerant property of our designs is much better than
that of Macula's designs when the size of the set is large enough
Movement-Efficient Sensor Deployment in Wireless Sensor Networks With Limited Communication Range.
We study a mobile wireless sensor network (MWSN) consisting of multiple
mobile sensors or robots. Three key factors in MWSNs, sensing quality, energy
consumption, and connectivity, have attracted plenty of attention, but the
interaction of these factors is not well studied. To take all the three factors
into consideration, we model the sensor deployment problem as a constrained
source coding problem. %, which can be applied to different coverage tasks,
such as area coverage, target coverage, and barrier coverage. Our goal is to
find an optimal sensor deployment (or relocation) to optimize the sensing
quality with a limited communication range and a specific network lifetime
constraint. We derive necessary conditions for the optimal sensor deployment in
both homogeneous and heterogeneous MWSNs. According to our derivation, some
sensors are idle in the optimal deployment of heterogeneous MWSNs. Using these
necessary conditions, we design both centralized and distributed algorithms to
provide a flexible and explicit trade-off between sensing uncertainty and
network lifetime. The proposed algorithms are successfully extended to more
applications, such as area coverage and target coverage, via properly selected
density functions. Simulation results show that our algorithms outperform the
existing relocation algorithms
Pooling designs with surprisingly high degree of error correction in a finite vector space
Pooling designs are standard experimental tools in many biotechnical
applications. It is well-known that all famous pooling designs are constructed
from mathematical structures by the "containment matrix" method. In particular,
Macula's designs (resp. Ngo and Du's designs) are constructed by the
containment relation of subsets (resp. subspaces) in a finite set (resp. vector
space). Recently, we generalized Macula's designs and obtained a family of
pooling designs with more high degree of error correction by subsets in a
finite set. In this paper, as a generalization of Ngo and Du's designs, we
study the corresponding problems in a finite vector space and obtain a family
of pooling designs with surprisingly high degree of error correction. Our
designs and Ngo and Du's designs have the same number of items and pools,
respectively, but the error-tolerant property is much better than that of Ngo
and Du's designs, which was given by D'yachkov et al. \cite{DF}, when the
dimension of the space is large enough
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