This paper presents the evaluation of a healthcare service robot system with vital signs measurement and medication reminders. The design followed the methodology proposed in [7]. This study is a first step to evaluat...
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Real time multimedia content transmission on the Internet is essential for the most current applications such as voice over IP, video conference, games and web TV. The most popular Internet transport protocols - TCP a...
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The main idea behind this project is to provide a unified platform which will cover a complete process for embedded systems learning. A modular approach is considered for skills practice through supporting individuali...
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The main idea behind this project is to provide a unified platform which will cover a complete process for embedded systems learning. A modular approach is considered for skills practice through supporting individualization in learning. This platform shall facilitate a novel development of universal approach in creative learning environment and knowledge management that encourage use of ICT. New learning model is challenging the education of engineers in embedded systems design through real-time experiments that stimulate curiosity with ultimate goal to support students to understand and construct their personal conceptual knowledge based on experiments. In addition to the technological approach, the use of cognitive theories on how people learn will help students to achieve a stronger and smarter adaptation of the subject. Applied methodology will be evaluated from the scientific point of view in parallel with the implementation in order to feedback results to the R&D.
We consider the problem of cardinality penalized optimization of a convex function over the probability simplex with additional convex constraints. The classical 1 regularizer fails to promote sparsity on the probabil...
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ISBN:
(纸本)9781627480031
We consider the problem of cardinality penalized optimization of a convex function over the probability simplex with additional convex constraints. The classical 1 regularizer fails to promote sparsity on the probability simplex since 1 norm on the probability simplex is trivially constant. We propose a direct relaxation of the minimum cardinality problem and show that it can be efficiently solved using convex programming. As a first application we consider recovering a sparse probability measure given moment constraints, in which our formulation becomes linear programming, hence can be solved very efficiently. A sufficient condition for exact recovery of the minimum cardinality solution is derived for arbitrary affine constraints. We then develop a penalized version for the noisy setting which can be solved using second order cone programs. The proposed method outperforms known rescaling heuristics based on 1 norm. As a second application we consider convex clustering using a sparse Gaussian mixture and compare our results with the well known soft k-means algorithm.
With the rapid development of computing technologies and broadband wireless communications, mobile computing and networking has been a hot research area recently. This special section focuses on the most recent advanc...
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With the rapid development of computing technologies and broadband wireless communications, mobile computing and networking has been a hot research area recently. This special section focuses on the most recent advances in the frontier research of mobile computing and networking, which is the output of the cooperation between JCST and CHINACOM2012. CHINACOM2012 is the 7th International Conference on Communications and Networking in China, which was held successfully in Kunming, China in August 2012.
We propose a natural process for allocating n balls into n bins that are organized as the vertices of an undirected graph G. Each ball first chooses a vertex u in G uniformly at random. Then the ball performs a local ...
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ISBN:
(纸本)9781627484855
We propose a natural process for allocating n balls into n bins that are organized as the vertices of an undirected graph G. Each ball first chooses a vertex u in G uniformly at random. Then the ball performs a local search in G starting from u until it reaches a vertex with local minimum load, where the ball is finally placed on. In our main result, we prove that this process yields a maximum load of only Θ (log log n) on expander graphs. In addition, we show that for d-dimensional grids the maximum load is Θ((log n/log log n)~(1/d+1)). Finally, for almost regular graphs with minimum degree Θ (logn), we prove that the maximum load is constant and also reveal a fundamental difference between random and arbitrary tie-breaking rules.
In this paper we present an optimization of the Optimum-Path Forest classifier training procedure, which is based on a theoretical relationship between minimum spanning forest and optimum-path forest for a specific pa...
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IEEE 802.15.4/ZigBee sensor networks support small power consumption and node expansion compared to other network standards for WSN. Body sensor networks (BSN) require a number of sensors for sensing medical informati...
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This paper presents an efficient parallel algorithm for a new class of min-max problems based on the matrix multiplicative weights update method. Our algorithm can be used to find near-optimal strategies for competiti...
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This paper presents an efficient parallel algorithm for a new class of min-max problems based on the matrix multiplicative weights update method. Our algorithm can be used to find near-optimal strategies for competitive two-player classical or quantum games in which a referee exchanges any number of messages with one player followed by any number of additional messages with the other. This algorithm considerably extends the class of games which admit parallel solutions, demonstrating for the first time the existence of a parallel algorithm for a game in which one player reacts adaptively to the other. As a consequence, we prove that several competing-provers complexity classes collapse to PSPACE such as QRG(2), SQG and two new classes called DIP and DQIP. A special case of our result is a parallel approximation scheme for a new class of semi definite programs whose feasible region consists of lists of semi definite matrices that satisfy a ``transcript-like'' consistency condition. Applied to this special case, our algorithm yields a direct polynomial-space simulation of multi-message quantum interactive proofs resulting in a first-principles proof of QIP=PSPACE.
The Guest Editors' primary objective in organizing this Special Issue was to provide additional impetus for research in hardware security. Currently, the field is heavily dominated by testing, CAD, and IC research...
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The Guest Editors' primary objective in organizing this Special Issue was to provide additional impetus for research in hardware security. Currently, the field is heavily dominated by testing, CAD, and IC researchers. They hope that researchers from other security fields will find the problems and the proposed solutions published here both interesting and important. Ten Special Issue papers are represented in this collection.
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