43234278
A Ramsey Goodness Result for Graphs with Many Pendant Edges
2037433
An upper bound for ramsey numbers
Let G″ be a graph obtained from G by deleting two vertices. It is shown that r(G, H) ⩽ A + B + 2 + 2 (A2 + AB + B2)3 where A = r(G″, H) and B = r(G,H″).
206570728
On Book-Complete Graph Ramsey Numbers
It is shown that a graph of orderNand average degreedthat does not contain the bookBm=K1+K1, mas a subgraph has independence number at leastNf(d), wheref(x)~(logx/x)(x?∞). From this result we find that the book-complete graph Ramsey number satisfiesr(Bm, Kn)?mn2/log(n/e). It is also shown that for every treeTmwithmedges,r(K1+Tm,Kn)?(2m?1)n2/log(n/e).
8083367
On Some Three-Color Ramsey Numbers
Abstract. In this paper we study three-color Ramsey numbers. Let Ki,j denote a complete i by j bipartite graph. We shall show that (i) for any connected graphs G1, G2 and G3, if r(G1, G2)≥s(G3), then r(G1, G2, G3)≥(r(G1, G2)−1)(χ(G3)−1)+s(G3), where s(G3) is the chromatic surplus of G3; (ii) (k+m−2)(n−1)+1≤r(K1,k, K1,m, Kn)≤ (k+m−1)(n−1)+1, and if k or m is odd, the second inequality becomes an equality; (iii) for any fixed m≥k≥2, there is a constant c such that r(Kk,m, Kk,m, Kn)≤c(n/logn), and r(C2m, C2m, Kn)≤c(n/logn)m/(m−1) for sufficiently large n.
34447441
Asymptotic bounds for some bipartite graph: complete graph Ramsey numbers
Abstract The Ramsey number r(H,Kn) is the smallest integer N so that each graph on N vertices that fails to contain H as a subgraph has independence number at least n. It is shown that r(K 2,m ,K n )⩽(m−1+ o (1))(n/ log n) 2 and r(C 2m ,K n )⩽c(n/ log n) m/(m−1) for m fixed and n→∞. Also r(K 2,n ,K n )=Θ(n 3 / log 2 n) and r(C 5 ,K n )⩽cn 3/2 / log n .
34644814
The Independence Number of Graphs with a Forbidden Cycle and Ramsey Numbers
Let k ≥ 5 be a fixed integer and let m = ⌊(k − 1)/2⌋. It is shown that the independence number of a Ck-free graph is at least c1[∑ d(v)1/(m − 1)](m − 1)/m and that, for odd k, the Ramsey number r(Ck, Kn) is at most c2(nm + 1/log n)1/m, where c1 = c1(m) > 0 and c2 = c2(m) > 0.
1293275
Getting work done on the web: supporting transactional queries
Many searches on the web have a transactional intent. We argue that pages satisfying transactional needs can be distinguished from the more common pages that have some information and links, but cannot be used to execute a transaction. Based on this hypothesis, we provide a recipe for constructing a transaction annotator. By constructing an annotator with one corpus and then demonstrating its classification performance on another,we establish its robustness. Finally, we show experimentally that a search procedure that exploits such pre-annotation greatly outperforms traditional search for retrieving transactional pages.
6924123
Publicly verifiable ownership protection for relational databases
Today, watermarking techniques have been extended from the multimedia context to relational databases so as to protect the ownership of data even after the data are published or distributed. However, all existing watermarking schemes for relational databases are secret key based, thus require a secret key to be presented in proof of ownership. This means that the ownership can only be proven once to the public (e.g., to the court). After that, the secret key is known to the public and the embedded watermark can be easily destroyed by malicious users. Moreover, most of the existing techniques introduce distortions to the underlying data in the watermarking process, either by modifying least significant bits or exchanging categorical values. The distortions inevitably reduce the value of the data. In this paper, we propose a watermarking scheme by which the ownership of data can be publicly proven by anyone, as many times as necessary. The proposed scheme is distortion-free, thus suitable for watermarking any type of data without fear of error constraints. The proposed scheme is robust against typical database attacks including tuple/attribute insertion/deletion, random/selective value modification, data frame-up, and additive attacks.
6040880
Rupture degree of graphs
We introduce a new graph parameter, the rupture degree. The rupture degree for a complete graph K n is defined as 1−n, and the rupture degree for an incomplete connected graph G is defined by r(G)=max{ω(G−X)−|X|−m(G−X):X⊂V(G), ω(G−X)>1}, where ω(G−X) is the number of components of G−X and m(G−X) is the order of a largest component of G−X. It is shown that this parameter can be used to measure the vulnerability of networks. Rupture degrees of several specific classes of graphs are determined. Formulas for the rupture degree of join graphs and some bounds of the rupture degree are given. We also obtain some Nordhaus–Gaddum type results for the rupture degree.
12892539
Experimental analysis of mode switching techniques in pen-based user interfaces
Inking and gesturing are two central tasks in pen-based user interfaces. Switching between modes for entry of uninterpreted ink and entry of gestures is required by many pen-based user interfaces. Without an appropriate mode switching technique, pen-based interactions in such situations may be inefficient and cumbersome. In this paper, we investigate five techniques for switching between ink and gesture modes in pen interfaces, including a pen-pressure based mode switching technique that allows implicit mode transition. A quantitative experimental study was conducted to evaluate the performance of these techniques. The results suggest that pressing a button with the non-preferred hand offers the fastest performance, while the technique of holding the pen still is significantly slower and more prone to error than the other techniques. Pressure, while promising, did not perform as well as the non-preferred hand button with our current implementation.
1415624
A spiking recurrent neural network
A spiking recurrent neural network implementing an associative memory is proposed. The circuit including four integrate-and-fire (IF) and Willshaw-type binary synapses is designed with the AMI 0.5/spl mu/m CMOS process. A large-scale network is simulated with Matlab and its storage capacity is calculated and analyzed.