Using Nondeterminism to Design Efficient Deterministic Algorithms

In this paper we illustrate how nondeterminism can be used conveniently and effectively in designing efficient deterministic algorithms. In particular, our method gives a parameterized algorithm of running time O((5.7 k)^k n) for the 3-D matching problem, which significantly improves the previous algorithm by Downey et al. The algorithm can be generalized to yield an improved algorithm for the r-D matching problem for any positive integer r. The method can also be employed in designing deterministic algorithms for other optimization problems as well.     

A novel Arabic OCR post-processing using rule-based and word context techniques

International Journal on Document Analysis and Recognition (IJDAR) - Optical character recognition (OCR) is the process of recognizing characters automatically from scanned documents for editing,...     

An efficient multi-predictor reversible data hiding algorithm based on performance evaluation of different prediction schemes

Multimedia Tools and Applications - With the broad development and evolution of digital data exchange, security has become an important issue in data storage and transmission since digital data can...     

CdS-sensitized TiO2 in phenazopyridine photo-degradation: Catalyst efficiency,stability and feasibility assessment

Mineralization of phenazopyridine, 1, in water, under solar-simulator radiation was efficiently achieved using nanoparticle CdS-sensitized rutile TiO₂, TiO₂/CdS, 2, as photo-catalysts. Despite that, 2 showed two main drawbacks. Firstly, the system was difficult to recover by simple filtration, and demanded centrifugation. Secondly, the sensitizer CdS showed relatively high tendency to leach out hazardous Cd²⁺ ions under photo-degradation reaction conditions. In an attempt to solve out such difficulties, 2 was supported onto sand surface. The sand/TiO₂/CdS system, 3, was easier to recover but showed slightly lower catalytic activity compared to 2. On the other hand, the support failed to prevent leaching of Cd²⁺. This indicates limited future applicability of CdS-sensitized TiO₂ photo-catalyst systems, in solar-based water purification strategies, unless leaching out tendency is completely prevented.     

Performance analysis of multiple‐input multiple‐output relay networks based impulse radio ultra‐wideband

In this paper, we study the performance of time hopping pulse position modulation for impulse radio ultra‐wideband. We consider relay network applying decode‐and‐forward protocol. The channels between nodes adopt the IEEE 802.15.4a norms. The bit error rate performance is analyzed considering the effect of interference. Our results show significant improvement due to the diversity gain provided by the relay nodes. However, the performance is limited when multiple access interference (MAI) is present. To combat the MAI effect and further improve the detection reliability, we propose to use antenna selection at the relay. The relay receiver is assumed to be equipped with multiple antennas, and only the best antenna is selected. This is shown to improve the performance in the presence of MAI and improve the diversity gain.Copyright © 2013 John Wiley & Sons, Ltd.     

Tight lower bounds for certain parameterized NP-hard problems

Based on the framework of parameterized complexity theory, we derive tight lower bounds on the computational complexity for a number of well-known NP-hard problems. We start by proving a general result, namely that the parameterized weighted satisfiability problem on depth-t circuits cannot be solved in time n^o(k)m^O(1), where n is the circuit input length, m is the circuit size, and k is the parameter, unless the (t − 1)-st level W[t − 1] of the W-hierarchy collapses to FPT. By refining this technique, we prove that a group of parameterized NP-hard problems, including weighted sat, hitting set, set cover, and feature set, cannot be solved in time n^o(k)m^O(1), where n is the size of the universal set from which the k elements are to be selected and m is the instance size, unless the first level W[1] of the W-hierarchy collapses to FPT. We also prove that another group of parameterized problems which includes weighted q-sat (for any fixed q 2), clique, independent set, and dominating set, cannot be solved in time n^o(k) unless all search problems in the syntactic class SNP, introduced by Papadimitriou and Yannakakis, are solvable in subexponential time. Note that all these parameterized problems have trivial algorithms of running time either n^km^O(1) or O(n^k).     

Analytical reasoning task reveals limits of social learning in networks

Social learning—by observing and copying others—is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is its ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of laboratory-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an ‘unreflective copying bias’, which limits their social learning to the output, rather than the process, of their peers’ reasoning—even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behaviour through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning.     

A MULTTOBJECTTVE APPROACH TO RELIABILITY DEMONSTRATION TESTING

In this paper, we describe a new modeling approach for designing a reliability demonstration test (RDT). The approach, based upon the use of a multiattribute value function, has the advantage of allowing the explicit, and simultaneous, consideration of multiple performance measures (e.g., sample size, consumer's risk, and producer's risk) in the design process. A case study involving the application of the model to the design of the RDTs for a computer assembly plant is also described