18873066
Extending Online Travel Agency with Adaptive Reservations
Current online ticket booking systems either do not allow customers to reserve a ticket with a locked price, or grant a fixed reservation timespan, typically 24 hours. The former often leads to false availability: when a customer decides to purchase a ticket after a few queries, she finds that either the ticket is no longer available or the price has hiked up. The latter, on the other hand, may result in unnecessary holdback: a customer cannot purchase a ticket because someone else is holding it, who then cancels the reservation after an excessively long period of time. False availability and holdback routinely lead to loss of revenues, credibility and above all, customers. To rectify these problems, this paper introduces a transaction model for e-ticket systems to support a reservation functionality: customers can reserve tickets with a locked price, for a timespan that is determined by the demands on the tickets, rather than being fixed for all kinds of the tickets. We propose a method for implementing the model, based on hypothetical queries and triggers. We also show how to adjust the reservation timespan w.r.t. demands. We experimentally verify that our model and methods effectively reduce both false availability and holdback rates. These yield a practical approach to improving not only e-ticket systems but also other e-commerce systems.
17285338
A reputation-chain trust model for the semantic Web
Trust plays a central role for efficient and secure interactions on the semantic Web. Nowadays, more and more research has focused on this topic. In this paper, we introduce RCSW, a reputation-chain trust model for the semantic Web. We illustrate the basic definitions and mechanisms of RCSW and present the algorithm to calculate trust ratings through the chain of the trust network. RCSW incorporates pairwise trust values and reliable factors of acquaintances and constructs an edge-weighted graph to calculate trust ratings. We also define classes of trust functions to allow users to individualize their trust calculation. Our proposed model can deal with trust management effectively and can quickly adapt to the changing environment.
12630564
Develop a Computational Trust Prototype for the Semantic Web
Nowadays, more and more research has focused on the trust management of the Semantic Web. Some mature technologies from many fields such as multiagent systems, social network analysis and artificial intelligence have been introduced to this field. However, some unique characteristics of the Semantic Web are more or less ignored. In this paper, we try to explore the semantic aspects of the trust management. We present DartTrust, a trust prototype for the semantic web in the application context of Traditional Chinese Medicine (TCM). We introduce RCSW - a Reputation-Chain trust model for the Semantic Web, which incorporates pairwise trust factor and reliable factor and constructs an edge-weighted graph to calculate trust ratings. We define a small trust ontology to illustrate the trust relationships. The trust ontology is described in OWL that can be understood and processed by machines. Therefore, DartTrust can provide reasoning functions and facilitate trust management with little human effort. As a demonstration of the prototype, we present its implementation on Traditional Chinese Medicine (TCM) at the end of this paper.
46276460
ACO Based QoS Routing Algorithm for Wireless Sensor Networks
In this paper, we proposed an approach for Quality of Service (QoS) routing algorithm of Wireless Sensor Networks (WSNs) based on Ant Colony Optimization (ACO). The special characteristics of WSNs need to reduce the computational complexity and energy consumption of the QoS routing algorithm especially. We note that ACO algorithm using collective intelligence of artificial ants as intelligent agents is very appropriate to solve the combinatorial optimization problems in a fully distributed way, so in this paper we use modified ACO approach to solve Delay Constraint Maximum Energy Residual Ratio (DCMERR) QoS routing problem of WSNs. The QoS routing solution proposed in this manuscript, which is named as ACO based QoS routing algorithm (ACO-QoSR), searches for the best paths, which are satisfied with the QoS requirements with intelligent artificial ants. To overcome the problem of limited energy in WSNs, there are some modifications to enhance ACO’s convergence rate. ACO-QoSR algorithm is the tradeoff between a certain guaranteed QoS requirements and acceptable computational complexity. The simulation results verify that ACO-QoSR algorithm can reduce the selected paths’ delay and improve the selected paths’ normalized energy residual ratio at the similar levels of routing overhead.
14869838
A Social Network-Based Trust Model for the Semantic Web
Trust is very essential to secure and high quality interactions on the Semantic Web. In this paper, we introduce a trust model, which incorporates pairwise trust ratings and reliable factors of acquaintances and constructs an edge-weighted graph to calculate trust values. We interpret trust in two dimensions to better deal with it. We apply the theory in social network field to calculate trust and simulate the trust relationships between humans. We also take advantage of formulas in probability and statistics to analyze the similarities between agents. The algorithm of the trust model aims to be simple, efficient and flexible.
38299104
A Computational Trust Model for Semantic Web Based on Bayesian Decision Theory
Enabling trust to ensure more effective and efficient agent interaction is at the heart of the Semantic Web vision. We propose a computational trust model based on Bayesian decision theory in this paper. Our trust model combines a variety of sources of information to assist users with making correct decision in choosing the appropriate providers according to their preferences that expressed by prior information and utility function, and takes three types of costs (operational, opportunity and service charges) into account during trust evaluating. Our approach gives trust a strict probabilistic interpretation and lays solid foundation for trust evaluating on the Semantic Web.
14636943
A 32-bit Decimal Floating-Point Logarithmic Converter
This paper presents a new design and implementation of a 32-bit decimal floating-point (DFP) logarithmic converter based on the digit-recurrence algorithm. The converter can calculate accurate logarithms of 32-bit DFP numbers which are defined in the IEEE 754-2008 standard. Redundant digit e1 is obtained by look-up table in the first iteration and the rest redundant digits ej are selected by rounding the scaled remainder during the succeeding iterations. The sequential architecture of the proposed 32-bit DFP logarithmic converter is implemented on Xilinx Virtex-II Pro P30 FPGA device and then synthesized with TMSC 0.18-um standard cell library. The implementation results indicate that the maximum frequency of the proposed architecture is 47.7 MHz in FPGA and 107.9 MHz in TMSC 0.18-um technology. The faithful 32-bit DFP logarithm results can be obtained in 18 cycles.
15507709
Data-Layout Optimization Using Reuse Distance Distribution
As the ever-increasing gap between the speed of processor and the speed of memory has become the cause of one of primary bottlenecks of computer systems, modern architecture systems use cache to solve this problem, whose utility heavily depends on program data locality. This paper introduces a platform independent data-layout optimization framework to improve program data locality. This framework uses a variable relation model based on variables’ reuse distance distribution to quantitate the relation of variables and accordingly assigns variables which are often accessed together in one group. At the same time this framework introduces a dynamic array regrouping method to group dynamic arrays assigned in a group. Experiments show that this data-layout optimization framework can effectively improve program data locality and program performance.
12263549
Tree-guided Bayesian inference of population structures
MOTIVATION
Inferring population structures using genetic data sampled from a group of individuals is a challenging task. Many methods either consider a fixed population number or ignore the correlation between populations. As a result, they can lose sensitivity and specificity in detecting subtle stratifications. In addition, when a large number of genetic markers are used, many existing algorithms perform rather inefficiently.


RESULT
We propose a new Bayesian method to infer population structures using multiple unlinked single nucleotide polymorphisms (SNPs). Our approach explicitly considers the population correlation through a tree hierarchy, and treat the population number as a random variable. Using both simulated and real datasets of worldwide samples, we demonstrate that an incorporated tree can consistently improve the power in detecting subtle population stratifications. A tree-based model often involves a large number of unknown parameters, and the corresponding estimation procedure can be highly inefficient. We further implement a partition method to analytically integrate out all nuisance parameters in the tree. As a result, our method can analyze large SNP datasets with significantly improved convergence rate.


AVAILABILITY
http://www.stat.psu.edu/~yuzhang/tips.tar.
14517815
Implementing Atomic Section by Using Hybrid Concurrent Control
Atomic section is an important language feather in multi- thread synchronizing. So far, it can only be implemented by using pessimistic or optimistic concurrent control singly. This paper introduces a flexible hybrid concurrent control system which could harmonize the two modes of concurrent control. Accordingly, a new atomic section is proposed as language level support to open an interface for both manual and compiler-assisted optimization.
20797286
A Generic Validation Framework for Wideband MIMO Channel Models
In this paper, a generic framework for validating wideband MIMO channel models based on channel measurement results is proposed. The framework is formulated as a series of continuous functions (metrics) and a definition of distance of continuous function space (degree of approximation). The metrics characterize the MIMO channel from different perspectives, and the distance provides a quantitative measure of the degree of approximation for the specified model. Several fundamental metrics which reflect the spatial multiplexing gain, diversity capability, time and frequency variability, are derived for exploring the frequency-selective fading property. Based on an extensive measurement campaign at 5.25 GHz, the propagation channel is reconstructed by a WINNER-like model. The metrics are calculated from both the model generated channel realizations and the measured impulse response as a demonstration. The proposed framework can be applied to compare different channel models and to evaluate the simplified version of channel models.