9464715
Assisting seller pricing strategy selection for electronic auctions
This research examines sellers' pricing strategy oriented to bidders' risk preferences, within the context of an electronic auction. A business model is then proposed to predict the probability of potential bidders' risk preference, which sellers can consider to set pricing strategy to maximize their profits. A tailored intelligent auction registry engine is constructed based upon an initial version of our business model. Because the extensible markup language (XML)-based simple object access protocol (SOAP) is utilized to support interactions with other resources, our engine is decoupled from the underlying technology choices; therefore, it can be deployed to different platforms.
5737792
Generators Bidding Behavior in the NYISO Day-Ahead Wholesale Electricity Market
Statistical and econometric modeling is used to analyze the dynamics of generators' bidding behavior and resulting market prices in the NYISO day-ahead market during the summer of 2001 at three levels. First, at the generator level, generators' offered capacity is modeled by a two-stage sample selection process. The grouping choices of generators are estimated in the first stage. In the second stage, generators' offered capacity is estimated conditional on their grouping choices. Second, at the group level, we estimate the offer curves of each group. Third, at the total supply level, the aggregate supply curve is simulated by aggregating the offer curves of bidding groups. The estimated market prices based on the simulated supply curve can replicate most volatility of actual market prices. We find that demand conditions affect generators' bidding behavior and thus market prices significantly by applying our model under different demand assumptions
5773205
Auction-Based Pricing Model for Web Service Providers
Applying auctions to Web services selection and invocation calls for examination due to the unique features of Web services, such as interoperable machine-to machine interactions and re-enterable bargaining services. In this paper, we propose a formal model for Web services-based auctions. Examining a one sided sealed auction type, we prove mathematically that service requestorsâ€™ risk preferences could lead to different pricing strategies for service providers towards higher profit. We argue that Service Level Agreement (SLA) documents can be used to analyze service requestorsâ€™ preferences. On top of WS Agreement, we propose a basic service requestor risk preference elicitation algorithm, as well as a historical data-based service requestor risk preference prediction model. Guidelines are provided to iteratively approach the learning rate of the proposed risk preference prediction model. The methods and techniques presented in this paper can be reused to investigate and examine more facades of services-oriented auctions towards establishing a new research realm on comprehensive services-oriented auctions.
445053
Prediction of Helix, Strand Segments from Primary Protein Sequences by a Set of Neural Networks
In prediction of secondary structure of proteins there are always some suspected segments. These suspected segments confuse people and lower the accuracy of prediction methods. To deal with this problem, a set of neural networks (NNs) are built based on helix, strand and coil segments selected from PDB. The test performance of these NNs on training data is perfect without surprise. However the prediction on test data is not good enough because the training data are lake of great representativeness. The results support the fact that closer neighbor vectors have the similar outputs of NNs. One can improve representativeness of training data without enlarging data scale as long as select less data from dense region and more from sparse region on condition that distribution of sample data has been known.
7396264
Pseudo-Randomness of Discrete-Log Sequences from Elliptic Curves
We investigate an upper bound on the discrepancy and a lower bound on the linear complexity of a class of sequences, derived from elliptic curves by using discrete logarithm in this paper. The results indicate that these sequences may have `nice' pseudo-random properties. The important tool in the proof is certain character sums estimate along elliptic curves. In addition, we apply linear recurrence relation over elliptic curves to output binary sequences with very interesting pseudo-random behavior.
8279850
Analysis and Simulation Protocols Based on Slotted ALOHA for Plastic Optical Fiber Network
In this paper a novel multipriority reservation protocols for plastic optical fiber network is proposed. In conventional OCDMA system only allows finite units to transmit and access simultaneously according to the number of channels which be restricted by BER. To resolve this problem, a novel protocol based on slotted ALOHA is proposed in this paper. By using the reservation scheme and a distributed arbitration algorithm, channel collision and destination conflict can be avoided. The protocol can efficiently support the transmission of multimedia messages that require the different time-delay. The network throughput and average delay has been investigated by numerical analysis and simulation experiments. It is showed that the multipriority reservation protocol in this POF network is valid and efficient.
10909471
On approximation algorithms of k-connected m-dominating sets in disk graphs
Connected Dominating Set (CDS) has been proposed as the virtual backbone to alleviate the broadcasting storm in wireless ad hoc networks. Most recent research has extensively focused on the construction of 1-Connected 1-Dominating Set (1-CDS) in homogeneous networks. However, the nodes in the CDS need to carry other node's traffic and nodes in wireless networks are subject to failure. Therefore, it is desirable to construct a fault tolerant CDS. In this paper, we study a general fault tolerant CDS problem, called k-Connected m-Dominating Set (k-m-CDS), in heterogeneous networks. We first present two approximation algorithms for 1-m-CDS and k-k-CDS problems. Using disk graphs to model heterogeneous networks, we show that our algorithms have a constant approximation ratio. Based on these two algorithms, we further develop a general algorithm for k-m-CDS. We also provide an interesting analysis for a special case of k-m-CDS, where k=m+1.
27036823
A new method in multi-issue negotiation
In this paper we describe a mechanism for automated negotiation in which artificial agents can deal with a multiissue negotiation in a one-to-many way based on some strategies. The negotiation process are governed dynamically by some strategies that emphasize on the diverse processing methods under the considering of different commodity attributes, including dynamic delayed evaluation and response to the received offers, generation of offer group with the same utility. Our analysis shows that the mechanism ensures that bargaining agents could reach a better agreement automatically. We also implement a prototype system to verify the advantages of our mechanism