Composite Evaluation of Replacing Small Generation Units with Large Ones in the Electricity Sector in China
This paper applies two methods to evaluate the economic effects of the policy of "replacing small units with large ones (RSWL)," one is Discounted Cash Flow (DCF) method which performs a technology economic analysis both from the financial and the economic perspectives, the other one is to use the Real Option theory to study the lagging investment problem of the big unit. Through an illustrative example, three alternatives of replacing 200 MW units with 600 MW units are compared. The sensitivity analysis is made to evaluate the impact of uncertain factors on the financial and economic indicators of the execution of RSWL. The environmental costs are also taken into account in the comparison and analysis. The proposed methods can aid the decision-making in the implementation of the policy of RSWL from a wider perspective and it can be used to evaluate the economic benefits and costs of the RSWL projects.

title: Externality Identification and Quantification of Transmission Construction Projects
abstract: This paper provides the evaluation method and model of the externality of the transmission projects, and identifies both negative and positive externalities, as well as makes quantitative and qualitative analysis of externality. In order to quantify the impact of transmission construction projects on the power flow distribution, power supply and demand, as well as the power price of the neighboring power grid, this paper operates the optimal power flow calculation on the Matlab platform through using the IEEE 30-Node Prototype System, and figures out the construction project's influence on the economic benefits of different power market participants. Based on the existing environmental evaluation study, this paper analyzes how the transmission construction project affects the natural resource and the environment and the daily life of the inhabitants. Taking into account the externality and quantifying the externality when evaluating the investment project can help the government and the investors to make the investment decision which is beneficial to the whole society.

title: Coordination Research on Key Parameters in Generation Competition Based on Dynamic Simulation
abstract: Power generation adequacy is critical for the reliability of electricity supply service, and therefore its investment draws much attention. This paper builds a dynamic simulation model to solve the setting of two key parameters, the energy price cap and the capacity price in the generation market, and applies this model to various cases to analyze the generation capacity development. Based on the simulation results, this paper analyzes the sensitivity of generation capacity to the key parameters. Furthermore, this paper proposes an evaluation index system for the simulation model, and discusses the correlation between the two key parameters, from the views of reliability and economy. The research shows that there might be potential unmarked misunderstandings in the setting of key parameters, and suggests that under a certain electricity bill for customers, parameter combination of low energy price cap and high capacity price should be made, in order to curb the fluctuation of generation capacity and maintain the system reliability.

title: Systematic benchmarking of microarray data feature extraction and classification
abstract: A combination of microarrays with classification methods is a promising approach to supporting clinical management decisions in oncology. The aim of this paper is to systematically benchmark the role of classification models. Each classification model is a combination of one feature extraction method and one classification method. We consider four feature extraction methods and five classification methods, from which 20 classification models can be derived. The feature extraction methods are t-statistics, non-parametric Wilcoxon statistics, ad hoc signal-to-noise statistics, and principal component analysis (PCA), and the classification methods are Fisher linear discriminant analysis (FLDA), the support vector machine (SVM), the k nearest-neighbour classifier (kNN), diagonal linear discriminant analysis (DLDA), and diagonal quadratic discriminant analysis (DQDA). Twenty randomizations of each of three binary cancer classification problems derived from publicly available datasets are examined. PCA plus FLDA is found to be the optimal classification model.

title: A Novel Load Control Strategy For TD-SCDMA Enhanced Uplink
abstract: In this paper, we propose a novel load control strategy for TD-SCDMA Enhanced Uplink, called as system-based load control strategy. We compare its performance with the cell-based load control strategy, which was widely accepted in TD-SCDMA release 4/5. It is concluded that system-based load control outperforms cell-based load control in the rise over thermal (RoT) control and the system throughput.

title: Increase of potential intellectual bandwidth in a scientific community through implementation of an end-user information system
abstract: Qureshi, et al. (2002) presented a case study where they used a framework, the intellectual bandwidth model to measure an organization's ability to create value. The model consists of two dimensions, information assimilation and collaboration. The IB model is a useful tool for managers because it enables them to plan solutions to complex business problems and to easily communicate these plans to key individuals. The model can also serve as a guide when making investment decisions. While it is important to increase an organization's intellectual bandwidth, it is equally important to assure that the resulting increase is employed to improve the organization's ability to innovate since, as it has been shown, innovation is the number one creator of organizational wealth (Baum et al., 2000). In this paper we discuss how intellectual bandwidth as proposed by Nunamaker et al. (2001) can be extended beyond the highest level of information assimilation identified in the model, automated sense-making, to ensure implementation of product innovations. To do this we propose adding two new information assimilation features, automated utilization and automated implementation. A real business example from the bioscience industry is presented in order to demonstrate how the IB model with extensions can be used. The study discusses an end-user information system, its current use and its potential to enhance an organization's value-creating capability.

title: The transient performance analysis of voice/data integrated networks
abstract: Quasi-birth-death (QBD) processes are used as performance models for voice/data integration schemes. It is assumed that voice and data packets of different bandwidths require different numbers of servers for service. Voice packets are lost when there are no available servers; data packets are queued in a buffer when there are not enough servers. A new approach is proposed to find the transient solutions of the QBD processes. The method is applied to a QBD model of a voice/data integration scheme to find time-dependent performance measures such as the expected number of data or voice packets in the system and the voice packet blocking probability.<<ETX>>

title: SPOT: A System for Detecting Projected Outliers From High-dimensional Data Streams
abstract: In this paper, we present a new technique, called stream projected ouliter detector (SPOT), to deal with outlier detection problem in high-dimensional data streams. SPOT is unique in a number of aspects. First, SPOT employs a novel window-based time model and decaying cell summaries to capture statistics from the data stream. Second, sparse subspace template (SST), a set of top sparse subspaces obtained by unsupervised and/or supervised learning processes, is constructed in SPOT to detect projected outliers effectively. Multi-Objective genetic algorithm (MOGA) is employed as an effective search method in unsupervised learning for finding outlying subspaces from training data. Finally, SST is able to carry out online self- evolution to cope with dynamics of data streams. This paper provides details on the motivation and technical challenges of detecting outliers from high-dimensional data streams, present an overview of SPOT, and give the plans for system demonstration of SPOT.