A Holistic Review of Public-Private Partnership Literature Published between 2008 and 2018

Adopting a holistic approach in the review of the public-private partnership (PPP) literature published since 2008 by incorporating scientometric analysis and further systematic analysis, this study aims to provide the big picture of the state-of-the-art research in PPP by addressing major issues and suggesting research trends in PPP. Following a three-step research methodology, this study started from a bibliometric analysis with science mapping to provide the state-of-the-art information on PPP research keywords, scholars, journal articles, institutions, and countries. A further systematic review was also conducted to identify future research directions of PPP in project management. The review of the existing literature in PPP revealed that there had been insufficient systematic approach in summarizing the research topics and proposing new research trends in PPP-related project management. It was further indicated that sustainability and innovation in PPP could be further studied, such as integrating building information modeling with PPP. Factors related to barriers in PPP implementation would continue growing. Future research directions in PPP were also proposed following the systematic review, for example, comparative studies of PPP practice between developing and developed countries. The current study provides a comprehensive approach by integrating bibliometric analysis, science mapping, and qualitative analysis in the latest PPP research. It reveals the contemporary research themes in PPP and provides directions for near-future directions of PPP research in project management

Searching for Ground Truth: a stepping stone in automating genre classification

This paper examines genre classification of documents and its role in enabling the effective automated management of digital documents by digital libraries and other repositories. We have previously presented genre classification as a valuable step toward achieving automated extraction of descriptive metadata for digital material. Here, we present results from experiments using human labellers, conducted to assist in genre characterisation and the prediction of obstacles which need to be overcome by an automated system, and to contribute to the process of creating a solid testbed corpus for extending automated genre classification and testing metadata extraction tools across genres. We also describe the performance of two classifiers based on image and stylistic modeling features in labelling the data resulting from the agreement of three human labellers across fifteen genre classes.

Possible DDˉD\bar{D} and BBˉB\bar{B} Molecular states in a chiral quark model

We perform a systematic study of the bound state problem of $D\bar{D}$ and $B\bar{B}$ systems by using effective interaction in our chiral quark model. Our results show that both the interactions of $D\bar{D}$ and $B\bar{B}$ states are attractive, which consequently result in $I^G(J^{PC})=0^+(0^{++})$ $D\bar{D}$ and $B\bar{B}$ bound states.Comment: arXiv admin note: substantial text overlap with arXiv:1204.395

Nearly constant dielectric loss behavior in poly(3-hydroxybutyrate-co-3-hydroxyvalerate) biodegradable polyester

2008-2009 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Immunization for complex network based on the effective degree of vertex

The basic idea of many effective immunization strategies is first to rank the importance of vertices according to the degrees of vertices and then remove the vertices from highest importance to lowest until the network becomes disconnected. Here we define the effective degrees of vertex, i.e., the number of its connections linking to un-immunized nodes in current network during the immunization procedure, to rank the importance of vertex, and modify these strategies by using the effective degrees of vertices. Simulations on both the scale-free network models with various degree correlations and two real networks have revealed that the immunization strategies based on the effective degrees are often more effective than those based on the degrees in the initial network.Comment: 16 pages, 5 figure

Enhancing the representation of subgrid land surface characteristics in land surface models

Land surface heterogeneity has long been recognized as important to represent in the land surface models. In most existing land surface models, the spatial variability of surface cover is represented as subgrid composition of multiple surface cover types, although subgrid topography also has major controls on surface processes. In this study, we developed a new subgrid classification method (SGC) that accounts for variability of both topography and vegetation cover. Each model grid cell was represented with a variable number of elevation classes and each elevation class was further described by a variable number of vegetation types optimized for each model grid given a predetermined total number of land response units (LRUs). The subgrid structure of the Community Land Model (CLM) was used to illustrate the newly developed method in this study. Although the new method increases the computational burden in the model simulation compared to the CLM subgrid vegetation representation, it greatly reduced the variations of elevation within each subgrid class and is able to explain at least 80% of the total subgrid plant functional types (PFTs). The new method was also evaluated against two other subgrid methods (SGC1 and SGC2) that assigned fixed numbers of elevation and vegetation classes for each model grid (SGC1: <i>M</i> elevation bands–<i>N</i> PFTs method; SGC2: <i>N</i> PFTs–<i>M</i> elevation bands method). Implemented at five model resolutions (0.1°, 0.25°, 0.5°, 1.0°and 2.0°) with three maximum-allowed total number of LRUs (i.e., <i>N</i>_LRU of 24, 18 and 12) over North America (NA), the new method yielded more computationally efficient subgrid representation compared to SGC1 and SGC2, particularly at coarser model resolutions and moderate computational intensity (<i>N</i>_LRU = 18). It also explained the most PFTs and elevation variability that is more homogeneously distributed spatially. The SGC method will be implemented in CLM over the NA continent to assess its impacts on simulating land surface processes

Interpreting forest and grassland biome productivity utilizing nested scales of image resolution and biogeographical analysis

Several hardware, software, and data collection problems encountered were conquered. The Geographic Information System (GIS) data from other systems were converted to ERDAS format for incorporation with the image data. Statistical analysis of the relationship between spectral values and productivity is being pursued. Several project sites, including Jackson, Pope, Boulder, Smokies, and Huntington Forest are evolving as the most intensively studied areas, primarily due to availability of data and time. Progress with data acquisition and quality checking, more details on experimental sites, and brief summarizations of research results and future plans are discussed. Material on personnel, collaborators, facilities, site background, and meetings and publications of the investigators are included