A generic and efficient framework for flash-aware spatial indexing

Spatial indexing on flash-based Solid State Drives (SSDs) has become a core aspect in spatial database applications, and has been carried out by flash-aware spatial indices. Although there are some flash-aware spatial indices proposed in the literature, they do not exploit all the benefits of SSDs, leading to loss of efficiency and durability. In this article, we propose eFIND, a new generic and efficient framework for flash-aware spatial indexing. eFIND takes into account the intrinsic characteristics of SSDs by employing (i) a write buffer to avoid expensive random writes, (ii) a flushing algorithm that smartly picks modifications to be flushed in batch to the SSD, (iii) a read buffer to decrease the overhead of random reads, (iv) a temporal control to avoid interleaved reads and writes, and (v) a log-structured approach to provide data durability. Performance tests showed the efficiency of eFIND. Compared to the state of the art, eFIND improved the construction of spatial indices from 43% to 77%, and the spatial query processing from 4% to 23%.     

语义万维网中基于Agent的智能检索框架

语义万维网是目前国际万维网联盟（world wide web consortium,W3C）为了解决因Web上的数据缺少语义信息而难以实现自动化处理的问题所开展的研究项目,其目的是为了对Web上发布的信息实现智能推理和自动化处理。Agent作为一种智能化主体,非常适合语义万维网环境下的各种应用。在语义万维网和智能Agent研究的基础上,综合信息检索、知识表示、Ontology建模等多方面技术,提出并实现了一个基于Ontology实现语义信息检索的多Agent系统框架,该系统包括信息收集、存储、查询和推理4个主要部分。     

A path-based approach for web page retrieval

Use of links to enhance page ranking has been widely studied. The underlying assumption is that links convey recommendations. Although this technique has been used successfully in global web search, it produces poor results for website search, because the majority of the links in a website are used to organize information and convey no recommendations. By distinguishing these two kinds of links, respectively for recommendation and information organization, this paper describes a path-based method for web page ranking. We define the Hierarchical Navigation Path (HNP) as a new resource for improving web search. HNP is composed of multi-step navigation information in visitors’ website browsing. It provides indications of the content of the destination page. We first classify the links inside a website. Then, the links for web page organization are exploited to construct the HNPs for each page. Finally, the PathRank algorithm is described for web page retrieval. The experiments show that our approach results in significant improvements over existing solutions.     

CISS: An efficient object clustering framework for DHT-based peer-to-peer applications

In most DHT-based peer-to-peer systems, objects are totally declustered since such systems use a hash function to distribute objects evenly. However, such an object de-clustering can result in significant inefficiencies in advanced access operations such as multi-dimensional range queries, continuous updates, etc, which are common in many emerging peer-to-peer applications. In this paper, we propose CISS (Cooperative Information Sharing System), a framework that supports efficient object clustering for DHT-based peer-to-peer applications. CISS uses a Locality Preserving Function (LPF) instead of a hash function, thereby achieving a high level of clustering without requiring any changes to existing DHT implementations. To maximize the benefit of object clustering, CISS provides efficient routing protocols for multi-dimensional range queries and continuous updates. Furthermore, our cluster-preserving load balancing schemes distribute loads without hotspots while preserving the object clustering property. We demonstrate the performance benefits of CISS through extensive simulation.     

A unified framework for multimodal retrieval

In this paper, a unified framework for multimodal content retrieval is presented. The proposed framework supports retrieval of rich media objects as unified sets of different modalities (image, audio, 3D, video and text) by efficiently combining all monomodal heterogeneous similarities to a global one according to an automatic weighting scheme. Then, a multimodal space is constructed to capture the semantic correlations among multiple modalities. In contrast to existing techniques, the proposed method is also able to handle external multimodal queries, by embedding them to the already constructed multimodal space, following a space mapping procedure of a submanifold analysis. In our experiments with five real multimodal datasets, we show the superiority of the proposed approach against competitive methods.     

A web services framework for distributed model management

Distributed model management aims to support the wide-spread sharing and usage of decision support models. Web services is a promising technology for supporting distributed model management activities such as model creation and delivery, model composition, model execution and model maintenance to fulfill dynamic decision-support and problem solving requests. We propose a web services based framework for model management (called MM-WS) to support various activities of the model management life cycle. The framework is based on the recently proposed Integrated Service Planning and Execution (ISP & E) approach for web services integration. We discuss encoding of domain knowledge (as individual models) and utilize the MM-WS framework to interleave synthesis of composite models with their execution. A prototypical implementation with an example is used to illustrate the utility of the framework to enable distributed model management and knowledge integration. Benefits and issues of using the framework to support model-based decision-making in organizational contexts are outlined.

CACHE RP : A novel dynamic cache size tuning model working with relative object popularity for fast web information retrieval

The CACHE_RPframework leverages the relative object popularity as the sole parameter for dynamic cache size tuning. In the process it consistently maintains the prescribed cache hit ratio on the fly by deriving the popularity ratio from the current statistics. As a result the accuracy of the statistical CACHE_RPoperation is independent of changes in the Internet traffic pattern that may switch suddenly. The contribution by the novel CACHE_RPframework is that by adaptively maintaining the given hit ratio it effectively reduces the end-to-end information retrieval roundtrip time (RTT) and frees more bandwidth for sharing. This bandwidth would otherwise be consumed in transferring large amounts of data from remote data sources to the proxy server before it is given to the client or requestor.     

A novel optimization framework for salient object detection

Visual saliency aims to locate the noticeable regions or objects in an image. In this paper, a coarse-to-fine measure is developed to model visual saliency. In the proposed approach, we firstly use the contrast and center bias to generate an initial prior map. Then, we weight the initial prior map with boundary contrast to obtain the coarse saliency map. Finally, a novel optimization framework that combines the coarse saliency map, the boundary contrast and the smoothness prior is introduced with the intention of refining the map. Experiments on three public datasets demonstrate the effectiveness of the proposed method.     

Cyberbroker: A lightweight web object collector

Centralized heavyweight collectors have been used to collect text-based web objects for building search engines. However, these collectors do not meet the need of collecting big web objects such as images and videos. We propose a lightweight mobile on-call object collector for the world wide web. Using this approach, we can deploy a collector easily on the site being indexed. We present a prototype system consisting of mobile Java collectors and search engines for collecting HTML/image objects. We provide analysis to find a lower bound in terms of total data transfer time required. This idealized scenario is complemented with another model based on implementation of the HTTP over TCP. The lower bound and the upper bound of the gains accrued are then validated using experiments. This revised version was published online in August 2006 with corrections to the Cover Date.     

A framework for object migration in object-oriented databases

This article presents a framework developed for accomodating various object migrations in ‘statically-typed’ object databases. Requirements for supporting object migrations are stipulated, and a conceptual model for describing and facilitating different kinds of migrations is described. Associated issues of controlling such migrations are then addressed, along with an initial investigation on the interence of implied migration paths and the completeness of migration operators. Some guidelines are then given to help users conduct migrations more effectively. An implementation prototype on top of an object-oriented database system was built, which embodies full support of all migration types specified in the migration model.     

A general shape context framework for object identification

A general shape context framework is proposed for object/image retrieval in occluded and cluttered environment with hundreds of models as the potential matches of an input. The approach is general since it does not require separation of input objects from complex background. It works by first extracting consistent and structurally unique local neighborhood information from inputs or models, and then voting on the optimal matches. Its performance degrades gracefully with respect to the amount of structural information that is being occluded or lost. The local neighborhood information applicable to the system can be shape, color, texture feature, etc. Currently, we employ shape information only. The mechanism of voting is based on a novel hyper cube based indexing structure, and driven by dynamic programming. The proposed concepts have been tested on database with thousands of images. Very encouraging results have been obtained.     

A B-spline based framework for volumetric object modeling

With the recent development of Iso-geometric Analysis (IGA) (Cottrell et al., 2009) and advanced manufacturing technologies employing heterogeneous materials, such as additive manufacturing (AM) of functionally graded material, there is a growing emerging need for a full volumetric representation of 3D objects, that prescribes the interior of the object in addition to its boundaries. In this paper, we propose a volumetric representation (V-rep) for geometric modeling that is based on trimmed B-spline trivariates and introduce its supporting volumetric modeling framework. The framework includes various volumetric model (V-model) construction methods from basic non-singular volumetric primitives to high level constructors, as well as Boolean operations’ support for V-models. A V-model is decomposed into and defined by a complex of volumetric cells (V-cells), each of which can also represent a variety of additional varying fields over it, and hence over the entire V-model. With these capabilities, the proposed framework is able of supporting volumetric IGA needs as well as represent and manage heterogeneous materials for AM. Further, this framework is also a seamless extension to existing boundary representations (B-reps) common in all contemporary geometric modeling systems, and allows a simple migration of existing B-rep data, tools and algorithms. Examples of volumetric models constructed using the proposed framework are presented.     

A genetic programming framework for content-based image retrieval

The effectiveness of content-based image retrieval (CBIR) systems can be improved by combining image features or by weighting image similarities, as computed from multiple feature vectors. However, feature combination do not make sense always and the combined similarity function can be more complex than weight-based functions to better satisfy the users’ expectations. We address this problem by presenting a Genetic Programming framework to the design of combined similarity functions. Our method allows nonlinear combination of image similarities and is validated through several experiments, where the images are retrieved based on the shape of their objects. Experimental results demonstrate that the GP framework is suitable for the design of effective combinations functions.