A grid-based node split algorithm for managing current location data of moving objects

There is rapidly increasing interest in Location Based Service (LBS) which utilizes location data of moving objects. To efficiently manage the huge amounts of location data in LBS, the GALIS (Gracefully Aging Location Information System) architecture, a cluster-based distributed computing architecture, is proposed. The GALIS using the non-uniform 2-level grid algorithm performs load balancing and indexing for nodes. However, the non-uniform 2-level grid algorithm has a problem creating unnecessary nodes when moving objects are crowded in a certain region. Therefore, a new node split algorithm, which is more efficient for various distribution of moving objects, is proposed in this paper. Because the algorithm proposed in this paper considers spatial distribution for the current location of moving objects, it can perform efficient load balancing without creating unnecessary nodes even when moving objects are congested in a certain region. Besides, the various data distribution configuration for moving objects has been experimented by implementing node split simulators and it’s been verified that the proposed algorithm can split nodes more efficiently than the existing algorithm.

Neuro‐filters used to enhance the image quality of video displays

Abstract— Digital images can be affected by external factors. There are many types of noise which affect digital images. Image filtration is a basic method used to suppress such hindrances. The disadvantage of most filtration methods and hardware filters created on their behalf is their inability to react to changes in the input signal. The structure of the filters used for image processing is similar to the structure of a bi‐dimensional neural‐network matrix. Investigations have shown that a system with serial‐parallel filters of any degree of complexity can be created on the basis of the neural‐network matrices. Each neural‐network matrix layer acts as a separate neuro‐filter which can be trained and adapted to changes in the characteristics of the images. The neural‐network matrices allow for the creation of various types of linear and nonlinear filters, as well as combinations on the basis of a uniform structure. It allows for the design of a universal hardware neuro‐filter structure that can perform as different types of filters by means of loading the connectors weight. In our paper, we consider the realization of neuro‐filters based on a neural‐network matrix, which allows the processing of both static and moving images and increases the image sharpness, suppresses the noise, and detects movable objects in the processed image.     

Survey on model-based manipulation planning of deformable objects

A systematic overview on the subject of model-based manipulation planning of deformable objects is presented. Existing modeling techniques of volumetric, planar and linear deformable objects are described, emphasizing the different types of deformation. Planning strategies are categorized according to the type of manipulation goal: path planning, folding/unfolding, topology modifications and assembly. Most current contributions fit naturally into these categories, and thus the presented algorithms constitute an adequate basis for future developments.     

Timed Petri Nets: Probabilistic Selection Of Data Dependent Paths

In this paper, the probabilistic selection of data dependent paths, in a time-augmented Petri net model, is introduced and tackled. Real-time systems are classified according to their timing requirements into soft real-time systems and hard real-time systems. It is shown that the type of real-time system to be modeled greatly effects the timing considerations that ensure proper performance. Expressions for the conditions needed to guarantee a correct functioning are derived. Some illustrative case studies are presented.     

A theoretical 2D image model for locating 3D targets

To construct a water quality monitoring system, challenging issues need to be addressed regarding the acquisition of target information (e.g. 3D location and occlusion) as well as the behavioural analysis of aquatic organisms. This paper presents a novel 3D information acquisition and location method, by means of an information acquisition platform consisting of a monitoring terminal, frame grabbers, a single camera and a single mirror. Using this platform, we propose a theoretical 2D image model for locating 3D targets and then validate it using data obtained from both real and artificial fish. The proposed model is based on the principles of light refraction, plane mirror imaging, underwater objects and camera imaging as well as the technologies of digital to analog conversion and object segmentation. In contrast with existing methods, our method can accurately reflect 3D information of aquatic organisms, thus providing critical technical support for the development of water quality monitoring systems in the future.     

Graceful Object-Based Performance Evolution

Object-based design and development are thought to facilitate graceful evolution of functionality, and thus enhance the reusability of software components. They can also facilitate graceful performance evolution. The performance of a layered object-based component can be made tunable to meet changing needs by permitting clients to ‘plug in’ appropriate implementations for its constituent components through generic parameters. If the components and their constituents are carefully designed, then performance tuning is possible without direct modification to the internal details of the participating components, thus significantly lowering the cost for performance evolution. The contribution of this paper is to software practice. It explains how software engineers can build performance-tunable components using C++ templates. It includes empirical results confirming that tuning produces expected performance improvements with minimal code change. The results are especially significant because they are scalable to arbitrarily large and heavily layered software components and subsystems. © 1997 by John Wiley & Sons, Ltd.     

Designing and implementing multi-user applications: A case study

We have developed a new multi-user application that integrates and extends the concepts in a variety of current multi-user applications. It allows multiple users to store, retrieve and browse through information, communicate information both synchronously and asynchronously, create ‘pipes’ of consistent, editable and persistent views, and interactively specify handlers for events. It has been implemented using the experimental technologies of distributed objects and multi-user editor generation. Our work on this application suggests a new and practical model for designing and implementing multi-user applications. In this paper, we describe the user interface and implementation of the application, give the rationale for our design choices, describe our experience with the tools and techniques used in the implementation, and present conclusions and directions for future work.     

CONTEXTUAL LANGUAGE MODELS FOR RANKING ANSWERS TO NATURAL LANGUAGE DEFINITION QUESTIONS

Question–answering systems make good use of knowledge bases (KBs, e.g., Wikipedia) for responding to definition queries. Typically, systems extract relevant facts from articles regarding the question across KBs, and then they are projected into the candidate answers. However, studies have shown that the performance of this kind of method suddenly drops, whenever KBs supply narrow coverage. This work describes a new approach to deal with this problem by constructing context models for scoring candidate answers, which are, more precisely, statistical n‐gram language models inferred from lexicalized dependency paths extracted from Wikipedia abstracts. Unlike state‐of‐the‐art approaches, context models are created by capturing the semantics of candidate answers (e.g., “novel,”“singer,”“coach,” and “city”). This work is extended by investigating the impact on context models of extra linguistic knowledge such as part‐of‐speech tagging and named‐entity recognition. Results showed the effectiveness of context models as n‐gram lexicalized dependency paths and promising context indicators for the presence of definitions in natural language texts.     

基于条件效果的对象动态可变图规划

主要研究了基于条件效果的对象动态可变的规划问题．提出了相关元件、无关元件、创建／删除对象元件和普通元件等概念，把带有条件效果的动作和不带有条件效果的动作都元件化，并采用了对象命题化的思想．给出了新的基于目标驱动的规划图扩展算法和前向搜索有效规划算法，并给出了相应的后向传播互斥的定义，使得规划图的规模比较小，减少了搜索空间，大大提高了求解有效规划的效率．由于算法中的动作创建的效果是依赖于上下文的描述，这更加符合现实需要，使处理的问题更接近于真实的世界状态，因而此算法比以往的算法应用性更强，更具有现实意义．     

Building Agile Systems with Mobile Code

Mobile code has been championed as a solution to a plethora of software problems. This paper describes investigative work undertaken in order to evaluate the mobile code abstractions of Mobile Agents and Mobile Objects, and to understand the implications of using these abstractions to build distributed systems.We describe two systems built to support the Sales Order Process of a distributed manufacturing enterprise, using IBM's Aglets Software Development Kit. The Sales Order Process model and the requirements for agility used as the basis for these implementations are derived from data collected in an industrial case study.Both systems are evaluated using the Goal/Question/Metric methodology. Two new metrics for Semantic Alignment and Change Capability are presented and used to evaluate each system with respect to the degree of system agility supported. The systems are evaluated through a set of scenarios generated during the case study in an attempt to see if they support system integration and agility in the manufacturing domain. Further we examine the implications of using a mobile code abstraction when compared with the abstraction offered by traditional distribution technology.The work described provides evidence that both Mobile Agent and Mobile Object systems have inherent properties that can be used to build agile distributed systems. Further, Mobile Agents with their additional autonomy provide marginally greater support.