274260
Preserving operation effects relation in group editors
Consistency maintenance is a critical and challenging issue in many interactive groupware applications that can be modeled as group editors. This paper addresses two open consistency problems: divergence and operation effects relation violation. While the former has been partly solved, the latter has never been addressed in any published work. We propose a novel approach to solving both problems in the same framework. Particularly it preserves the effects relation of concurrent operations so that convergence is achieved automatically. Our work provides a new perspective into group editors and operational transformation algorithms.
17885452
Commutativity-based concurrency control in groupware
Commutativity of operations is often exploited in concurrent systems to attain high levels of concurrency. A commutativity-based concurrency control method, called operational transformation (OT), has been actively researched in groupware over the past 15 years. However, much progress can still be made on more practicable approaches to developing and proving OT algorithms. Several constraints have been proposed previously but they are generally difficult to follow and verify in practice. This paper proposes an alternative approach to address this problem. A new consistency model is defined which greatly simplifies the design and proof of OT algorithms
7717414
A time interval based consistency control algorithm for interactive groupware applications
Traditional concurrency control methods such as locking and serialization are not suitable for distributed interactive applications that demand fast local response. Operational transformation (OT) is the standard solution to concurrency control and consistency maintenance in group editors, an important class of interactive groupware applications. It generally trades consistency for local responsiveness, because human users can often tolerate temporary inconsistencies but do not like their interactions be lost or nondeterministically blocked. This paper presents a time interval based operational transformation algorithm (TIBOT) that overcomes the various limitations of previous related work. Our approach guarantees content convergence and is significantly more simple and efficient than existing approaches. This is achieved in a pure replicated architecture by using a linear clock and by posing some constraints on communication that are reasonable for the application domain.
14672206
Using marker-based deformable models for deriving anatomical models from medical image databases
The outcome of the application of a deformable model is dependent on its initialization and parameter settings. This is an obstacle to robust automatic segmentation. An approach to reducing the dependences is proposed in this paper based on geodesic topographic distance transforms from two manually or automatically placed markers. This is a novel method that uses object and background differentiation in deformable models via watershed theories. The implementation is based on efficient numerical methods. Experiments have shown that it is a highly promising approach. This approach has been applied to the determination of tissue characteristics in early childhood using a CT database of neonates. We believe that by relaxing dependences on the initialization and parameters this approach will enable a degree of automation needed for segmentation-based construction of organ models from large image databases, particularly when the markers can be determined automatically on the basis of a priori knowledge
7219842
Accurate Curvilinear Modeling for Precise Measurements of Tubular Structures
Accurate curvilinear models of tubular structures are essential for the precise measurements and description of those structures. Two major obstacles to obtaining an accurate curvilinear model from a three-dimensional (3D) image are tortuosity of the tubular structure and interferences from such sources as foreign entities in the neighborhood, pathological deformation and artifacts. Using existing algorithms, the tortuosity and interferences can give rise to models that tend to significantly distort subsequent length and angle measurements. In this paper, we describe a novel approach that overcomes those obstacles by combining a knowledge-embedding model with a front propagation method. We then demonstrate the effectiveness of our method through its potential applications in path planning and measurement for minimally invasive diagnosis and treatment purposes.
2700551
Combining Front Propagation with Shape Knowledge for Accurate Curvilinear Modelling
In this paper, we propose an approach to accurately modelling tubular, anatomical structures as curvilinear entities. Current optimal path and centerline extraction techniques are either prone to introducing spurious tortuosity, or unable to consistently avoid taking shortcuts at high curvature positions. These problems not only affect spatial appreciation of the structure but may also significantly impact the accuracy of length, angle and tortuosity measurements. Our approach overcomes the above deficiencies through the combination of a front propagation method and a model in which a priori shape knowledge is embedded. This approach is designed to be used in endovascular and neurological surgical planning. The efficacy of our method is demonstrated using synthetic and clinical data.
205481363
A new sufficient condition for Hamiltonicity of graphs
Rahman and Kaykobad proved the following theorem on Hamiltonian paths in graphs. Let G be a connected graph with n vertices. If d(u)+d(v)+δ(u, v) ≥ n+1 for each pair of distinct non-adjacent vertices u and v in G, where δ(u, v) is the length of a shortest path between u and v in G, then G has a Hamiltonian path. It is shown that except for two families of graphs a graph is Hamiltonian if it satisfies the condition in Rahman and Kaykobad's theorem. The result obtained in this note is also an answer for a question posed by Rahman and Kaykobad.
9514355
Integration of Multi-Source Spatial Information for Coastal Management and Decision Making
This paper presents the second-year outcomes of our Digital Government project "Digitalization of Coastal Management and Decision Making Supported by Multi-Dimensional Geospatial Information and Analysis". One of the primary objectives of the second year is to develop and integrate multiple spaceborne, airborne, and in-situ remotely sensed measurements, spatio-temporal databases, coastal hydrological modeling, and geospatial information analysis for coastal management and decision making. The developed coastal management and decision-making system includes applications for coastal mapping and change detection, water surface modeling and analysis, on-site coastal management and decision-making, and web-based spatial data manipulation. Studies have also been conducted on uncertainties in the used coastal spatial data. The above system has been tested at a pilot site along Ohio's Lake Erie shore and is to be applied to a new test site in Tampa Bay, Florida.