Search Space Research Papers - Academia.edu (original) (raw)

Automated segmentation of the esophagus in CT images is of high value to radiologists for oncological examinations of the mediastinum. It can serve as a guideline and prevent confusion with pathological tissue. However, segmentation is a... more

Automated segmentation of the esophagus in CT images is of high value to radiologists for oncological examinations of the mediastinum. It can serve as a guideline and prevent confusion with pathological tissue. However, segmentation is a challenging problem due to low contrast and versatile appearance of the esophagus. In this paper, a two step method is proposed which first finds the approximate shape using a "detect and connect" approach. A classifier is trained to find short segments of the esophagus which are approximated by an elliptical model. Recently developed techniques in discriminative learning and pruning of the search space enable a rapid detection of possible esophagus segments. Prior shape knowledge of the complete esophagus is modeled using a Markov chain framework, which allows efficient inferrence of the approximate shape from the detected candidate segments. In a refinement step, the surface of the detected shape is non-rigidly deformed to better fit the...

The testing and debugging of complex programs has always been one of the most cost-determining factors in software design. This is even more true when parallel programs are considered. Debugging them is often based on a debugging cycle.... more

The testing and debugging of complex programs has always been one of the most cost-determining factors in software design. This is even more true when parallel programs are considered. Debugging them is often based on a debugging cycle. First we make an assumption about the probable source of the bug, and next the validity of this assumption is verified. By repeatedly applying this technique, we try to limit the search-space until eventually the bug is resolved. There is a great need however for powerful high-level tools that enable the localization of bugs without indulging in this time-consuming error-prone debugging cycle. This paper describes such a high-level debugging tool, based on the animation of a program on its hierarchical-graphical representation.

A model for highway development is presented, which uses geographic information systems (GIS), genetic algorithms (GA), and computer visualization (CV). GIS serves as a repository of geographic information and enables spatial... more

A model for highway development is presented, which uses geographic information systems (GIS), genetic algorithms (GA), and computer visualization (CV). GIS serves as a repository of geographic information and enables spatial manipulations and database management. GAs are used to optimize highway alignments in a complex search space. CV is a technique used to convey the characteristics of alternative solutions, which can be the basis of decisions. The proposed model implements GIS and GA to find an optimized alignment based on the minimization of highway costs. CV is implemented to investigate the effects of intangible parameters, such as unusual land and environmental characteristics not considered in optimization. Constrained optimization using GAs may be performed at subsequent stages if necessary using feedback received from CVs. Implementation of the model in a real highway project from Maryland indicates that integration of GIS, GAs, and CV greatly enhances the highway development process.

This paper proposes a new grammar-guided genetic programming (GGGP) system by introducing two original genetic operators: crossover and mutation, which most influence the evolution process. The first, the so-called grammar-based crossover... more

This paper proposes a new grammar-guided genetic programming (GGGP) system by introducing two original genetic operators: crossover and mutation, which most influence the evolution process. The first, the so-called grammar-based crossover operator, strikes a good balance between search space exploration and exploitation capabilities and, therefore, enhances GGGP system performance. And the second is a grammar-based mutation operator, based on the crossover, which has been designed to generate individuals that match the syntactical constraints of the context-free grammar that defines the programs to be handled. The use of these operators together in the same GGGP system assures a higher convergence speed and less likelihood of getting trapped in local optima than other related approaches. These features are shown throughout the comparison of the results achieved by the proposed system with other important crossover and mutation methods in two experiments: a laboratory problem and the real-world task of breast cancer prognosis.

Abstract In this paper, an investigation of the behavior of a recently defined hybrid algorithm for continuous variables electromagnetic optimization problems is presented. This algorithm makes use of the nonlinear simplex method as a... more

Abstract In this paper, an investigation of the behavior of a recently defined hybrid algorithm for continuous variables electromagnetic optimization problems is presented. This algorithm makes use of the nonlinear simplex method as a principal optimizator, and a greedy genetic algorithm to explore the search space. The algorithm is greatly affected by the tuning of some parameters. Referring to a solenoids system optimal design problem, a detailed comparison of performances obtained implementing a metaheuristic tuning is presented

This paper develops the multidimensional binary search tree (or k -d tree, where k is the dimensionality of the search space) as a data structure for storage of information to be retrieved by associative searches. The k -d tree is defined... more

This paper develops the multidimensional binary search tree (or k -d tree, where k is the dimensionality of the search space) as a data structure for storage of information to be retrieved by associative searches. The k -d tree is defined and examples are given. It is shown to be quite efficient in its storage requirements. A significant advantage of this structure is that a single data structure can handle many types of queries very efficiently. Various utility algorithms are developed; their proven average running times in an n record file are: insertion, O (log n ); deletion of the root, O ( n ( k -1)/ k ); deletion of a random node, O (log n ); and optimization (guarantees logarithmic performance of searches), O ( n log n ). Search algorithms are given for partial match queries with t keys specified [proven maximum running time of O ( n ( k - t )/ k )] and for nearest neighbor queries [empirically observed average running time of O (log n ).] These performances far surpass the b...

This paper presents a new solution to the thermal unit-commitment (UC) problem based on an integer-coded genetic algorithm (GA). The GA chromosome consists of a sequence of alternating sign integer numbers representing the sequence of... more

This paper presents a new solution to the thermal unit-commitment (UC) problem based on an integer-coded genetic algorithm (GA). The GA chromosome consists of a sequence of alternating sign integer numbers representing the sequence of operation/reservation times of the generating units. The proposed coding achieves significant chromosome size reduction compared to the usual binary coding. As a result, algorithm robustness

AI has had notable success in building high-performance game-playing programs to complete against the best human players. However, the availability of fast and plentiful machines with large memories and disks creates the possibility of... more

AI has had notable success in building high-performance game-playing programs to complete against the best human players. However, the availability of fast and plentiful machines with large memories and disks creates the possibility of solving a game. This has been done before for simple or relatively small games. In this paper, we present new ideas and algorithms for solving the game of checkers. Checkers is a popular game of skill with a search space of 10 20 possible positions. This paper reports on our first result. One of the ...

Retrieval of relevant documents from a collection is a tedious task. As genetic algorithms (GA) are robust and efficient search and optimization techniques, they can be used to search the huge document search space. In this paper, a... more

Retrieval of relevant documents from a collection is a tedious task. As genetic algorithms (GA) are robust and efficient search and optimization techniques, they can be used to search the huge document search space. In this paper, a general frame work of information retrieval system is discussed. The applicability of genetic algorithms in the field of information retrieval is also

In 1962, a checkers-playing program written by Arthur Samuel defeated a self-proclaimed master player, creating a sensation at the time for the fledgling eld of computer science called articial intelligence. The historical record refers... more

In 1962, a checkers-playing program written by Arthur Samuel defeated a self-proclaimed master player, creating a sensation at the time for the fledgling eld of computer science called articial intelligence. The historical record refers to this event as having solved the game of checkers. This paper discusses achieving three dierent levels of solving the game: publicly (as evidenced by Samuel's