Nonsystematic Search and No-Good Learning

Nonsystematic search algorithms seem, in general, to be well suited to large-scale problems with many solutions. However, they tend to perform badly for problems with few solutions, and they cannot be used for insoluble problems, since they are incomplete.Here we present a new algorithm, learn-SAT, that, although based on nonsystematic search, is complete. Completeness is realized through a process of no-good learning, learning-by-merging. This requires exponential space in the worst case. We show, nevertheless, that learn-SAT performs very well on certain SAT problems that are tightly constrained or insoluble. Indeed, its performance generally approximates the best SAT algorithms and does much better at lower clause densities. Learn-SAT also maintains much of the efficient performance of nonsystematic search for large-scale problems with many solutions, at least relative to backtrack search algorithms.These results indicate that the burden on memory, imposed by no-good learning, is not generally a problem for learn-SAT. This is perhaps surprising in view of previous work. What is even more surprising is the scalability of learn-SAT. For some types of problem it scales very much better than the nearest competitive algorithm. There are other types, however, for which this is not the case.The performance profile of learn-SAT emerges from an experimental methodology related to the one outlined by Mammen and Hogg in 1997.     

A linear-time algorithm to construct a rectilinear Steiner minimal tree fork-extremal point sets

Ak-extremal point set is a point set on the boundary of ak-sided rectilinear convex hull. Given ak-extremal point set of sizen, we present an algorithm that computes a rectilinear Steiner minimal tree in timeO(k ⁴ n). For constantk, this algorithm runs inO(n) time and is asymptotically optimal and, for arbitraryk, the algorithm is the fastest known for this problem.     

An objective, entropy-based approach to evaluating migration issues in computer IS

Recent breakthroughs in computing technology have created a set of perplexing new problems for information systems (IS) professionals. These revolve around decisions to be made about replacing current systems with newer technology, upgrading existing systems, and migrating to other platforms or environments. Many decision makers must rely on subjective assessments, such as their instincts or the recommendation of vendors rather than on an objective analysis of their information needs and how they can be met by various system alternatives. A model to quantify these issues, providing an objective measure for comparing system alternatives, including migration, would be valuable. Such a model is demonstrated here; it uses the Shannon-Weaver entropy model in conjunction with quality measures to quantify actual and potential system effectiveness.     

Overcoming the information overload problem in a multiform feedback-based virtual reality system for hand motion rehabilitation: healthy subject case study

The use of composite multiple feedback in a newly proposed virtual reality system enables the patient to perceive similar real-world performance in the virtual world. However, it might cause information overload, which makes the patient feel confused and distracted during training. The aim of this study is to investigate the effectiveness of having separate function-specific feedback pre-training prior to the final multiform feedback task. During the evaluating tests with thirty healthy subjects, it has been found that effective pre-training set could overcome the problem in the main task. Minor modifications on the pre-training set could overcome or aggravate the problem, which indicates the importance of choosing the correct pre-training parameters.     

A multi-institutional, multinational study of programming concepts using card sort data

Abstract: This paper presents a case study of the use of a repeated single‐criterion card sort with an unusually large, diverse participant group. The study, whose goal was to elicit novice programmers' knowledge of programming concepts, involved over 20 researchers from four continents and 276 participants drawn from 20 different institutions. In this paper we present the design of the study and the unexpected result that there were few discernible systematic differences in the population. The study was one of the activities of the National Science Foundation funded Bootstrapping Research in Computer Science Education project (2003).     

Fatigue crack growth behavior of X2095 Al–Li alloy

Microstructures and micro-textures of X2095 Al–Li alloy in as-received/superplastic state were characterized by means of SEM/BDS, X-ray diffraction and orientation imaging microscopy (OIM). It was observed that the microstructure of the alloy was typical of a particulate-reinforced composite material, consisting of aluminum matrix and homogeneously distributed T_B(Al₇Cu₄Li) particles with a volume fraction of about 10%. Brass-type texture was the dominant texture component. Both constant amplitude and near-threshold fatigue crack growth rates of the alloy in the L–T and T–L orientations were determined at different stress ratios. Particular attention was paid to the role of the T_B phase in the fatigue crack growth. When a fatigue crack approached a T_B particle, the crack basically meandered to avoid the particle. The T_B particles thus provided a strong resistance to the propagation of fatigue crack by promoting crack deflection and the related crack closure effects. The fatigue crack propagation behavior has been explained by the microstructural features, micro-textures, cracking characteristics and crack closure effects.     

Some Aspects of Binding GKS to C++

Aspects of a prototype binding of GKS to the C++ programming language are presented. The binding makes use of classes and derived classes to define GKS concepts such as segments and workstations. Operator overloading is used for some GKS Functions.     

A platform for biological sequence comparison on parallel computers

We have written two programs for searching biological sequence databases that run on Intel hypercube computers. PSCANLIB compares a single sequence against a sequence library, and PCOMPLIB compares all the entries in one sequence library against a second library. The programs provide a general framework for similarity searching; they include functions for reading in query sequences, search parameters and library entries, and reporting the results of a search. We have isolated the code for the specific function that calculates the similarity score between the query and library sequence; alternative searching algorithms can be implemented by editing two files. We have implemented the rapid FASTA sequence comparison algorithm and the more rigorous Smith-Waterman algorithm within this framework. The PSCANLIB program on a 16 node iPSC/2 80386-based hypercube can compare a 229 amino acid protein sequence with a 3.4 million residue sequence library in approximately 16 s with the FASTA algorithm. Using the Smith-Waterman algorithm, the same search takes 35 min. The PCOMPLIB program can compare a 0.8 million amino acid protein sequence library with itself in 5.3 min with FASTA on a third-generation 32 node Intel iPSC/860 hypercube.     

Aluminum: Approaching the new millennium

During the past 100 years, aluminum has developed into a staple of the manufacturing industry. The industry has undergone successive revolutions in consumption, smelter location, and pricing. Now, it faces more change as products mature, new markets struggle to develop, and technology advances further.