ppxscal/embedding_network huggingface dataset:
An optimal method for dna sequencing by hybridization
Authors: Franco P. Preparata
Venue:  (2003)

Sequencing by Hybridization (SBH) is a potentially powerful method for sequencing unknown DNA. An information-theoretic argument indicates that SBH can be used to sequence DNA fragments orders of magnitude longer than existing methods. Although originally proposed in 1988, SBH was unable to fulfill its promise until recently, with the invention of gapped probes containing biochemical wildcard nucleotides called universal bases. Using gapped probes and novel algorithms exploiting their structure, SBH performance has been able to formally approach the theoretic bound. This research is concerned with the development, analysis and refinement of algorithms which push performance closer to the bound, for randomly generated and natural DNA sequences. We present a novel analysis of the branching behaviour of the gapped SBH algorithm, and of the two failures modes of the sequencing algorithm. We also present several enhancements to the basic gapped SBH algorithm. Two of these enhancements improve performance on random DNA, and a third is designed to identify and recover from failures which occur only in natural sequences. The aggregate result of the improvements presented is to push the overall effectiveness of the algorithm on random data to almost 2/3 of the proven theoretic bound, and to significantly reduce the gap between random and natural sequence reconstruction.
Maximizing the spread of influence through a social network
Authors: David Kempe, Jon Kleinberg, Éva Tardos
Venue: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining (2003)

Models for the processes by which ideas and influence propagate through a social network have been studied in a number of domains, including the diffusion of medical and technological innovations, the sudden and widespread adoption of various strategies in game-theoretic settings, and the effects of "word of mouth" in the promotion of new products. Recently, motivated by the design of viral marketing strategies, Domingos and Richardson posed a fundamental algorithmic problem for such social network processes: if we can try to convince a subset of individuals to adopt a new product or innovation, and the goal is to trigger a large cascade of further adoptions, which set of individuals should we target?We consider this problem in several of the most widely studied models in social network analysis. The optimization problem of selecting the most influential nodes is NP-hard here, and we provide the first provable approximation guarantees for efficient algorithms. Using an analysis framework based on submodular functions, we show that a natural greedy strategy obtains a solution that is provably within 63% of optimal for several classes of models; our framework suggests a general approach for reasoning about the performance guarantees of algorithms for these types of influence problems in social networks.We also provide computational experiments on large collaboration networks, showing that in addition to their provable guarantees, our approximation algorithms significantly out-perform node-selection heuristics based on the well-studied notions of degree centrality and distance centrality from the field of social networks.
SPADES a system for parallel-agent, discrete-event simulation
Authors: Patrick Riley
Venue: AI Magazine (2003)

Simulations are an excellent tool for studying AI. However, the simulation technology in use by, and designed for, the AI community often fails to take advantage of much of the work in the larger simulation community to produce stable, repeatable, and efficient simulations. I present SPADES (SYSTEM FOR PARALLEL-AGENT DISCRETE-EVENT SIMULATION) as a simulation substrate for the AI community. SPADES focuses on the agent as a fundamental simulation component. The "thinking time" of an agent is tracked and reflected in the results of the agents' actions. SPADES supports and manages the distribution of agents across machines while it is robust to variations in network performance and machine load. SPADES is not tied to any particular simulation and is a powerful new tool for creating simulations for the study of AI.
Computational comparative genomics: genes, regulation, evolution
Authors: Manolis (Kellis) Kamvysselis
Venue:  (2003)

Understanding the biological signals encoded in a genome is a key challenge of computational biology. These signals are encoded in the four-nucleotide alphabet of DNA and are responsible for all molecular processes in the cell. In particular, the genome contains the blueprint of all protein-coding genes and the regulatory motifs used to coordinate the expression of these genes. Comparative genome analysis of related species provides a general approach for identifying these functional elements, by virtue of their stronger conservation across evolutionary time. In this thesis we address key issues in the comparative analysis of multiple species. We present novel computational methods in four areas (1) the automatic comparative annotation of multiple species and the determination of orthologous genes and intergenic regions; (2) the validation of computationally predicted protein-coding genes; (3) the systematic de-novo identification of regulatory motifs; (4) the determination of combinatorial interactions between regulatory motifs. We applied these methods to the comparative analysis of four yeast genomes, including the best-studied eukaryote, Saccharomyces cerevisiae or baker's yeast. Our results show that nearly a tenth of currently annotated yeast genes are not real, and have refined the structure of hundreds of genes. Additionally, we have automatically discovered a dictionary of regulatory motifs without any previous biological knowledge. These include most previously known regulatory motifs, and a number of novel motifs. We have automatically assigned candidate functions to the majority of motifs discovered, and defined biologically meaningful combinatorial interactions between them. Finally, we defined the regions and mechanisms of rapid evolution, with important biological implications. Our results demonstrate the central role of computational tools in modern biology. The analyses presented in this thesis have revealed biological findings that could not have been discovered by traditional genetic methods, regardless of the time or effort spent. The methods presented are general and may present a new paradigm for understanding the genome of any single species. They are currently being applied to a kingdom-wide exploration of fungal genomes, and the comparative analysis of the human genome with that of the mouse and other mammals. (Copies available exclusively from MIT Libraries, Rm. 14-0551, Cambridge, MA 02139-4307. Ph. 617-253-5668; Fax 617-253-1690.)
Evolutionary and adaptive strategies for efficient search across whole system engineering design hierarchies
Authors: I. C. Parmee
Venue: Artificial Intelligence for Engineering Design, Analysis and Manufacturing (1998)

Evolutionary and Adaptive strategies (ES & AS) for diverse multilevel search across a preliminary, whole-system design hierarchy defined by discrete and continuous variable parameters are described. Such strategies provide high-level decision support when integrated with preliminary design software describing the major elements of an engineering system. Initial work involving a Structured Genetic Algorithm (stGA) with appropriate mutation regimes to encourage search diversity is described and preliminary results are presented. The shortcomings of the stGA approach are identified and alternative strategies are introduced. A dual agent strategy (GAANT) involving elements of an ant colony search and an evolutionary search concurrently manipulating the discrete and continuous variable parameter sets is presented. Appropriate communication between the two search agents results in a more efficient search across the hierarchy than that achieved by the stGA, while also simplifying the chromosomal representation. This simplification allows the further development of the preliminary design hierarchy in terms of complexity. The technique therefore represents a significant contribution to configuration design where multilevel, mixed discrete/continuous parameter design problems can be prevalent.
Increased system reliability through improved validation of knowledge in expert systems with single domain expert development teams
Authors: Aaron Ben Clevenson
Venue:  (2003)

Current software engineering techniques provide a solid foundation for the validation and verification of computer applications. They ensure that delivered applications are of higher quality and have a reduced number of &ldquo;bugs&rdquo; due to developer error. These techniques do not address &ldquo;bugs&rdquo; that are inherent in the knowledge, requirements, or specifications as they are received from the experts. 30% of the &ldquo;bugs&rdquo; occurring in software development originate in the Requirements Phase (Jones, 1991). Baseline data indicates that a third of these, or 10% of the &ldquo;bugs&rdquo; in software development projects, are due to errors in the knowledge or specifications received from the expert. This dissertation describes a technique, Knowledge Validation, which enhances knowledge acquisition for expert system development or specification and requirements gathering in traditional software development projects. For projects with multiple experts participating on the development team, techniques such as use of the Delphi Algorithm (Brown et al. 1969; Shafai, 1989) are available to reduce these expert induced errors. This technique focuses on projects where there is a single expert participating on the development team.
On the Implementation of SPMD Applications Using Haskell#
Authors: Francisco Heron de Carvalho Junior, Rafael Dueire Lins, Nívia Cruz Quental
Venue: Proceedings of the 15th Symposium on Computer Architecture and High Performance Computing (2003)

Commodities-built clusters, a low cost alternative for distributed parallel processing, brought high-performance computing to a wide range of users. However, the existing widespread tools for distributed parallel programming, such as messaging passing libraries, does not attend newsoftware engineering requirements that nave emerged due to increase in complexity of applications. Haskell# is a parallel programming language intending to reconcile higher abstraction and modularity with scalable performance. In this paper, it is demonstrated the use of Haskell# in the programming of three SPMD benchmark programs, which have lower-level MPI implementations available.
Spatialized audioconferencing: what are the benefits?
Authors: Ryan Kilgore, Mark Chignell, Paul Smith
Venue: Proceedings of the 2003 conference of the Centre for Advanced Studies on Collaborative research (2003)

Audioconference participants often have difficulty identifying the voices of other conferees, especially in ad hoc groups of unfamiliar members. Simultaneous presentation of multiple voices through a single, monaural channel can be discordant and difficult to comprehend. To address these shortcomings, we have developed the Vocal Village, a communications tool that allows for real-time spatialized audioconferencing across the Internet. The Vocal Village system uses binaural audio signals to present the voices of individual conference participants from different apparent positions in space by adding location cues to audio information.This paper describes our experimental research to determine whether the real-time, "within the head," spatialization cues implemented by Vocal Village are sufficient to provide performance benefits compared to traditional, monaural audio-conferencing methods. Performance benefits included memory, speaker identification, and participant preference. We also investigated whether providing users with the ability to control the location of conference participants within a virtual auditory space further enhanced any such benefits.The "within the head" spatialization used in this experiment did not lead to a statistically significant increase in the ability to remember who said what in an audioconference. However, there was a borderline significant increase in remembering who said what when participants were given the opportunity to move the voices of two similar sounding conferees into different apparent locations. Participants also significantly preferred spatialized audio formats over the mono audio format. Spatialization had a significant effect on improving participants' perceived confidence in their memory of conferee viewpoints. Additionally, spatialization significantly reduced both the perceived difficulty of identifying speakers during conferences, as well as the amount of attention perceived to be dedicated to performing such voice identification. Providing subjects with the ability to control the apparent location of conference participants resulted in the greatest benefit to both of these measures.
Some statistics on ALGOL 68 programs
Authors: Dick Grune
Venue: ACM SIGPLAN Notices (1979)

An attempt is made to assess some static and dynamic properties of ALGOL 68 programs, which are useful for optimization decisions. The results indicate that slicing and assignation are the most important candidates for optimization, and that optimization efforts need to be directed to the simple cases only.
Euclid and Modula
Authors: David T. Barnard, W. David Elliott, David H. Thompson
Venue: ACM SIGPLAN Notices (1978)

Both Euclid and Modula are programming languages based on Pascal and intended for writing system software such as operating system kernels. The further goals of each language, however, resulted in two rather different languages. Modula is meant to be used in multiprogramming systems primarily on mini-computers; thus Modula aims for very small run-time support and efficient compilation by a small compiler. Many of the Euclid language design decisions, on the other hand, were influenced by the authors' overriding concern for the ability to verify Euclid programs. This paper discusses design goals of the two languages and the language differences that resulted. After contrasting individual features of the two languages, modules and multiprogramming are discussed in more detail.
Prototype-based mining of numeric data streams
Authors: Francisco Ferrer-Troyano, Jesús S. Aguilar-Ruiz, José C. Riquelme
Venue: Proceedings of the 2003 ACM symposium on Applied computing (2003)

Great organizations collect open-ended and time-changing data received at a high speed. The possibility of extracting useful knowledge from these potentially infinite databases is a new challenge in Data Mining. In this paper we propose an anytime incremental learning algorithm for mining numeric data streams. Within Supervised Learning, our approach is based on prototypes and hypercubic decision rules, concerning with the simplicity of the model provided and the time complexity as primary goals. Experimental results with synthetic databases of 100 gigabytes show a good performance from streams of data in continuous transformation.
A general compiler framework for speculative multithreaded processors
Authors: Anasua Bhowmik
Venue:  (2003)

The increasing transistor densities offered by semiconductor technology and the desire to reduce the completion time of general purpose programs have led the hardware designers and the compiler writers to develop aggressive techniques for exploiting program parallelism. Speculative multithreading (SpMT) is emerging as an effective mechanism for exploiting thread level parallelism from non-numeric programs. SpMT processors allow the program to execute in the presence of ambiguous control and data dependences and recover when dependence violations are detected at run-time. Proper thread formation is crucial to obtain good speedup in an SpMT system. Most existing compilers for SpMT architectures concentrate on extracting parallelism from only loops. However, general purpose programs spend considerable amount of time outside the loops (or in the loops that cannot be parallelized). Studies have confirmed that a significant amount of parallelism also exists outside loops. In this dissertation we present a compiler framework for partitioning sequential programs into multiple threads for parallel execution in an SpMT system. Beside exploiting loop level parallelism, our compiler extracts parallelism from regions outside loops as well. Our compiler performs extensive program analyses and profiling to capture the actual data dependences and control dependences in programs. We have also developed a simple and fast interprocedural analysis scheme to facilitate the program analysis by SpMT compilers. We have proposed two models to represent the inter-thread data dependences in the program and have used them in our partitioning algorithm. The compiler is implemented on the SUIF-MachSUIF platform and is able to partition large programs, such as the SPEC benchmark programs. We have evaluated the effectiveness of our compiler with a trace driven simulator. Experimental results clearly show the ability of our compiler to extract significant parallelism from both the loops and non-loop regions of the non-numeric programs. Our experimental studies also indicate that hardware supports for data value prediction and out-of-order thread spawning are to achieve better performance.
A collaborative intelligent tutoring system for medical problem-based learning
Authors: Siriwan Suebnukarn, Peter Haddawy
Venue: Proceedings of the 9th international conference on Intelligent user interfaces (2004)

This paper describes COMET, a collaborative intelligent tutoring system for medical problem-based learning. The system uses Bayesian networks to model individual student knowledge and activity, as well as that of the group. It incorporates a multi-modal interface that integrates text and graphics so as to provide a rich communication channel between the students and the system, as well as among students in the group. Students can sketch directly on medical images, search for medical concepts, and sketch hypotheses on a shared workspace. The prototype system incorporates substantial domain knowledge in the area of head injury diagnosis. A major challenge in building COMET has been to develop algorithms for generating tutoring hints. Tutoring in PBL is particularly challenging since the tutor should provide as little guidance as possible while at the same time not allowing the students to get lost. From studies of PBL sessions at a local medical school, we have identified and implemented eight commonly used hinting strategies. We compared the tutoring hints generated by COMET with those of experienced human tutors. Our results show that COMET's hints agree with the hints of the majority of the human tutors with a high degree of statistical agreement (McNemar test, p = 0.652, Kappa = 0.773).
Construction of a Chinese&ndash;English Verb Lexicon for Machine Translation and Embedded Multilingual Applications
Authors: Bonnie Jean Dorr, Gina-Anne Levow, Dekang Lin
Venue: Machine Translation (2002)

This paper addresses the problem of automatic acquisition of lexical knowledge for rapid construction of engines for machine translation and embedded multilingual applications. We describe new techniques for large-scale construction of a Chinese&ndash;English verb lexicon and we evaluate the coverage and effectiveness of the resulting lexicon. Leveraging off an existing Chinese conceptual database called HowNet and a large, semantically rich English verb database, we use thematic-role information to create links between Chinese concepts and English classes. We apply the metrics of recall and precision to evaluate the coverage and effectiveness of the linguistic resources. The results of this work indicate that: (a) we are able to obtain reliable Chinese&ndash;English entries both with and without pre-existing semantic links between the two languages; (b) if we have pre-existing semantic links, we are able to produce a more robust lexical resource by merging these with our semantically rich English database; (c) in our comparisons with manual lexicon creation, our automatic techniques were shown to achieve 62% precision, compared to a much lower precision of 10% for arbitrary assignment of semantic links.
Software metrics, information and entropy
Authors: Jana Dospisil
Venue: Practicing software engineering in the 21st century (2003)

This chapter describes the foundation and properties of object-oriented software measures. Many software measures for object-oriented applications have been developed and tested in the development environment. However, the process of defining new measures is still alive. The reason for such development lies in difficulties associated with understanding and maintaining object-oriented applications. It is still difficult to relate the measures to the phenomena we want to improve. Do our measurements indicate problems in reliability, maintenance, or too much complexity of some portions of the application? In order to reduce the complexity of software, new development methodologies and tools are being introduced. An example of the new approach to development is separation of concern. The tools, such as Aspect/J (Kiezales et al., 1997) or Hyper/J (Ossher & Tarr, 1998), facilitate the development process. There does not seem to be a sound metrics suite to measure complexity and efficiency of applications developed and coded with Aspect/J or Hyper/J. In this chapter, we attempt to review the current research into object-oriented software metrics and suggest theoretical framework for complexity estimation and ranking of compositional units in object-oriented applications developed with Hyper/J.
Misuse detection for information retrieval systems
Authors: Rebecca Cathey, Ling Ma, Nazli Goharian, David Grossman
Venue: Proceedings of the twelfth international conference on Information and knowledge management (2003)

We present a novel approach to detect misuse within an information retrieval system by gathering and maintaining knowledge of the behavior of the user rather than anticipating attacks by unknown assailants. Our approach is based on building and maintaining a profile of the behavior of the system user through tracking, or monitoring of user activity within the information retrieval system. Any new activity of the user is compared to the user profile to detect a potential misuse for the authorized user. We propose four different methods to detect misuse in information retrieval systems. Our experimental results on $2$ GB collection favorably demonstrate the validity of our approach.
Secure sensor networks for perimeter protection
Authors: Sasikanth Avancha, Jeffrey Undercoffer, Anupam Joshi, John Pinkston
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2003)

Sensor networks have been identified as being useful in a variety of domains to include the battlefield and perimeter defense. We motivate the security problems that sensor networks face by developing a scenario representative of a large application class where these networks would be used in the future. We identify threats to this application class and propose a new lightweight security model that operates in the base station mode of sensor communication, where the security model is mindful of the resource constraints of sensor networks. Our application class requires mitigation against traffic analysis, hence we do not use any routing mechanisms, relying solely on broadcasts of end-to-end encrypted packets. Our model extends the broadcast range of the base station model by utilizing nodes adjacent to the base station as an intermediary hop. Additionally, our model detects and corrects some classes of aberrant node behavior. We have simulated our model and present simulation results.