ppxscal/embedding_network huggingface dataset:
A fuzzy neural network with fuzzy impact grades
Authors: Song Hengjie, Miao Chunyan, Shen Zhiqi, Miao Yuan, Bu-Sung Lee
Venue: Neurocomputing (2009)

Fuzzy rule derivation is often difficult and time-consuming, and requires expert knowledge. This creates a common bottleneck in fuzzy system design. In order to solve this problem, many fuzzy systems that automatically generate fuzzy rules from numerical data have been proposed. In this paper, we propose a fuzzy neural network based on mutual subsethood (MSBFNN) and its fuzzy rule identification algorithms. In our approach, fuzzy rules are described by different fuzzy sets. For each fuzzy set representing a fuzzy rule, the universe of discourse is defined as the summation of weighted membership grades of input linguistic terms that associate with the given fuzzy rule. In this manner, MSBFNN fully considers the contribution of input variables to the joint firing strength of fuzzy rules. Afterwards, the proposed fuzzy neural network quantifies the impacts of fuzzy rules on the consequent parts by fuzzy connections based on mutual subsethood. Furthermore, to enhance the knowledge representation and interpretation of the rules, a linear transformation from consequent parts to output is incorporated into MSBFNN so that higher accuracy can be achieved. In the parameter identification phase, the backpropagation algorithm is employed, and proper linear transformation is also determined dynamically. To demonstrate the capability of the MSBFNN, simulations in different areas including classification, regression and time series prediction are conducted. The proposed MSBFNN shows encouraging performance when benchmarked against other models.
A Reasoning-Based Support Tool for Ontology Mapping Evaluation
Authors: Christian Meilicke, Heiner Stuckenschmidt, Ondřej Šváb-Zamazal
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

In this paper we describe a web-based tool that supports the human in revising ontology alignments. Our tool uses logical reasoning as a basis for detecting conflicts in mappings and exploits these conflicts to propagate user decision. The proposed approach reduces the effort of the human expert and points to logical problems that are hard to find without support.
DISCOVER
Authors: Wenjie Fu, Pradipta Ray, Eric P. Xing
Venue: Bioinformatics (2009)

Motivation: Identifying transcription factor binding sites (TFBSs) encoding complex regulatory signals in metazoan genomes remains a challenging problem in computational genomics. Due to degeneracy of nucleotide content among binding site instances or motifs, and intricate ‘grammatical organization’ of motifs within cis-regulatory modules (CRMs), extant pattern matching-based in silico motif search methods often suffer from impractically high false positive rates, especially in the context of analyzing large genomic datasets, and noisy position weight matrices which characterize binding sites. Here, we try to address this problem by using a framework to maximally utilize the information content of the genomic DNA in the region of query, taking cues from values of various biologically meaningful genetic and epigenetic factors in the query region such as clade-specific evolutionary parameters, presence/absence of nearby coding regions, etc. We present a new method for TFBS prediction in metazoan genomes that utilizes both the CRM architecture of sequences and a variety of features of individual motifs. Our proposed approach is based on a discriminative probabilistic model known as conditional random fields that explicitly optimizes the predictive probability of motif presence in large sequences, based on the joint effect of all such features. Results: This model overcomes weaknesses in earlier methods based on less effective statistical formalisms that are sensitive to spurious signals in the data. We evaluate our method on both simulated CRMs and real Drosophila sequences in comparison with a wide spectrum of existing models, and outperform the state of the art by 22% in F1 score. Availability and Implementation: The code is publicly available at http://www.sailing.cs.cmu.edu/discover.html. Contact: epxing@cs.cmu.edu Supplementary information:Supplementary data are available at Bioinformatics online.
Multiscale finite-volume method for parabolic problems arising from compressible multiphase flow in porous media
Authors: Hadi Hajibeygi, Patrick Jenny
Venue: Journal of Computational Physics (2009)

The multiscale finite-volume (MSFV) method was originally developed for the solution of heterogeneous elliptic problems with reduced computational cost. Recently, some extensions of this method for parabolic problems have been proposed. These extensions proved effective for many cases, however, they are neither general nor completely satisfactory. For instance, they are not suitable for correctly capturing the transient behavior described by the parabolic pressure equation. In this paper, we present a general multiscale finite-volume method for parabolic problems arising, for example, from compressible multiphase flow in porous media. Opposed to previous methods, here, the basis and correction functions are solutions of full parabolic governing equations in localized domains. At the same time, to enhance the computational efficiency of the scheme, the basis functions are kept pressure independent and do not have to be recalculated as pressure evolves. This general approach requires no additional assumptions and its good efficiency and high accuracy is demonstrated for various challenging test cases. Finally, to improve the quality of the results and also to extend the scheme for highly anisotropic heterogeneous problems, it is combined with the iterative MSFV (i-MSFV) method for parabolic problems. As one iterates, the i-MSFV solutions of compressible multiphase problems (parabolic problems) converge to the corresponding fine-scale reference solutions in the same way as demonstrated recently for incompressible cases (elliptic problems). Therefore, the proposed MSFV method can also be regarded as an efficient linear solver for parabolic problems and studies of its efficiency are presented for many test cases.
Disambiguating authors in academic publications using random forests
Authors: Pucktada Treeratpituk, C. Lee Giles
Venue: Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries (2009)

Users of digital libraries usually want to know the exact author or authors of an article. But different authors may share the same names, either as full names or as initials and last names (complete name change examples are not considered here). In such a case, the user would like the digital library to differentiate among these authors. Name disambiguation can help in many cases; one being a user in a search of all articles written by a particular author. Disambiguation also enables better bibliometric analysis by allowing a more accurate counting and grouping of publications and citations. In this paper, we describe an algorithm for pair-wise disambiguation of author names based on a machine learning classification algorithm, random forests. We define a set of similarity profile features to assist in author disambiguation. Our experiments on the Medline database show that the random forest model outperforms other previously proposed techniques such as those using support-vector machines (SVM). In addition, we demonstrate that the variable importance produced by the random forest model can be used in feature selection with little degradation in the disambiguation accuracy. In particular, the inverse document frequency of author last name and the middle name's similarity alone achieves an accuracy of almost 90%.
PC Troubleshoooting Pocket Guide, 5th edition
Authors: Jean Andrews
Venue:  (2007)

This compact volume provides essential diagnostic and troubleshooting information The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Investigating Learner Autonomy toward e-learning
Authors: Shu-Sheng Liaw, Hsiu-Mei Huang
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

Although e-learning is a capable tool for world wide students, learner autonomy is a critical issue for enhancing e-learning usage. The purpose of this study is to investigate individual learner autonomy toward e-learning. Based on Taiwan and UK University's students, this research proposes a web questionnaire survey to explore learners' attitudes toward e-learning. After statistical analyses, both Taiwan's and UK's students' learner autonomy can be predicted by perceived usefulness of sharing, quality of learning functions, and quality of interaction. Moreover, from Taiwan's and UK's students, learner autonomy has high correlation with perceived enjoyment of multi-format contents. Additionally, the results of this study find that Taiwan's students have more positive attitudes toward e-learning than UK's students have.
Biologically-implemented genetic algorithm for protein engineering
Authors: Hiroshi Someya, Kensaku Sakamoto, Masayuki Yamamura
Venue: Proceedings of the 11th Annual conference on Genetic and evolutionary computation (2009)

Protein engineering, developing novel proteins with a desired activity, has become increasingly important in many fields. This paper presents two studies in protein engineering: (i) a biological implementation of a genetic algorithm, with an observed in vitro evolution, and (ii) its preliminary computer simulation using a prototypical probabilistic model based on a random walk. The steady evolution of the fitness distribution of the mutant proteins that appeared in the biological experiments has provided some convincing evidence about the search behavior and the fitness landscape. The computer simulation and the simple probabilistic model have indicated their future potential for providing a practical alternative to the time-consuming manual operations in the biological experiments. Successful experimental results in the two studies have raised expectations of their further development and mutually beneficial interactions.
Technology infrastructure in support of a medical & bioinformatics masters degree
Authors: Guenter Tusch, Paul Leidig, Gregory Wolffe, David Elrod, Carl Strebel
Venue: Proceedings of the 14th annual ACM SIGCSE conference on Innovation and technology in computer science education (2009)

In 2003, Grand Valley State University started a Masters program in Medical & Bioinformatics. This M.S. degree, together with related degrees in Biostatistics and Biotechnology, were part of the "Professional Science Masters" development and implementation initiative supported by the Sloan Foundation. The interdisciplinary curriculum includes common core courses, the promotion and development of "soft skills" through teamwork and project management experiences, and an applied research focus with a mandatory business/industry internship. Instrumental to achieving these goals is a strong lab component to the curriculum that incorporates familiarity with industry-standard and widely-used software packages. We here give an update on details of the system architecture, software components, and their adaptations through the first six years of our program.
Development of Know-how Information Sharing System in Care Planning Processes
Authors: Kaoru Eto, Tatsunori Matsui, Yasuo Kabasawa
Venue: Proceeding of the 2006 conference on Learning by Effective Utilization of Technologies: Facilitating Intercultural Understanding (2006)

The purpose of this study is to develop a computer support system for educating personnel who are involved in care management. We propose a system in which know-how information can be shared. We consider that visualizing and showing care plans drawn up by experts in various forms allows a beginner to see the differences between a beginner's plan and expert plans. Sharing know-how information is possible by recording, accumulating, and giving titles to what has been noticed in comparing documents. This system can visualize the similarities among documents that interpreted the results of an assessment, and can flexibly change different viewpoints, additionally, can map a user's new document into a two-dimensional document space. We confirmed that these functions were appropriate.
Rendering the effect of labradoescence
Authors: Andrea Weidlich, Alexander Wilkie
Venue: Proceedings of Graphics Interface 2009 (2009)

Labradorescence is a complex optical phenomenon that can be found in certain minerals, such as Labradorite or Spectrolite. Because of their unique colour properties, these minerals are often used as gemstones and decorative objects. Since the phenomenon is strongly orientation dependent, such minerals need a special cut to make the most of their unique type of colourful sheen, which makes it desirable to be able to predict the final appearance of a given stone prior to the cutting process. Also, the peculiar properties of the effect make a believable reproduction with an ad-hoc shader difficult even for normal, non-predictive rendering purposes. We provide a reflectance model for labradorescence that is directly derived from the physical characteristics of such materials. Due to its inherent accuracy, it can be used for predictive rendering purposes, but also for generic rendering applications.
Languages: From Formal to Natural Essays Dedicated to Nissim Francez on the Occasion of His 65th Birthday, 1st edition
Authors: Orna Grumberg, Michael Kaminski, Shmuel Katz, Shuly Wintner
Venue:  (2009)

This Festschrift volume, published in honor of Nissim Francez on the occasion of his 65th birthday, contains 15 papers, written by friends and colleagues, many of whom congregated at a celebratory symposium held on May 24-25, 2009, in Haifa, Israel. The theme of the symposium was Languages: From Formal to Natural, reflecting the focus of Nissim Francez' research career, which started in program verification and the semantics of programming languages and later concentrated on natural languages and computational linguistics. The papers included in this volume cover the entire spectrum of this field of research.
Microsoft Office 2007: Introductory Concepts and Techniques, Windows XP Edition, 1st edition
Authors: Gary B. Shelly, Thomas J. Cashman, Misty E. Vermaat
Venue: Shelly Cashman (2007)

Microsoft Office 2007: Introductory Concepts and Techniques Windows XP Edition provides a project-based, step-by-step approach to teaching the Office 2007 applications.
On subtyping, wildcards, and existential types
Authors: Nicholas Cameron, Sophia Drossopoulou
Venue: Proceedings of the 11th International Workshop on Formal Techniques for Java-like Programs (2009)

Wildcards are an often confusing part of the Java type system: the behaviour of wildcard types is not fully specified by subtyping, due to wildcard capture, and the rules for type checking are often misunderstood. Their very formulation seems somehow 'different' from the rest of the Java type system, which is based on a simple, nominal hierarchy. We investigate subtyping in models for Java with and without generics and wildcards. We separate subclassing from subtyping, unify subtyping for class and wildcard types using existential types, and show that Java wildcards emerge naturally from the combination of inclusion and parametric polymorphism.
Policy teaching through reward function learning
Authors: Haoqi Zhang, David C. Parkes, Yiling Chen
Venue: Proceedings of the tenth ACM conference on Electronic commerce (2009)

Policy teaching considers a Markov Decision Process setting in which an interested party aims to influence an agent's decisions by providing limited incentives. In this paper, we consider the specific objective of inducing a pre-specified desired policy. We examine both the case in which the agent's reward function is known and unknown to the interested party, presenting a linear program for the former case and formulating an active, indirect elicitation method for the latter. We provide conditions for logarithmic convergence, and present a polynomial time algorithm that ensures logarithmic convergence with arbitrarily high probability. We also offer practical elicitation heuristics that can be formulated as linear programs, and demonstrate their effectiveness on a policy teaching problem in a simulated ad-network setting. We extend our methods to handle partial observations and partial target policies, and provide a game-theoretic interpretation of our methods for handling strategic agents.
Starting Out with Java: From Control Structures through Objects, 4th edition
Authors: Tony Gaddis
Venue: Mycodemate Series (2009)

KEY BENEFIT: Gaddis introduces Java with an accessible, step-by-step style that helps beginners understand how to become skilled programmers. KEY TOPICS: Introduction to Computers and Java; Java Fundamentals; Decision Structures; Loops and Files; Methods; A First Look at Classes; A First Look at GUI Applications; Arrays and the ArrayList Class; A Second Look at Classes and Objects; Text Processing and More About Wrapper Clauses; Inheritance; Exceptions and Advanced File I/O; Advanced GUI Applications; Applets and More; Recursion. MARKET: Ideal for beginners to Java programming.
Investigating transactional memory performance on ccNUMA machines
Authors: Ruibo Wang, Kai Lu, Xicheng Lu
Venue: Proceedings of the 18th ACM international symposium on High performance distributed computing (2009)

Most Software Transactional Memory (STM) research has focused on multi-core processors and small SMP machines; limited research has been aimed at the clusters, leaving the area of big SMP machines unexplored. Big SMP machine usually use Non-Uniform Memory Access (NUMA) to unburden the overloading between CPUs and the memory. In this paper, we evaluate several STM implementations on big SMP machine with cache coherent NUMA (ccNUMA) architecture. We found the remote memory access latency is the key factor influencing the STM performance. We also analyze the different design choices of STM. Finally, we conclude a specific design choice to achieve high performance in this domain.
Identification and Frequency Estimation of Inversion Polymorphisms from Haplotype Data
Authors: Suzanne S. Sindi, Benjamin J. Raphael
Venue: Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology (2009)

Structural rearrangements, including copy-number alterations and inversions, are increasingly recognized as an important contributor to human genetic variation. Copy number variants are readily measured via array-based techniques like comparative genomic hybridization, but copy-neutral variants such as inversion polymorphisms remain difficult to identify without whole genome sequencing. We introduce a method to identify inversion polymorphisms and estimate their frequency in a population using readily available single nucleotide polymorphism (SNP) data. Our method uses a probabilistic model to describe a population as a mixture of forward and inverted chromosomes and identifies putative inversions by characteristic differences in haplotype frequencies around inversion breakpoints. On simulated data, our method accurately predicts inversions with frequencies as low as 25% in the population and reliably estimates inversion frequencies over a wide range. On the human HapMap Phase 2 data, we predict between 88 and 142 inversion polymorphisms with frequency ranging from 20 to 92 percent. Many of these correspond to known inversions or have other evidence supporting them, and the predicted inversion frequencies largely agree with the limited information presently available.
Design and dimensioning of an edge router using Markov model
Authors: Partha Bhattacharjee, Goutam Sanyal
Venue: International Journal of Communication Networks and Distributed Systems (2009)

This paper presents the formulation, modelling and analysis of network traffic for the purpose of designing an edge router. Presuming packet arrival in Poisson's process and departure or service time distribution to be exponential, a Markov model has been developed. The stochastic characteristics of the traffic has been monitored and studied over long durations. Traffic data was captured from internet backbone. Different design parameters like buffer capacity, outgoing link speed and various other key parameters have been derived. Additionally, an algorithm has been suggested to manipulate the weights of the queues dynamically in a weighted round robin scheduling, thereby changing the packet departure rate of the flows. The algorithm eventually provides a control over the load factors and the probability of packet drop of the flows as per the need of quality of service and differentiated service.
Unsupervised Learning of Semantic Relations for Molecular Biology Ontologies
Authors: Massimiliano Ciaramita, Aldo Gangemi, Esther Ratsch, Jasmin Šarić, Isabel Rojas
Venue: Proceeding of the 2008 conference on Ontology Learning and Population: Bridging the Gap between Text and Knowledge (2008)

Manual ontology building in the biomedical domain is a work-intensive task requiring the participation of both domain and knowledge representation experts. The representation of biomedical knowledge has been found of great use for biomedical text mining and integration of biomedical data. In this chapter we present an unsupervised method for learning arbitrary semantic relations between ontological concepts in the molecular biology domain. The method uses the GENIA corpus and ontology to learn relations between annotated named-entities by means of several standard natural language processing techniques. An in-depth analysis of the output evaluates the accuracy of the model and its potentials for text mining and ontology building applications. The proposed learning method does not require domain-specific optimization or tuning and can be straightforwardly applied to arbitrary domains, provided the basic processing components exist.
Opportunistic medical monitoring using bluetooth P2P networks
Authors: Dae-Ki Cho, Seung-Hoon Lee, Alexander Chang, Tammara Massey, Chia-Wei Chang, Min-Hsieh Tsai, Majid Sarrafzadeh, Mario Gerla
Venue: Proceedings of the 2008 International Symposium on a World of Wireless, Mobile and Multimedia Networks (2008)

Remote medical monitoring with medical sensors and wireless communications has recently gained attention for the potential savings and improved quality in patient health-care. Currently, many mobile wireless medical infrastructures connect to the Internet in a point-to-point fashion, such as the cellular network. However, our research investigates new models for remote patient care that exploit P2P networking among patients and healthcare providers (nurses, doctors, emergency personnel). In this paper, we identify several medical applications based on P2P Health Networking focusing on two specific scenarios where nurses and patients are both equipped with Bluetooth devices. Nurses opportunistically collect, share and upload data in a P2P fashion. During an emergency, the nearest nurse is alerted via Bluetooth Enhanced Inquiry Response mechanism. The simulation and test-bed experimentation demonstrate that Bluetooth P2P networking is both feasible and cost-effective in remote medical monitoring.