ppxscal/embedding_network huggingface dataset:
Parallel execution time prediction of the multitask parallel programs
Authors: Rongteng Wu, Jizhou Sun, Jinyan Chen
Venue: Performance Evaluation (2008)

A critical problem of predicting the execution time of parallel programs is computing the maximum execution time of tasks involved in the parallel computation. For a parallel composition of n tasks, distribution information of execution time of the constituent task is crucial to accurately predicting mean, variance and even distribution of execution time of the composition of tasks when the execution time of them is stochastic. This paper presents a method of predicting the maximum parallel execution time of n constituent tasks, each of which has independent, identically distributed random execution time. First, execution time of any constituent task as a random variable is transformed into standard normal variable, or approximately so, by using Johnson distributions. Then the distribution and moments of the maximum parallel execution time are obtained after appropriate Johnson transformation is chosen and its corresponding parameters are determined. The experiment on synthetic distributions such as exponential distribution shows that most relative errors of the first four moments are near the 0.1%. And the experiment on some practical applications shows that the relative errors of the first four moments are below 0.1%. The computing complexity of our algorithm, as a function of the number n of the tasks or processors, is O(n), and even O(1) while using approximate distribution, such as Gumbel distribution.
Iterative identification of fault-prone binaries using in-process metrics
Authors: Lucas Layman, Gunnar Kudrjavets, Nachiappan Nagappan
Venue: Proceedings of the Second ACM-IEEE international symposium on Empirical software engineering and measurement (2008)

Code churn, the amount of code change taking place within a software unit over time, has been correlated with fault-proneness in software systems. We investigate the use of code churn and static metrics collected at regular time intervals during the development cycle to predict faults in an iterative, in-process manner. We collected 159 churn and structure metrics from six, four-month snapshots of a 1 million LOC Microsoft product. The number of software faults fixed during each period is recorded per binary module. Using stepwise logistic regression, we create a prediction model to identify fault-prone binaries using three parameters: code churn (the number of new and changed blocks); class Fan In and class Fan Out (normalized by lines of code). The iteratively-built model is 80.0% accurate at predicting fault-prone and non-fault-prone binaries. These fault-prediction models have the advantage of allowing the engineers to observe how their fault-prediction profile evolves over time.
A Semantic-Oriented Platform for Performance Monitoring of Distributed Java Applications
Authors: Włodzimierz Funika, Piotr Godowski, Piotr Pęgiel
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

In this paper we present an approach to semantic performance analysis in on---line monitoring systems. We have designed a novel monitoring system which uses ontological description for all concepts exploited in the distributed systems monitoring. We introduce a complete implementation of a robust system with semantics, which is not biased to any kind of the underlying "physical" monitoring system, giving the end user the power of intelligent monitoring features like automatic metrics selection and collaborative work.
Embedding Computational Intelligence in Pervasive Spaces
Authors: Hani Hagras
Venue: IEEE Pervasive Computing (2007)

This column shows how we might embed AI mechanisms in pervasive spaces to produce more intelligent, adaptive, and convenient environments. It concentrates on computational intelligence--in particular, fuzzy systems and neural networks--because this emerging AI domain covers most of the requirements for this task.
Analytical Evaluation of Clients' Failures in a LVoD Architecture Based on P2P and Multicast Paradigms
Authors: Rodrigo Godoi, Xiaoyuan Yang, Porfidio Hernández
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Peer-to-peer (P2P), multicast or hybrid paradigms are used nowadays as the main strategies in order to improve performance and scalability of Large Video on Demand (LVoD) systems. Using P2P and multicast supposes facing situations like how often peers connect and disconnect from the system or reconfiguration of multicast delivery trees. Therefore, such distributed designs require a complex control mechanism that can involve huge volume of network messages as well as computational requirements. Nevertheless, the control schemes are neglected in the LVoD design, which is rather focused on the application level logic for video data transmission. In this paper we analyze extensively, by mean of analytical models, the requirement of the control subsystem of a P2P multicast architecture named PCM/MCDB. In our analysis, we consider different designs schemes and the results show an increasing importance of the control module in the LVoD infrastructure.
Adopting organizational virtualization in B2B firms: An empirical study in Singapore
Authors: Chunhui Liu, Choon-Ling Sia, Kwok-Kee Wei
Venue: Information and Management (2008)

We empirically tested a parsimonious model that incorporates cost-benefit analysis/transaction cost theory, institutional theory, and organizational capability-based theory to predict organizational adoption of IT-facilitated virtualization in an Asian context. Virtualization implies the use of IT and communication technology by organizations in managing their interactions and key business operations with stakeholders, such as customers, suppliers and employees. Our research extends existing literature by using organizational structure adoption theories. The study should provide insights into the salient adoption issues of Asian firms. A survey was conducted of B2B organizations in Singapore. Results indicated that an increase in the level of net perceived benefits, external influences, and organizational capabilities had a positive effect on organizational decision makers' intention to use virtualization. In particular, external influences were found to be the most important antecedents of intention to adopt virtualization in B2B organizations in Singapore.
Acquisition of OWL DL Axioms from Lexical Resources
Authors: Johanna Völker, Pascal Hitzler, Philipp Cimiano
Venue: Proceedings of the 4th European conference on The Semantic Web: Research and Applications (2007)

State-of-the-art research on automated learning of ontologies from text currently focuses on inexpressive ontologies. The acquisition of complex axioms involving logical connectives, role restrictions, and other expressive features of the Web Ontology Language OWL remains largely unexplored. In this paper, we present a method and implementation for enriching inexpressive OWL ontologies with expressive axioms which is based on a deep syntactic analysis of natural language definitions. We argue that it can serve as a core for a semi-automatic ontology engineering process supported by a methodology that integrates methods for both ontology learning and evaluation. The feasibility of our approach is demonstrated by generating complex class descriptions from Wikipedia definitions and from a fishery glossary provided by the Food and Agriculture Organization of the United Nations.
Formal verification of asynchronous systems using decision diagrams
Authors: Gianfranco Ciardo
Venue:  (2008)

Benefiting from decades of research, powerful techniques such as decision-diagram-based and SAT-based techniques have enabled formal verification to be widely used in design industry. Most formal verification research effort has been focused on synchronous systems, as the majority of digital designs today are synchronous. However, as synchronous design methodology is hitting its fundamental limitations, such as clock skew and high-power consumption, asynchronous design methodology can solve these problems naturally and has attracted much attention from both academia and industry. This thesis presents several effective and scalable decision-diagram-based formal verification techniques for asynchronous systems. By exploiting the characteristics of decision diagrams and the structural properties of asynchronous systems, we proposed a new variant of decision diagrams to exploit the event locality of asynchronous systems. With this new encoding technique, we presented a new Saturation-based reachability analysis algorithm in [27] which is applicable to general asynchronous systems and achieves significant performance improvements over existing approaches. Inspired by the success of SAT-based bounded model checking approaches, we proposed several advanced bounded reachability checking approaches using decision diagrams in [94], resulting in Bounded Saturation. Bounded Saturation approaches utilize our Saturation algorithm to compute bounded state spaces by employing different variants of decision diagrams: MDDs, EDDs, and ADDs, and empirically are shown to be very competitive with the existing SAT-based approaches. To further improve the scalability of the symbolic approaches, we proposed an automatic chaining heuristic in [16] to reduce the number of iterations required for symbolic state-space generation and model-checking. Decision diagram variable ordering is well-known to be critical for any decision diagram based approaches. In [22], we presented a novel static ordering heuristic that exploits event locality and utilizes functional dependencies in asynchronous systems.
The probability of error for frequency hopping spread spectrum in wireless communication using MFSK modulations
Authors: Othman Sidek, Abid Yahya
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

The paper is focus on the performance of fast frequency hopped spread spectrum by using M-ary frequency shift keying (MFSK) modulations. In fast FH systems, the frequency-hop rate Rh is some multiple of the symbol rate. Basically, each (M-ary) symbol interval is subdivided into N subintervals, which are called chips and one of M frequencies is transmitted in each subinterval. The probability of error for noncoherent detection of binary FSK for each hop with p = 0.01 is discussed in this paper.
Market equilibrium via a primal--dual algorithm for a convex program
Authors: Nikhil R. Devanur, Christos H. Papadimitriou, Amin Saberi, Vijay V. Vazirani
Venue: Journal of the ACM (JACM) (2008)

We give the first polynomial time algorithm for exactly computing an equilibrium for the linear utilities case of the market model defined by Fisher. Our algorithm uses the primal--dual paradigm in the enhanced setting of KKT conditions and convex programs. We pinpoint the added difficulty raised by this setting and the manner in which our algorithm circumvents it.
Clinical Performance of Breast Tomosynthesis as a Function of Radiologist Experience Level
Authors: Andrew P. Smith, Elizabeth A. Rafferty, Loren Niklason
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

This study reports the performance of breast tomosynthesis (3D images) combined with digital mammography (2D images), compared to digital mammography alone, as a function of the experience of the radiologist. In this trial, twelve readers analyzed 316 image sets, giving BIRADS (and other) scores first for the digital mammograms, and subsequently for the combined datasets of tomosynthesis and digital mammograms. Clinical performance was measured using two metrics: area under the ROC curve (AUROC) and recall rate, and was analyzed as a function of the experience level. The study found that all radiologists AUROC improved when using 3D+2D compared to 2D, with no correlation with experience level, increasing by 0.077 ± 0.058 (mean ± 1 standard deviation) for the 5 least experienced and increasing by 0.078 ± 0.029 for the 5 most experienced. Similarly, the use of 3D+2D compared to 2D imaging showed a mean decrease in recall rate of 39.2% for the most experienced and a decrease of 39.6% for the least experienced, again with no correlation found with experience level. In summary, radiologists with a range of experience demonstrated improved performance using tomosynthesis in combination with digital mammography (3D+2D), as measured using recall rate reduction and AUROC metrics.
Studying Model Ambiguity in a Language ITS
Authors: Brent Martin, Amanda Nicholas
Venue: Proceedings of the 11th international conference on User Modeling (2007)

Ambiguity is a well-known problem in student modelling, and in user modelling in general. In this paper we present the results of an experiment in the domain of German adjectives. We trialled a modified student interface that gathers more data during problem solving by requiring the student to perform a related subtask. There is evidence that the students who performed the subtask outperformed the control group on a post-test despite the extra task slowing them down, suggesting the extra effort required by the students to overcome ambiguity was worth the intervention.
MIT Lincoln Laboratory Multimodal Person Identification System in the CLEAR 2007 Evaluation
Authors: Kevin Brady
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

A description of the MIT Lincoln Laboratory system used in the person identification task of the recent CLEAR 2007 Evaluation is documented in this paper. This task is broken into audio, visual, and multimodal subtasks. The audio identification system utilizes both a GMM and a SVM subsystem, while the visual (face) identification system utilizes an appearance-based [Kernel] approach for identification. The audio channels, originating from a microphone array, were preprocessed with beamforming and noise preprocessing.
Knowledge-Based Modeling and Simulation of Diseases with Highly Differentiated Clinical Manifestations
Authors: Marjorie Mcshane, Sergei Nirenburg, Stephen Beale, Bruce Jarrell, George Fantry
Venue: Proceedings of the 11th conference on Artificial Intelligence in Medicine (2007)

This paper presents the cognitive model of gastroesophageal reflux disease (GERD) developed for the Maryland Virtual Patient simulation and mentoring environment. GERD represents a class of diseases that have a large number of clinical manifestations. Our model at once manages that complexity while offering robust automatic function in response to open-ended user actions. This ontologically grounded model is largely based on script-oriented representations of causal chains reflecting the actual physiological processes in virtual patients. A detailed description of the GERD model is presented along with a high-level description of the environment for which it was developed.
Unrestricted pure call-by-value recursion
Authors: Johan Nordlander, Magnus Carlsson, Andy J. Gill
Venue: Proceedings of the 2008 ACM SIGPLAN workshop on ML (2008)

Call-by-value languages commonly restrict recursive definitions by only allowing functions and syntactically explicit values in the right-hand sides. As a consequence, some very appealing programming patterns that work well in lazy functional languages are hard to apply in a call-by-value setting, even though they might not be using laziness for any other purpose than to enable the desired form of recursion. In this paper we present an operational semantics as well as a straightforward implementation technique for unrestricted recursion under pure call-by-value. On that basis we are able to demonstrate that highly recursive programming idioms such as combinator-based parsing are indeed compatible with call-by-value evaluation.
Keyphrase Extraction from Chinese News Web Pages Based on Semantic Relations
Authors: Fei Xie, Xindong Wu, Xue-Gang Hu, Fei-Yue Wang
Venue: Proceedings of the IEEE ISI 2008 PAISI, PACCF, and SOCO international workshops on Intelligence and Security Informatics (2008)

Keyphrases are very useful for saving time on browsing through the news web pages. A new keyphrase extraction method from Chinese news web pages based on semantic relations is presented in this paper. Semantic relations between phrases are analyzed, and a lexical chain is used to construct a semantic relation graph. Keyphrases are extracted and a semantic link graph is built on the lexical chains. News web pages with core hints are selected from www.163.com to test our method. The experimental results show that the proposed method substantially outperforms the method based on term frequency, especially when the number of keyphrases extracted is 3 - the precision is improved by 26.97 percent, and the recall is improved by 20.93 percent.
A Network-Based Framework for Collaborative Development and Performance of Digital Musical Instruments
Authors: Joseph Malloch, Stephen Sinclair, Marcelo M. Wanderley
Venue: Computer Music Modeling and Retrieval. Sense of Sounds: 4th International Symposium, CMMR 2007, Copenhagen, Denmark, August 27-31, 2007. Revised Papers (2008)

This paper describes the design and implementation of a framework designed to aid collaborative development of a digital musical instrument mapping layer. The goal was to create a system that allows mapping between controller and sound parameters without requiring a high level of technical knowledge, and which needs minimal manual intervention for tasks such as configuring the network and assigning identifiers to devices. Ease of implementation was also considered, to encourage future developers of devices to adopt a compatible protocol.System development included the design of a decentralized network for the management of peer-to-peer data connections using OpenSound Control. Example implementations were constructed using several different programming languages and environments. A graphical user interface for dynamically creating, modifying, and destroying mappings between control data streams and synthesis parameters is also presented.
GREAT: UML transformation tool for porting middleware applications
Authors: Alexander Christoph, Matthias M. Müller
Venue: Science of Computer Programming (2008)

Design and maintenance of enterprize applications is complicated due to dependencies on technical requirements of the middleware framework. Especially, porting enterprise applications to another middleware layer or even new versions thereof requires a lot of handiwork and coding, since abstraction-, transformation-, and refinement steps have to be performed. Transformations should be assisted by a tool set which facilitates the migration process from one to another middleware platform. This paper presents GREAT, a rule-based transformation framework which facilitates transformations among models on the same or different abstraction levels. The feasibility of GREAT is shown by the transformation of a real world application conforming to EJB standard 1.1 into a version which complies to EJB standard 2.0.
(DSP-FPGA) based multiple motors control system
Authors: Omar Al-Ayasrah
Venue: Proceedings of the 7th WSEAS International Conference on Applied Computer and Applied Computational Science (2008)

There are so many applications that have more than one motor t o be controlled dependently or independently at the same time with high performance low cost control system. This paper presents a Multiple Motors Control System with high performance and low cost for a variety of applications. The proposed technique is DSP and FPGA based system. An external FPGA structural design is interfaced with the PWM Generation Unit of the DSP board for the use of Multiple Motors Control using one DSP Processor, like the Mixed Signals ADSP-21992, with one PWM Generation Unit to reduc e the overall cost and complexity of the multiple motors control system. Simulation and experimental results are achieved successfully and introduced in this paper.
Forecast Model of Impact of Meteorological Factors on Coronary Artery Disease Patients
Authors: Arvydas Martinkėnas, Vytautas Kaminskas, Giedrius Varoneckas
Venue: Informatica (2007)

A medical-meteorological weather assessment using hybrid spatial classification of synoptic and meteorological data was done. Empirical models for assessment as well as for forecast of medical-meteorological weather type at the seaside climatic zone in Palanga were developed. It was based on the data of meteofactors (atmospheric pressure, relative humidity, temperature, oxygen density in atmosphere, cyclone fronts, etc.) as well as on the occurrence of meteotropical reactions of cardiovascular function collected during 8-year period. The empirical models allow objectively assess and forecast 3 types of medical-meteorological weather types: favourable, unfavourable and very unfavourable weather. Classification model assessed favourable weather type in 56.1%, unfavourable in 31.7% and very unfavourable in 12.2%, while forecast was of favourable weather type in 52.4%, unfavourable in 46% and very unfavourable in 1.6% of days. Developed model enables more precise weather estimation and forecast meteotropical reactions promoting development of preventive measures of cardiovascular complications for reduction of negative weather impact on health in coronary artery diseases patients.
Analysis of Local Route Maintenance for Ad Hoc Network
Authors: Shaobin Cai, Nianmin Yao, Wenbin Yao, Yong Li, Guochang Gu
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

In ad hoc network, most link ailure recoveries can be localized to a small region along the previous route. However, the theory is not proved by mathematic analysis and simulations. In this paper, we analyze it by mathematical analysis and by simulations.
Cramer-Shoup Satisfies a Stronger Plaintext Awareness under a Weaker Assumption
Authors: Isamu Teranishi, Wakaha Ogata
Venue: Proceedings of the 6th international conference on Security and Cryptography for Networks (2008)

In the seminal paper of Eurocrypt 2006, Dent defined a new assumption, simulatability, and showed that the well-known Cramer-Shoup public-key encryption scheme satisfied the weakest version of the plaintext awareness, the computational plaintext awareness, under the simulatability assumption, the DDH assumption, the DHK assumption, and the collision resistance of the hash function. However, a tricky aspect of the computational plaintext awareness was later shown. Moreover, the definition of the simulatability is elaborated. In this paper, we show that the Cramer-Shoup scheme satisfies a stronger variant of the plaintext awareness, the statistical plaintext awareness, under a weaker and simpler assumption than the simulatability. In particular, we show the statistical PA2-ness of the Cramer-Shoup scheme under computational assumptions.
ParaMT: A Paraphraser for Machine Translation
Authors: Anabela Barreiro
Venue: Proceedings of the 8th international conference on Computational Processing of the Portuguese Language (2008)

In this paper we present ParaMT, a bilingual/multilingual paraphraser to be applied in machine translation. We select paraphrases of support verb constructions and use the NooJ linguistic environment to formalize and generate translation equivalences through the use of dictionary and local grammars with syntactic and semantic content. Our research shows that linguistic paraphrasal knowledge constitutes a key element in conversion of source language into controlled language text that presents more successful translation results.