ppxscal/embedding_network huggingface dataset:
Performance Studies on KBANN
Authors: R. P. Jagadeesh, Chandra Bose, G. Nagaraja
Venue: Proceedings of the Fourth International Conference on Hybrid Intelligent Systems (2004)

Hybrid models combining the analytical (rulebased) and connectionist (artificial neural network (ANN)) paradigms are called Knowledge Based Neural Networks (KBNN). The Knowledge Based Artificial Neural Network (KBANN) is one such model that makes use of the domain theory represented as propositional rules and training examples. In this article, we analyze the performance of KBANN and suggest some ideas of improving its capabilities. A study on the effect of inductive bias on KBANN, use of adaptive learning algorithms instead of the standard backpropagation to improve the training times and the use of regularization methods for improving generalization performance is presented. It is shown that for better performance, the initial weight assignment to links obtained by domain theory varies with the domain and the performance of KBANN is improved by using regularization methods like the weight decay along with Rprop training algorithm instead of the standard backpropagation.
Forcing unbalanced complete bipartite minors
Authors: Daniela Kühn, Deryk Osthus
Venue: European Journal of Combinatorics (2005)

Myers conjectured that for every integer s there exists a positive constant C such that for all integers t every graph of average degree at least Ct contains a Ks,t minor. We prove the following stronger result: for every 0 < ε < 10-16 there exists a number t0 = t0(ε) such that for all integers t ≥ t0 and s ≤ ε7t/log t every graph of average degree at least (1 + ε)t contains a Ks + K-t minor (and thus also a Ks,t minor). The bounds are essentially the best possible.
Mapping the degree of match between B2B interactions and inter-organizational systems: uptake of IOS in two Australian cooperatives
Authors: Maarten Bekking, Ariane von Raesfeld, Shirley Gregor
Venue: Proceedings of the 6th international conference on Electronic commerce (2004)

In this paper we will advance a perspective that links business network analysis to inter-organizational systems (IOS) uptake, starting with an analytic framework to characterize both different types of electronic business to business interactions (via the web) as well as the network of business relationships in which they are used. In order to see whether inter-organizational IT systems and business networks (mis)match they are compared on two dimensions: 'mode of interaction' (relational versus transactional) and 'nature of coordination' (emergent versus directive). The study analyses two Australian agricultural cooperatives 'Capgrains' and 'Bluegum'. The transactional focus and directive control of Capgrains' online ordering system did not match with the relational interaction and emergent coordination that was common in their network of business relationships, resulting in a mismatch and low level of use of the system. The Bluegum's group communication system much better matched with the business relationships in the cooperative and higher use of the IOS. Indicating a positive relation between match and uptake of the IOS.
A Compiler and Runtime Infrastructure for Automatic Program Distribution
Authors: Roxana E. Diaconescu, Lei Wang, Zachary Mouri, Matt Chu
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01 (2005)

This paper presents the design and the implementation of a compiler and runtime infrastructure for automatic program distribution.We are building a research infrastructure that enables experimentation with various program partitioning and mapping strategies and the study of automatic distribution's effect on resource consumption (e.g., CPU, memory, communication). Since many optimization techniques are faced with conflicting optimization targets (e.g., memory and communication), we believe that it is important to be able to study their interaction. We present a set of techniques that enable flexible resource modeling and program distribution. These are: dependence analysis, weighted graph partitioning, code and communication generation, and profiling. We have developed these ideas in the context of the Java language. We present in detail the design and implementation of each of the techniques as part of our compiler and runtime infrastructure. Then, we evaluate our design and present preliminary experimental data for each component, as well as for the entire system.
Simulating Large Wireless Sensor Networks Using Cellular Automata
Authors: Renan O. Cunha, Aloizio P. Silva, Antonio A. F. Loureiro, Linnyer B. Ruiz
Venue: Proceedings of the 38th annual Symposium on Simulation (2005)

A wireless sensor network is a special kind of ad hoc network where the nodes can sense, actuate, compute and communicate with each other using point-to-point multi-hop communication. Sensor networks can be used in a wide range of applications, such as environmental monitoring and industrial applications. Despite their potential applications, such networks have particular features imposed by resource restrictions, such as low computational power, reduced bandwidth and specially limited power source. Nowadays, real wireless sensor networks infrastructures are still very expensive. Therefore, most of the evaluations of new protocols are being made through simulation tools. The objective of this work is to verify the applicability of using cellular automata to simulate some aspects of sensor networks. A simulator has been developed to evaluate an algorithm for a very common problem in sensor networks: the topology control. The solution presented is based on the geographical position and the operational states of the sensor nodes. The obtained results indicate that cellular automata can be used with success to simulate large wireless sensor networks.
An in-depth look at computer performance growth
Authors: Magnus Ekman, Fredrik Warg, Jim Nilsson
Venue: ACM SIGARCH Computer Architecture News (2005)

It is a common belief that computer performance growth is over 50% annually, or that performance doubles every 18-20 months. By analyzing publicly available results from the SPEC integer (CINT) benchmark suites, we conclude that this was true between 1985 and 1996 -- the early years of the RISC paradigm.During the last 7.5 years (1996-2004), however, performance growth has slowed down to 41%, with signs of a continuing decline. Meanwhile, clock frequency has improved with about 29% annually. The improvement in clock frequency was enabled both by an annual device speed scaling of 20% as well as by longer pipelines with a lower gate-depth in each stage. This paper takes a fresh look at -- and tries to remove the confusion about -- performance scaling that exists in the computer architecture community.
Notes on max flow time minimization with controllable processing times
Authors: Monaldo Mastrolilli
Venue: Computing (2003)

In a scheduling problem with controllable processing times the job processing time can be compressed through incurring an additional cost. We consider the identical parallel machines max flow time minimization problem with controllable processing times. We address the preemptive and non-preemptive version of the problem. For the preemptive case, a linear programming formulation is presented which solves the problem optimally in polynomial time. For the non-preemptive problem it is shown that the First In First Out (FIFO) heuristic has a tight worst-case performance of 3 - 2/m, when jobs processing times and costs are set as in some optimal preemptive schedule.
Impact of Failure on Interconnection Networks for Large Storage Systems
Authors: Qin Xin, Ethan L. Miller, Thomas J. E. Schwarz, Darrell D. E. Long
Venue: Proceedings of the 22nd IEEE / 13th NASA Goddard Conference on Mass Storage Systems and Technologies (2005)

Recent advances in large-capacity, low-cost storage devices have led to active research in design of large-scale storage systems built from commodity devices for supercomputing applications. Such storage systems, composed of thousands of storage devices, are required to provide high system bandwidth and petabyte-scale data storage. A robust network interconnection is essential to achieve high bandwidth, low latency, and reliable delivery during data transfers. However, failures, such as temporary link outages and node crashes, are inevitable. We discuss the impact of potential failures on network interconnections in very large-scale storage systems and analyze the trade-offs among several storage network topologies by simulations. Our results suggest that a good interconnect topology be essential to fault-tolerance of a petabyte-scale storage system.
Vulnerability Profile for Linux
Authors: Ratsameetip Wita, Yunyong Teng-Amnuay
Venue: Proceedings of the 19th International Conference on Advanced Information Networking and Applications - Volume 1 (2005)

A system with efficient security tools is not secured if its operating system is vulnerable. Various security enhancements for operating systems provide different security levels and profiles. Administrators have to choose the appropriate level or profile of protection for their systems. Our work attempts to systematically quantify the level of vulnerability for operating systems with a profiling scheme based on the severity of the attack as listed in the CVE. Linux, due to its open source nature, is used as a case study. Vanilla Linux, Linux with hardening, and Linux with LSM enhancement, are profiled and compared.
An Empirical Performance Comparison of Machine Learning Methods for Spam E-Mail Categorization
Authors: Chih-Chin Lai, Ming-Chi Tsai
Venue: Proceedings of the Fourth International Conference on Hybrid Intelligent Systems (2004)

The increasing volume of unsolicited bulk e-mail (also known as spam) has generated a need for reliable anti-spam filters. Using a classifier based on machine learning techniques to automatically filter out spam e-mail has drawn many researchers' attention. In this paper, we review some of relevant ideas and do a set of systematic experiments on e-mail categorization, which has been conducted with four machine learning algorithms applied to different parts of e-mail. Experimental results reveal that the header of e-mail provides very useful information for all the machine learning algorithms considered to detect spam e-mail.
Enabling proteomics: the need for an extendable &lsquo;workbench&rsquo; for user-configurable solutions: Conference Reviews
Authors: Robert J. Beynon
Venue: Comparative and Functional Genomics (2004)

Proteomics has the capability to generate overwhelming quantities of data in relatively short timescales, and it is not uncommon to see experimenters investing substantially more time in data analysis than in data gathering. Although several sophisticated tools for data reduction and analysis are available, they lack the flexibility to cope with increasingly innovative experimental strategies and new database resources that encode both qualitative and quantitative data. I will outline a specification of a flexible proteomics tool that could address many current bottlenecks and deficiencies. Copyright &copy; 2004 John Wiley & Sons, Ltd.
Context-awareness, privacy and mobile access: a web semantic and multiagent approach
Authors: Fabien L. Gandon, Norman M. Sadeh
Venue: Proceedings of the 1st French-speaking conference on Mobility and ubiquity computing (2004)

We give an overview of the work achieved in myCampus, an open environment relying on context-awareness to assist mobile accesses to services available on the intranet of a campus, while enforcing privacy preferences of the users.
Making a Game of Network Security
Authors: Marc Dougherty
Venue: Proceedings of the 18th USENIX conference on System administration (2004)

This paper describes our experiences in the design and implementation of a network for security training exercises, and one such exercise. The network described herein is flexible, and could be used for a wide variety of training exercises. Organizations of all sizes can use this type of exercise to train new personnel or keep existing staff at their best. In addition to the training benefits, these exercises can also be highly entertaining. The designs described here are intended to assist others in the construction of similar networks, and additional training scenarios.
The interrelationship and effect of culture and risk communication in setting internet banking security goals
Authors: Ioannis V. Koskosas, Ray J. Paul
Venue: Proceedings of the 6th international conference on Electronic commerce (2004)

The aim of this research is to investigate information systems security in the context of internet banking. In doing so, it adopts a socio-organizational approach to the subject matter by investigating the interrelationship between culture and risk communication within information technology groups and their possible effect on the level of security goal setting. The research explores and describes different socio-organizational perspectives and seeks to demonstrate the importance of culture and risk communication in setting efficiently internet banking goals within the broader context of information systems security management. To this end, it gives also an overview of different goal setting procedures within the IT departments of three financial institutions.
System challenges for ubiquitous & pervasive computing
Authors: Roy Want, Trevor Pering
Venue: Proceedings of the 27th international conference on Software engineering (2005)

The terms Ubiquitous and Pervasive computing were first coined at the beginning of the 90's, by Xerox PARC and IBM respectively, and capture the realization that the computing focus was going to change from the PC to a more distributed, mobile and embedded form of computing. Furthermore, it was predicted by some researchers that the true value of embedded computing would come from the orchestration of the various computational components into a much richer and adaptable system than had previously been possible. Now some fifteen years later, we have made progress towards these aims. The Hardware platforms used to implement these systems encapsulate significant computation capability in a small form-factor, consume little power and have a small cost. However, the system software capabilities have not advanced at a pace that can take full advantage of this infrastructure. This paper will describe where software and hardware have combined to enable ubiquitous computing, where these systems have limitations and where the biggest challenges still remain.
Evolutionary Artificial Neural Network Optimisation in Financial Engineering
Authors: Serge Hayward
Venue: Proceedings of the Fourth International Conference on Hybrid Intelligent Systems (2004)

Analytical examination of loss functions' families demonstrates that investors' utilitymaximisation is determined by their risk attitude. In computational settings, stock traders' fitness is assessed in response to a slow-step increase in the value of the risk aversion coefficient. The experiment rejects the claims that the accuracy of the forecast does not depend upon which error-criteria are used and none of them is related to the profitability of the forecast. Profitability of networks trained with L6 loss function appeared to be statistically significant and stable, although links between loss functions and accuracy of forecasts were less conclusive.
Optimal Statistical Model for Forecasting Ozone
Authors: M. Abdollahian, R. Foroughi
Venue: Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume I - Volume 01 (2005)

The objective of this paper is to apply time series analysis to Ozone data in order to obtain the optimal forecasting model . Different ARMA models are fitted to the Ozone data and the best fitted model, ARMA(20,2), is found to produce the best predictions withMAPE = 42%. Applying simple exponential smoothing to the time series, however, results in even higher accuracy for predictions. This leads us to believe that in certain cases depending on the characteristics of the time series, naïve methods of forecasting may produce more accurate results.
Markov Chain Correlation Based Clustering of Gene Expression Data
Authors: Youping Deng, Venkatachalam Chokalingam, Chaoyang Zhang
Venue: Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume II - Volume 02 (2005)

An efficient Markov chain correlation based clustering method (MCC) has been proposed for clustering gene expression data. The gene expression data is first normalized and Markov chains (MC) are constructed from the dynamics of the gene expressions, in which the behavior of the genes at each step of the experiment can be taken into account. Based on the correlation of one-step Markov chain transition probabilities, an agglomerative method is employed to group the series that have similar behavior at each point. The proposed MCC clustering method has been applied to four gene expression datasets to obtain a number of clusters. The results show that the MCC method outperforms the commonly used K-means method and produces clusters that are more meaningful in terms of the similarity of the grouped genes. Another advantage of the proposed method over the existing clustering methods is that the knowledge of the group number is not required.
Code-Size Minimization in Multiprocessor Real-Time Systems
Authors: Sanjoy Baruah, Nathan Fisher
Venue: Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Workshop 2 - Volume 03 (2005)

Program code size is a critical factor in determining the manufacturing cost of many embedded systems, particularly those aimed at the extremely cost-conscious consumer market. However, the focus of most prior theoretical research on partitioning algorithms for real-time multiprocessor platforms has been on ensuring that the cumulative computing requirements of the tasks assigned to each processor does not exceed the processor's computing capacity. We consider the problem of task partitioning in multiprocessor platforms in order to minimize the total code size, in application systems in which there may be several different implementations of each task available, with each implementation having different code sizes and different computing requirements. We prove that the general problem is intractable, and present polynomial-time algorithms for solving (well-defined) special cases of the general problem.
Making RDF presentable: integrated global and local semantic Web browsing
Authors: Lloyd Rutledge, Jacco van Ossenbruggen, Lynda Hardman
Venue: Proceedings of the 14th international conference on World Wide Web (2005)

This paper discusses generating document structure from annotated media repositories in a domain-independent manner. This approaches the vision of a universal RDF browser. We start by applying the search-and-browse paradigm established for the WWW to RDF presentation. Furthermore, this paper adds to this paradigm the clustering-based derivation of document structure from search returns, providing simple but domain-independent hypermedia generation from RDF stores. While such generated presentations hardly meet the standards of those written by humans, they provide quick access to media repositories when the required document has not yet been written. The resulting system allows a user to specify a topic for which it generates a hypermedia document providing guided navigation through virtually any RDF repository. The impact for content providers is that as soon as one adds new media items and their annotations to a repository, they become immediately available for automatic integration into subsequently requested presentations.
Performance evaluation of Data Distribution Management strategies: Research Articles
Authors: Azzedine Boukerche, Caron Dzermajko
Venue: Concurrency and Computation: Practice Experience (2004)

Data Distribution Management (DDM) is a High Level Architecture&#x002F;Run-Time Infrastructure (HLA&#x002F;RTI) service that manages the distribution of state updates and interaction information in large-scale distributed simulations and limits and controls the volume of data exchanged during the simulation.In this paper, we describe a mini-RTI framework that we have developed in an effort to determine the most efficient model for applying the DDM service and the limitations of the scalability of various DDM methods. We study and compare the performance of the following five DDM strategies: two variations of the fixed-based method, two variations of the dynamics grid-based scheme and the region-based method. Due to a lack of accepted benchmarks, we also propose a variety of workloads and scenarios, which we hope will become a standards benchmark within the distributed simulation communities. Copyright &copy; 2004 John Wiley & Sons, Ltd.
Interconnect accelerating techniques for sub- 100-nm gigascale systems
Authors: Hong-Yi Huang, Shih-Lun Chen
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2004)

This work describes new circuits called capacitor coupling trigger and capacitor coupling accelerator (CCA) circuits used to reduce the long interconnect RC delay in sub-100-nm processes. The proposed circuits use capacitors to split the output driving paths to eliminate the short-circuit current and thus improve the signal transition time. Besides, the capacitor coupling technique is applied to adjust the gate threshold voltage of the proposed circuits and isolate the input signal from the output driving transistors. The proposed circuits are faster than the prior circuits. Furthermore, the CCA can be applied to bi-directional interface, multiports bus, field-programmable gate array interconnections, and complex dynamic logic circuits.
An infrastructure for development of object-oriented, multi-level configuration management services
Authors: Tien N. Nguyen, Ethan V. Munson, John T. Boyland, Cheng Thao
Venue: Proceedings of the 27th international conference on Software engineering (2005)

In an integrated development environment, the ability to manage the evolution of a software system in terms of logical abstractions, compositions, and their interrelations is crucial to successful software development. This paper presents a novel framework and infrastructure, Molhado, upon which to build object-oriented software configuration management (SCM) services in a SCM-centered integrated development environment. Key contributions of this paper include a product versioning model, an extensible, logical, and object-oriented system model, and a reusable product versioning SCM infrastructure, that allow new types of objects to be implemented as extensions of the system model's basic entities. Versions and configurations of objects are managed at different levels of abstraction and granularity. A new SCM-centered editing environment or development environment for a specific development paradigm can be rapidly realized by re-using Molhado's infrastructure and implementing new object types and their associated tools. This paper also demonstrates our approach in creating prototypes of SCM-centered development environments for different paradigms.
RDF Aggregate Queries and Views
Authors: Edward Hung, Yu Deng, V. S. Subrahmanian
Venue: Proceedings of the 21st International Conference on Data Engineering (2005)

Resource Description Framework (RDF) is a rapidly expanding web standard. RDF databases attempt to track the massive amounts of web data and services available. In this paper, we study the problem of aggregate queries. We develop an algorithm to compute answers to aggregate queries over RDF databases and algorithms to maintain views involving those aggregates. Though RDF data can be stored in a standard relational DBMS (and hence we can execute standard relational aggregate queries and view maintenance methods on them), we show experimentally that our algorithms that operate directly on the RDF representation exhibit significantly superior performance.