ppxscal/embedding_network huggingface dataset:
Working Today on Tomorrow's Storage Technology
Authors: George Lawton
Venue: Computer (2006)

Disk-drive manufacturers are transitioning to perpendicular storage techniques, which provide modestly improved capacity with relatively slight changes to current production processes.
A case study in meta-simulation design and performance analysis for large-scale networks
Authors: David Bauer, Garrett Yaun, Christopher D. Carothers, Murat Yuksel, Shivkumar Kalyanaraman
Venue: Proceedings of the 36th conference on Winter simulation (2004)

Simulation and emulation techniques are fundamental to aid the process of large-scale protocol design and network operations. However, the results from these techniques are often view with a great deal of skepticism from the networking community. Criticisms come in two flavors: (i) the study presents isolated and potentially random feature interactions, and (ii) the parameters used in the study may not be representative of real-world conditions. In this paper, we explore both issues by applying large-scale experiment design and black-box optimization techniques to analyze convergence of network routes in the Open Shortest Path First protocol over a realistic network topology. By using these techniques, we show that: (i) the needed number of simulation experiments can be reduced by an order of magnitude compared to traditional full-factorial experiment design (FFED) approach, (ii) unnecessary parameters can easily be eliminated, and (iii) rapid understanding of key parameter interactions can be achieved.
System-Wide Dynamic Power Management for Portable Multimedia Devices
Authors: Linwei Niu, Gang Quan
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

Energy reduction is critical to increase the mobility and battery life for today's pervasive portable computing systems. At the same time, energy reduction must be subject to the real-time constraints and quality of service (QoS) requirements for multimedia applications running on many of these systems. This paper presents a novel run-time scheduling approach to reduce the system-wide energy consumption for such systems. In this paper, the multimedia applications are modeled using a popular weakly hard realtime model, i.e., the (m, k)-model. Our experimental results show that, by judiciously scheduling the real-time tasks and shutting down the processor and/or peripheral devices, our approach can lead to significant energy savings while guaranteeing the (m, k)-firm deadlines at the same time.
An exact algorithm for the share-of-choice problem
Authors: Jeffrey D. Camm
Venue:  (2006)

Products and services can be thought of as bundles of attributes that are each made up of many levels. Consumers consider tradeoffs between various attributes and levels before making a purchase decision for a product. A popular marketing research technique called conjoint analysis is used to study these tradeoffs. The data on consumer preferences is generally decomposed using a regression procedure into utility values that the consumer associates with each level of every attribute. In the design of a new product, it is critical to determine a judicious combination of attribute levels that is likely to perform well in a market containing competitor products. Using these utility measures, a firm can design products that would best meet consumer expectations and the seller's objectives. A popular way to measure the success of a new product is to calculate the amount of market share it is expected to capture in a competitive market. Researchers have proposed the share-of-choice problem whose objective is to maximize the number of respondents from a conjoint study who prefer a new product to their status-quo products. The share-of-choice problem is NP-hard. The linear-programming based branch-and-bound algorithm is inefficient in solving real world instances of the share-of-choice problem. Several heuristic procedures to solve the share-of-choice problem have appeared in the literature. In this research, an exact algorithm is proposed to solve real world instances of the share-of-choice problem to optimality. An experiment is designed to test the run-time performance of the exact algorithm using a set of simulated problems that mimic real world problem characteristics. We also suggest potential extensions of the exact algorithm to solve modified versions of the share-of-choice problem, and also to solve the related product line design problem.
Maintenance of Fast Updated Frequent Pattern Trees for Record Modification
Authors: Tzung-Pei Hong, Jun-Wei Lin, Yu-Lung Wu
Venue: Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1 (2006)

In this paper, we attempt to extend the FP-tree construction algorithm for efficiently handling record modification. A fast updated FP-tree (FUFP-tree) structure is used, which makes the tree update process become easier. An FUFP-tree maintenance algorithm is also proposed for reducing the execution time in reconstructing the tree when records are modified. Experimental results show that the proposed FUFPtree maintenance algorithm for record modification runs faster than the batch FP-tree construction algorithm for handling updated records and generates nearly the same tree structure as the FP-tree algorithm.
Parallel EDAs to create multivariate calibration models for quantitative chemical applications
Authors: A. Mendiburu, J. Miguel-Alonso, J. A. Lozano, M. Ostra, C. Ubide
Venue: Journal of Parallel and Distributed Computing (2006)

This paper describes the application of a collection of data mining methods to solve a calibration problem in a quantitative chemistry environment. Experimental data obtained from reactions which involve known concentrations of two or more components are used to calibrate a model that, later, will be used to predict the (unknown) concentrations of those components in a new reaction. This problem can be seen as a selection + prediction one, where the goal is to obtain good values for the variables to predict while minimizing the number of the input variables needed, taking a small subset of really significant ones. Initial approaches to the problem were principal components analysis and filtering combined with two prediction techniques: artificial neural networks and partial least squares regression. Finally, a parallel estimation of distribution algorithm was used to reduce the number of variables to be used for prediction, yielding the best models for all the considered problems.
Acyclic domination on bipartite permutation graphs
Authors: Guangjun Xu, Liying Kang, Erfang Shan
Venue: Information Processing Letters (2006)

For a graph G = (V, E), a subset S ⊆ V is called an acyclic dominating set of G if every vertex in V - S is adjacent to at least one vertex in S and the subgraph induced by S contains no cycles. In this paper, we present a linear time algorithm for transforming a minimum dominating set in a bipartite permutation graph into a minimum acyclic dominating set. Chao et al. gave a linear time algorithm to find a minimum dominating set of a permutation graph. Thus, we show that the acyclic domination problem is linear time solvable for bipartite permutation graphs.
Why Machine Ethics?
Authors: Colin Allen, Wendell Wallach, Iva Smit
Venue: IEEE Intelligent Systems (2006)

Machine ethics, machine morality, artificial morality, and computational ethics are all terms for an emerging field of study that seeks to implement moral decision-making faculties in computers and robots. Machine ethics is not merely science fiction but a topic that requires serious consideration given the rapid emergence of increasingly complex autonomous software agents and robots. The authors introduce the issues shaping this new field of enquiry and describe issues regarding the development of artificial moral agents.This article is part of a special issue on Machine Ethics.
Parameter Estimation of Reinforced Soil Based on Neural Networks
Authors: Shouling He, Jiang Li
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

This paper presents the application of neural networks for estimating constitutive parameters of a nonlinear elastic model. The model is used to describe mechanical behavior of soil reinforced with fiber and lime. First, shear modulus and soil strength are assumed to be unknown nonlinear functions of multiple variables such as fiber and lime contents, confining pressure and sample aging periods. Then, a multilayer neural network is designed to map the highly nonlinear functions. Finally, conventional triaxial shearing tests are conducted with nine groups of soil samples to provide the experimental data for training and testing the neural network. The neural network model is compared to a linear regression model with exponential parameters. Results indicate the neural network approach is more efficient and the neural model provides much higher accuracy than the linear regression model.
Secondary Structure Prediction: Helix, Sheet and Coil, which method is accurate? Which is more efficient?
Authors: Allam Appa Rao
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

Feed-forward neural networks have been used to predict protein secondary structure for about 2 decades. Feed-forward nets are trained using a set of patterns known as the training set for which the desired outputs are known in advance - a process known in the neural network literature as supervised learning. These feedforward nets take known sequence-structure pairs as training examples and try to generalize the concept of secondary structure for a given sequence.
On the response of EMT-based control to interacting targets and models
Authors: Zinovi Rabinovich, Jeffrey S. Rosenschein
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

A novel control mechanism was recently introduced based on Extended Markov Tracking (EMT) [9, 10]. In this paper, we present a study of its response to multiple interacting control goals. We show a simple extension that can be integrated into EMT-based control, and which provides it with the ability to handle several behavioral targets. Experimental support for the validity of this extension is provided. We also describe an experiment with a simulated robot, where EMT-based controllers interact and interfere indirectly via the environment. Experiments support the resilience of multiagent EMT-based team control to potential conflicts that may appear within a team.
Multiscale contour description for pattern recognition
Authors: Kidiyo Kpalma, Joseph Ronsin
Venue: Pattern Recognition Letters (2006)

In this paper, we present a new method and its preliminary results within the context of pattern analysis and recognition. This method is based on the multiscale analysis of a curve and deals with the contour of planar objects. Our method uses a low-pass Gaussian kernel to gradually smooth the contour by decreasing the filter bandwidth. Applying gain control to the smoothed contour stretches it to the same scale as the original one so that both contours intersect. By varying the bandwidth and marking all the intersection points between the smoothed contour and the original one we can generate the intersection points map (IPM) function. The initial results obtained by applying this method to various contours appears to indicate that the IPM function has some very interesting properties within the context of pattern recognition. It is translation and rotation insensitive and also scale change resistant for a large range of scaling. The IPM function generated when applied to noisy contours shows that the method is resistant to noise for a range of noise energy. Applying the features extracted by this method to retrieve a pattern from a database confirms the efficiency of the method.
Web Application Security Engineering
Authors: J. D. Meier
Venue: IEEE Security and Privacy (2006)

Integrating security throughout the life cycle can improve overall Web application security. With adetailed review of the steps involved in applying security-specific activities throughout the softwaredevelopment life cycle, the author walks practitioners through effective, efficient application design,development, and testing.
Improving Grouped-Entity Resolution Using Quasi-Cliques
Authors: Byung-Won On, Ergin Elmacioglu, Dongwon Lee, Jaewoo Kang, Jian Pei
Venue: Proceedings of the Sixth International Conference on Data Mining (2006)

The entity resolution (ER) problem, which identifies duplicate entities that refer to the same real world entity, is essential in many applications. In this paper, in particular, we focus on resolving entities that contain a group of related elements in them (e.g., an author entity with a list of citations, a singer entity with song list, or an intermediate result by GROUP BY SQL query). Such entities, named as grouped-entities, frequently occur in many applications. The previous approaches toward grouped-entity resolution often rely on textual similarity, and produce a large number of false positives. As a complementing technique, in this paper, we present our experience of applying a recently proposed graph mining technique, Quasi-Clique, atop conventional ER solutions. Our approach exploits contextual information mined from the group of elements per entity in addition to syntactic similarity. Extensive experiments verify that our proposal improves precision and recall up to 83% when used together with a variety of existing ER solutions, but never worsens them.
Electrophysiological Signatures of Visual Lexical Processing: Open- and Closed-Class Words
Authors: Colin M. Brown, Peter Hagoort, Mariken Ter Keurs
Venue: Journal of Cognitive Neuroscience (1999)

This paper presents evidence of the disputed existence of an electrophysiological marker for the lexical-categorical distinction between open- and closed-class words. Event-related brain potentials were recorded from the scalp while subjects read a story. Separate waveforms were computed for open- and closed-class words. Two aspects of the waveforms could be reliably related to vocabulary class. The first was an early negativity in the 230- to 350-msec epoch, with a bilateral anterior predominance. This negativity was elicited by open- and closedclass words alike, was not affected by word frequency or word length, and had an earlier peak latency for closed-class words. The second was a frontal slow negative shift in the 350- to 500-msec epoch, largest over the left side of the scalp. This late negativity was only elicited by closed-class words. Although the early negativity cannot serve as a qualitative marker of the open- and closed-class distinction, it does reflect the earliest electrophysiological manifestation of the availability of categorical information from the mental lexicon. These results suggest that the brain honors the distinction between open- and closed-class words, in relation to the different roles that they play in on-line sentence processing.
Event detection from evolution of click-through data
Authors: Qiankun Zhao, Tie-Yan Liu, Sourav S. Bhowmick, Wei-Ying Ma
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Previous efforts on event detection from the web have focused primarily on web content and structure data ignoring the rich collection of web log data. In this paper, we propose the first approach to detect events from the click-through data, which is the log data of web search engines. The intuition behind event detection from click-through data is that such data is often event-driven and each event can be represented as a set ofquery-page pairs that are not only semantically similar but also have similar evolution pattern over time. Given the click-through data, in our proposed approach, we first segment it into a sequence of bipartite graphs based on theuser-defined time granularity. Next, the sequence of bipartite graphs is represented as a vector-based graph, which records the semantic and evolutionary relationships between queries and pages. After that, the vector-based graph is transformed into its dual graph, where each node is a query-page pair that will be used to represent real world events. Then, the problem of event detection is equivalent to the problem of clustering the dual graph of the vector-based graph. The clustering process is based on a two-phase graph cut algorithm. In the first phase, query-page pairs are clustered based on thesemantic-based similarity such that each cluster in the result corresponds to a specific topic. In the second phase, query-page pairs related to the same topic are further clustered based on the evolution pattern-based similarity such that each cluster is expected to represent a specific event under the specific topic. Experiments with real click-through data collected from a commercial web search engine show that the proposed approach produces high quality results.
Agents' roles in B2C e-commerce
Authors: Luigi Palopoli, Domenico Rosaci, Domenico Ursino
Venue: AI Communications (2006)

The rapid evolution of the Internet from a general information space to an electronic market space provides the users with the possibility to navigate among thousands of Web sites for comparing products and merchants, for making their purchases or for obtaining some desired services. However, from the user's viewpoint, such a navigation often requires an high cost in terms of time to spend on the Web to perform a satisfying comparison of the various alternatives. From the supplier's viewpoint, it is needed to propose products in a suitable way to customers, taking into account the typology of each customer, her/his preferences, habits, etc.In this context, generally denoted as Business-to-Customer (B2C) e-commerce, the use of software agents as mediators in e-commerce activities seems to be particularly promising.In this paper, we describe and analyze the various roles agents have assumed in B2C e-commerce applications. Furthermore, we propose a Consumer Buying Behaviour model, called E2-CBB, that considers new emergent issues, as the capability to solve semantic heterogeneity, and the adaptive presentations of Web stores. By using such a model, we classify and compare a number of agent-based approaches for managing B2C e-commerce, proposed in the literature in the last ten years.
Using New Soft Clustering Technique in Adaptive Web Site
Authors: R. A. Shokry, A. A. Saad, N. M. El-Makkey, M. A. Ismail
Venue: Proceedings of the 2006 IEEE/WIC/ACM international conference on Web Intelligence and Intelligent Agent Technology (2006)

The ability of the web site to automatically reorganize the site structure towards the benefit of user groups or individuals, known as web site adaptation, is becoming a major requirement for web site designers to improve their sites' usability. Clustering techniques are used as the basis of many existing approaches for developing adaptive web sites. However the used clustering techniques limit the efficiency of these approaches. We developed a new soft clustering technique to be used as the underlying technique for adaptive web sites. In particular, it proposes the use of soft k-medoids technique to provide a more efficient solution to the index page synthesis problem. The performance of the proposed systems is evaluated using real data. The performance evaluation experiments showed the effectiveness of the proposed systems. Also, the experiments showed the scalability of the proposed systems for an increasing number of users and for an increasing size of web logs.
An Empirical Study on Education Strategy to E-learning in a Developing Country
Authors: Joseph Kizito Bada, Bijan Khazali
Venue: Proceedings of the Fourth IEEE International Workshop on Technology for Education in Developing Countries (2006)

The use of information and communication technology (ICT) has enhanced teaching and learning in developing countries. Educational institutions use ICT as a tool for teaching and learning in a number of ways including but not limited to Internet-based content delivery (an example is blackboard software), visualization by using PowerPoint projector and overhead projector, local area network (LAN) for conducting lessons with the instructor taking control at the server computer. The use of ICT has not been fully explored for delivery of educational services and in particular e-learning. In this paper, we have presented the opinion of the public and education service providers for the future of e-learning in Uganda. In particular we present the interest of students in web based learning, the category of students who can benefit from e-learning approach, and the present information technology infrastructure that can support e-learning implementation programme in a developing country with Uganda as a case study.
Computational mechanism design for multi-sensor information fusion
Authors: A. Rogers, R. K. Dash, N. R. Jennings, S. Reece, S. Roberts
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

Conventional information fusion architectures are challenged by developments in sensor networks that allow individually-owned (and thereby selfish) sensors to interact and share data. Given this, we advocate the use of tools and techniques from computational mechanism design, a field at the intersection of computer science, game theory and economics, to address the challenges posed by these networks. These techniques allow us to engineer networks with desirable system-wide properties, in which sensors are represented as selfish rational agents, each attempting to fulfill their own individuals goals. In this paper, we present the work of the Argus II DARP project (http://www.robots.ox.ac.uk/~argus/) and we demonstrate the application of mechanism design within a real world information fusion sensor network scenario.
Deploying, updating, and managing tools for collecting software metrics
Authors: Alberto Sillitti, Barbara Russo, Paolo Zuliani, Giancarlo Succi
Venue: Proceedings of the 2004 workshop on Quantitative techniques for software agile process (2004)

Collecting software engineering data is difficult due to the number of problems that researchers face in this activity. One of the most relevant is the ability to install and keep up-to-date the measurement tools installed in the production machines in order to collect such data. Even when a few machines are involved, maintaining all the tools required to collect data from the different development tools requires a full-time system administrator. Moreover, since most of these tools are research tools, researchers are updating them very frequently to fix bugs or to add new features. In a production environment, especially when Agile Methodologies are in place, the time and effort. For these reasons, automating the management of the tools for metrics collection is a key factor to provide easy-to-use tools and allow development teams to collect data useful for both practitioners and researchers.