ppxscal/embedding_network huggingface dataset:
Including the influence of groundwater exchanges in a lumped rainfall-runoff model
Authors: Natasha Herron, Barry Croke
Venue: Mathematics and Computers in Simulation (2009)

The growing realisation that groundwater and surface water systems are components of connected hydrologic system has in recent years sparked the development of integrated surface-ground water models. In this paper, a version of the IHACRES rainfall-runoff model is presented, in which the CMD module for calculating effective rainfall is coupled to a streamflow-groundwater module, and applied to the Coxs Creek catchment, a variably gaining-losing stream system in Australia. The aim is to determine the capacity for the coupled model to capture the switching off-on behaviour evident in the observed flow record. Model performance can be improved in terms of event prediction, volume of baseflow and the percentile of flow cessation, through manipulation of CMD parameters, however, improvements in some performance criteria come at the expense of performance in others. An analysis of the input rainfall time-series, generated using a standard weighted Thiessen polygon approach, reveals mismatches between observed streamflow events and the occurrence of rainfall, which impose major limits on model performance. The challenge is to develop a simple lumped rainfall-runoff model that has the potential to improve system understanding and allow for meaningful exploration of alternate climate, groundwater extraction and land use change scenarios, given a situation of data poor catchments in many parts of Australia.
Evaluation of Alternative Label Placement Techniques in Dynamic Virtual Environments
Authors: Stephen D. Peterson, Magnus Axholt, Matthew Cooper, Stephen R. Ellis
Venue: Proceedings of the 10th International Symposium on Smart Graphics (2009)

This paper reports on an experiment comparing label placement techniques in a dynamic virtual environment rendered on a stereoscopic display. The labeled objects are in motion, and thus labels need to continuously maintain separation for legibility. The results from our user study show that traditional label placement algorithms, which always strive for full label separation in the 2D view plane, produce motion that disturbs the user in a visual search task. Alternative algorithms maintaining separation in only one spatial dimension are rated less disturbing, even though several modifications are made to traditional algorithms for reducing the amount and salience of label motion. Maintaining depth separation of labels through stereoscopic disparity adjustments is judged the least disturbing, while such separation yields similar user performance to traditional algorithms. These results are important in the design of future 3D user interfaces, where disturbing or distracting motion due to object labeling should be avoided.
Application of Visualization Method to Concrete Mix Optimization
Authors: Bin Shi, Liexiang Yan, Quan Guo
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part III (2009)

Due to the complex interaction of components, the design of concrete mix becomes difficult. This paper presents an artificial neural network (ANN) based visualization method to optimize the concrete mix design. It aims to minimize the cost of concrete such that all desired qualities are maintained. The procedure can be described as mapping data of concrete mix from multidimensional space to a two-dimensional plane with an ANN model, and then generating concrete property contours on this plane. The optimized mix proportions region can be determined intuitively based on the contours distribution. By means of an inversion mapping algorithm, the optimal point in this region can be mapped inversely to the original multidimensional space. Practical production test results show that good concrete mixes, which agree with the concrete compressive strength criterion and have lower cost, can be obtained. Application of this method can contribute significant benefits to the commercial concrete companies.
A hybrid recommendation technique based on product category attributes
Authors: Amir Albadvi, Mohammad Shahbazi
Venue: Expert Systems with Applications: An International Journal (2009)

Recommender systems are powerful tools that allow companies to present personalized offers to their customers and defined as a system which recommends an appropriate product or service after learning the customers' preferences and desires. Extracting users' preferences through their buying behavior and history of purchased products is the most important element of such systems. Due to users' unlimited and unpredictable desires, identifying their preferences is very complicated process. In most researches, less attention has been paid to user's preferences varieties in different product categories. This may decrease quality of recommended items. In this paper, we introduced a technique of recommendation in the context of online retail store which extracts user preferences in each product category separately and provides more personalized recommendations through employing product taxonomy, attributes of product categories, web usage mining and combination of two well-known filtering methods: collaborative and content-based filtering. Experimental results show that proposed technique improves quality, as compared to similar approaches.
Solving Traveling Salesman Problem by Using an Evolutionary Algorithm Based on the Local Search Strategy
Authors: Xuan Wang, Gan-Nian Zhang, Yuan-Xiang Li
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

This paper introduces a new evolutionary algorithm based on the local search strategy and uses it to solve the Traveling Salesman Problem. The algorithm incorporates speediness of local search methods in neighborhood search with robustness of evolutionary methods in global search in order to obtain global optimum. The experimental results show that the algorithm is of potential to obtain global optimum or more accurate solutions than other evolutionary methods for the TSP.
A unified approach to introductory computer science: can one size fit all?
Authors: Timothy Huang, Amy Briggs
Venue: ACM SIGCSE Bulletin (2009)

We discuss our recent experience offering a single introductory computer science course for all students with no prior computer science coursework. The new course interleaves material from traditional CS0 and CS1 courses, providing all students with both a broad overview and an appreciation for the algorithmic foundations of the discipline of computer science. We describe our motivation for this approach, the content of the new course, and some conclusions based on our experiences and feedback from student course evaluations.
How to Improve Collaborative Decision Making in the Context of Knowledge Management
Authors: Inès Saad, Michel Grundtsein, Camille Rosenthal-Sabroux
Venue: Proceeding of the 2008 conference on Collaborative Decision Making: Perspectives and Challenges (2008)

In this paper we present a Multi-criteria Classification Methodology for identifying and evaluating crucial knowledge. We aim to identify, on the one hand, the explicit and tacit crucial knowledge to be preserved in the organizational memory, and on the other hand the tacit knowledge that is hard to formalize.
Bubble Letters: a child-centric interface for virtual and real world experience
Authors: Jinyoung Kim, Donggi Jung, Kibeom Lee, Yongjin Jin, Woon Seung Yeo
Venue: Proceedings of the 8th International Conference on Interaction Design and Children (2009)

In this paper, we suggest a new interactive game for children, Bubble Letters, which allows children to experience both real and virtual environments by interacting with physical interfaces. A user composes a message from the screen and displays it on the public screen. With this process, children can learn how to compose and deliver their messages to their friends with fun, and may also develop a conception of the world by involving physical interactions. Adults can also enjoy Bubble Letters by retrieving childhood memories through childlike acts with their children.
An efficient protection scheme for wireless mesh networks
Authors: Osameh M. Al-Kofahi, Ahmed E. Kamal
Venue: Proceedings of the 2009 conference on Information Science, Technology and Applications (2009)

Network coding is a promising technique that allowed a lot of enhancements to many traditional network applications. In this paper, we study the problem of utilizing network coding to provide protection against a single link failure to a many-to-one flow in a wireless mesh network with a single sink node. We show that by using network coding proactive protection can be achieved using around 50% of the resources used if network coding was not allowed. In addition, we prove the NP-completeness of the problem for networks with limited minimum cuts. Also, to make the coding and decoding efficient, we show how to do these operations over a binary field. Finally, the performance of the coding-based scheme is compared with traditional approaches, and it is shown that in the case of a failure our approach will be better than the standard approaches.
Hierarchical Strategy Learning for FLUX Agents
Authors: Hendrik Skubch
Venue:  (2007)

FLUX is a programming system for reasoning agents based on the fluent calculus. FLUX agents maintain an internal model of their environment, enabling them to represent partial knowledge. This ability gives rise to powerful reasoning techniques such as planning. Conventionally, the strategy such an agents executes in order to achieve a certain goal is static and needs to be defined in advance. Agents which are able to derive a strategy on their own, using experience and domain knowledge, can provide a way to tackle real world problems that change unexpectedly or for which no solution is known in advance. In this work, we focus on learning a strategy able to use the reasoning capabilities offered by systems such as FLUX. We present a technique to decompose a problem into smaller subproblems using heuristics derived from a given domain description. On this basis, subprograms are learnt in different hypothesis spaces, which correspond to different reasoning techniques. With the help of a grammar inducer, an inductive inference machine composes the found subprograms into the final strategy. The application of this work is still restricted to scenarios where a simulator is available. 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
Using rituals to express cultural differences in synthetic characters
Authors: Samuel Mascarenhas, João Dias, Nuno Afonso, Sibylle Enz, Ana Paiva
Venue: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1 (2009)

There is currently an ongoing demand for richer Intelligent Virtual Environments (IVEs) populated with social intelligent agents. As a result, many agent architectures are taking into account a plenitude of social factors to drive their agents' behaviour. However, cultural aspects have been largely neglected so far, even though they are a crucial aspect of human societies. This is largely due to the fact that culture is a very complex term that has no consensual definition among scholars. However, there are studies that point out some common and relevant components that distinguish cultures such as rituals and values. In this article, we focused on the use of rituals in synthetic characters to generate cultural specific behaviour. To this end, we defined the concept of ritual and integrated it into an existing agent architecture for synthetic characters. A ritual is seen as a symbolic social activity that is carried out in a predetermined fashion. This concept is modelled in the architecture as a special type of goal with a pre-defined plan. Using the architecture described, and in order to assess if it is possible to express different cultural behaviour in synthetic characters, we created two groups of agents that only differed in their rituals. An experiment was then conducted using these two scenarios in order to evaluate if users could identify different cultural behaviour in the two groups of characters. The results show that users do indeed identify the differences in the two cultures and most importantly that they ascribe the differences to cultural factors.
Algebras for combinatorial search
Authors: J. michael Spivey
Venue: Journal of Functional Programming (2009)

Combinatorial search strategies including depth-first, breadth-first and depth-bounded search are shown to be different implementations of a common algebraic specification that emphasizes the compositionality of the strategies. This specification is placed in a categorical setting that combines algebraic specifications and monads.
Domain Interaction Footprint
Authors: Christian Schillinger, Prisca Boisguerin, Gerd Krause
Venue: Bioinformatics (2009)

Motivation: The flow of information within cellular pathways largely relies on specific protein–protein interactions. Discovering such interactions that are mostly mediated by peptide recognition modules (PRM) is therefore a fundamental step towards unravelling the complexity of varying pathways. Since peptides can be recognized by more than one PRM and high-throughput experiments are both time consuming and expensive, it would be preferable to narrow down all potential peptide ligands for one specific PRM by a computational method. We at first present Domain Interaction Footprint (DIF) a new approach to predict binding peptides to PRMs merely based on the sequence of the peptides. Second, we show that our method is able to create a multi-classification model that assesses the binding specificity of a given peptide to all examined PRMs at once. Results: We first applied our approach to a previously investigated dataset of different SH3 domains and predicted their appropriate peptide ligands with an exceptionally high accuracy. This result outperforms all recent methods trained on the same dataset. Furthermore, we used our technique to build two multi-classification models (SH3 and PDZ domains) to predict the interaction preference between a peptide and every single domain in the corresponding domain family at once. Predicting the domain specificity most reliably, our proposed approach can be seen as a first step towards a complete multi-domain classification model comprised of all domains of one family. Such a comprehensive domain specificity model would benefit the quest for highly specific peptide ligands interacting solely with the domain of choice. Contact: gkrause@fmp-berlin.de Supplementary information: Supplementary data are available at Bioinformatics online.
The role of congregation in service-oriented development
Authors: Colin Atkinson, Philipp Bostan
Venue: Proceedings of the 2009 ICSE Workshop on Principles of Engineering Service Oriented Systems (2009)

Although they are still being refined, the principles of service-oriented architectures have significant benefits for the maintenance and administration of enterprise systems. However, they are not particularly well suited for supporting the development of client applications and business processes. In particular, the absence of the notion of types, in the sense of abstract data types and object-oriented programming, limits the way in which client application developers can access resources in a service-oriented architecture and leverage reusable assets. In this paper we propose the notion of congregation as a key step and ingredient in service-oriented development that supports flexible deployment and usage of types in an enterprise system. We explain the need for congregation and provide a small motivating example of its application.
Communication of direction through lateral skin stretch at the fingertip
Authors: Brian T. Gleeson, Scott K. Horschel, William R. Provancher
Venue: Proceedings of the World Haptics 2009 - Third Joint EuroHaptics conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2009)

A variety of tasks could benefit from the availability of direction cues that do not rely on vision or sound. Skin stretch has been found to be a reliable means of communicating direction and has potential to be rendered by a compact device. We have conducted experiments exploring the use of lateral skin stretch at the fingertip to communicate direction. A small rubber cylinder was pressed against a subject's fingertip and moved at constant speed to stretch the skin of the fingerpad. The skin was stretched with a range of displacements (0.05 mm–1 mm) and speeds (0.5 mm/s-4 mm/s). Subjects were asked to respond with the direction of the skin stretch, choosing from 4 directions, each separated by 90 degrees. It was found that subjects could perceive skin stretch direction with as little as 0.05 mm of stretch. Direction detection accuracy was found to be dependent upon both the speed and total displacement of the skin stretch. Higher speeds and larger displacements resulted in greater accuracy. High accuracy rates, greater than 95%, were observed with as little as 0.2 mm of skin stretch and at speeds as slow as 2 mm/s. Accuracy was also found to vary with the direction of the stimulus. This preliminary information will be used to inform the design of a miniature tactile display suitable for use in hand-held electronics.
Integrating a Feature Selection Algorithm for Classification of Voltage Sags Originated in Transmission and Distribution Networks
Authors: Abbas Khosravi, Toni Martinez, Joaquim Melendez, Joan Colomer, Jorge Sanchez
Venue: Proceeding of the 2007 conference on Artificial Intelligence Research and Development (2007)

As a global problem in the power quality area, voltage sags are matter of high interest for both utilities and customers. With a view to resolving the problem of sag source location in the power network, this paper introduces a new method based on dimension reduction capability of Multiway Principal Component Analysis (MPCA). MPCA models are developed using three dimensional databases of voltage and current Root Mean Square (RMS) values. Computed scores are then used for training commonly used classifiers for putting sags in two classes. A feature selection algorithm is successfully applied for determining the optimal subsets of scores for training classifiers and also the number of principal components in the MPCA models. The proposed method is tested with success using some real voltage sags recorded in some substations. Also, through some experiments we demonstrate that satisfactorily high classification rates must be attributed to the applied feature selection algorithm.
Dynamic registration and discovery of location-based services using spatial registries
Authors: Nathanaël Cottin, Maxime Wack
Venue: Proceedings of the 3rd workshop on Agent-oriented software engineering challenges for ubiquitous and pervasive computing (2009)

Service-Oriented Architectures rely on services cooperation to answer requesters' needs. Services invocation requires access points, such as Internet URLs, provided by specific services called registries. Traditional registries allow to register (advertise) services and provide requesters with suitable services' binding information. However, these registries are not designed to take a particular concern about Location-Based Services (LBSs). LBSs' discovery must be strongly related to requesters' provided geographical locations as well as LBSs' coverage areas which define LBSs' geographical limits of action. This work introduces Spatial Registries, a new type of registries specialized in LBSs' registration and discovery. Spatial Registries' operations on LBSs registration and discovery are described. Different architectural designs and security issues related to Spatial Registries are also discussed.
A course on algorithms and data structures using on-line judging
Authors: Ginés Gárcia-Mateos, José Luis Fernández-Alemán
Venue: ACM SIGCSE Bulletin (2009)

High dropout rates are commonly the main problem we must face in Computer Science degrees. There are two main causes of dropout: the implicit complexity of the matter, and a lack of motivation among students. The second-year programming course of our university suffered dropout rates of over 70% of the more than three hundred enrolled students. In order to overcome this problem, we have adopted a new teaching methodology based on two key ideas: replacing the traditional final exam with a series of activities in a continuous evaluation context; and making those activities more appealing to the students. In particular, most of the activities are designed as on-line programming competitions; they are carried out by using a web-based automatic evaluation system, the on-line judge. Experimental results show the high effectiveness of the proposed approach. On average, the dropout rate decreased to 45% while the pass rate doubled. Some strategies are used to ensure the authorship of the programs and to detect source code plagiarism.
Network effects in algorithmic game theory
Authors: Anna R. Karlin
Venue:  (2008)

With the development of the Internet and new technologies, network effects are recognized as a critical part of the industrial organization and play a fundamental role in expanding the economics of Information Technology industries. Network effects occur when the value or utility of a product or service to an individual varies depending on the number and possibly the set of other individuals who own the product or service. Our focus is to understand the role of network effects and study the following questions in different settings: (1) What is the best way to take advantage of network effects to market a new product? We study the question in a viral marketing model with diffusion of information through a social network. We model the question as an optimization problem and show a strong inapproximability result. Our result continues to hold for a few special settings and answers a complexity question proposed in [54, 119]. (2) What is the best way to reach and evaluate social optimum? Motivated by applications in online dating and kidney exchange, we study a stochastic matching problem, where nodes represent agents in a matching market with dichotomous preferences, i.e., each agent finds every other agent either acceptable or unacceptable and is indifferent between all acceptable agents. The goal is to produce a matching between acceptable agents of maximum size. We give a simple greedy strategy for selecting probes which produces a matching whose cardinality is, in expectation, at least a quarter of the size of this optimal algorithm's matching. We additionally show that variants of our algorithm can handle more complicated constraints, such as a limit on the maximum number of rounds, or the number of pairs probed in each round. To evaluate social optimum in terms of competition among agents, we propose the notion of cheap labor cost in "hiring a team" markets to characterize how much better off a market can be for a consumer by removing a subset of agents. We present tight bounds on the cheap labor cost for a variety of markets including s-t path markets, matroid markets and perfect bipartite matching markets. (3) What is the best way to maximize the total revenue given the existence of network effects? We study the question in an envy-free pricing setting with metric substitutability among items. While the general envy-free pricing problem is hard to approximate, the addition of metric substitutability constraints allows us to solve the problem exactly in polynomial time by reducing it to an instance of weighted independent set on a perfect graph. When the substitution costs do not form a metric, even in cases when a (1 + &epsi;)-approximate triangle inequality holds, the problem becomes NP-hard. Our results show that the triangle inequality is the exact sharp threshold for the problem of going from "tractable" to "hard".