ppxscal/embedding_network huggingface dataset:
Ant Colony with Stochastic Local Search for the Quadratic Assignment Problem
Authors: Malek Mouhoub, Zhijie Wang
Venue: Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (2006)

The existing Ant Colony Optimization (ACO) Algorithms for the Quadratic Assignment Problem (QAP) are often combined with two kinds of Stochastic Local Search (SLS) methods: the 2-opt local search and the tabu local search. In this paper, these two SLS methods are respectively improved according to the properties of ACO and QAP. For the 2-opt local search, a new random walk strategy is used to avoid a quick stagnation into local optima. Moreover, a forward-looking strategy is proposed to explore the neighborhood more thoroughly. In the case of tabu local search, a random walk strategy is also employed to avoid getting stuck at local optima. Experimental evaluation of the ACO algorithms combined with the improved local search proposed in this paper are conducted on problems from the well known QAPLIB library. The results demonstrate that each ACO algorithm, combined with its respective improved local search, has a better performance, in terms of the quality of the solution returned, than the ACO algorithm with the original local search techniques. Moreover, we also noticed that the improved methods outperform each other for different classes of problems.
Implementation of Outdoor Mixed Reality Gaming on Mobile Devices
Authors: Yoshimichi Sasaki, Masaru Kamada, Tatsuhiro Yonekura
Venue: Proceedings of the 2006 International Conference on Cyberworlds (2006)

A system of vision-based mixed reality is developed for implementing outdoor gaming on a mobile device having a single camera and a slow CPU. To help the poor device, it is assumed that sufficiently many marker objects of the same size are scattered in the real world so that relative translation and rotation of the camera can be easily calculated from their position and size in the camera image. This system can be applied to outdoor games of which scenario allows for existence of some items that the markers can mimic.
Geometric modeling applications in rational drug design: a survey
Authors: Hans J. Wolters
Venue: Computer Aided Geometric Design (2006)

Computer aided design methods are starting to gain acceptance in the field of life sciences and drug discovery, thus giving rise to a discipline coined Computer Aided Drug Discovery (CADD). This trend is accompanied by a larger interest in 3-dimensional methods. Traditionally for many applications chemical entities such as proteins and molecules have been regarded as either 2D graphs or sequences of letters (proteins and genome). This survey article will give an overview and historical perspective of the state of the art of geometric modeling as it relates to drug discovery.
A linear space algorithm for computing a longest common increasing subsequence
Authors: Yoshifumi Sakai
Venue: Information Processing Letters (2006)

Let X and Y be sequences of integers. A common increasing subsequence of X and Y is an increasing subsequence common to X and Y. In this note, we propose an O(|X| ċ |Y|)-time and O(|x| + |Y|)-space algorithm for finding one of the longest common increasing subsequences of X and Y, which improves the space complexity of Yang et al. [I.H. Yang, C.P. Huang, K.M. Chao, A fast algorithm for computing a longest common increasing subsequence, Inform. Process. Lett. 93 (2005) 249-253] O(|X| ċ |Y|)-time and O(|X| ċ |Y|)-space algorithm, where |X| and |Y| denote the lengths of X and Y, respectively.
Dealing with Class Skew in Context Recognition
Authors: Mathias Stager, Paul Lukowicz, Gerhard Troster
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

As research in context recognition moves towards more maturity and real life applications, appropriate and reliable performance metrics gain importance. This paper focuses on the issue of performance evaluation in the face of class skew (varying, unequal occurrence of individual classes), which is common for many context recognition problems. We propose to use ROC curves and Area Under the Curve (AUC) instead of the more commonly used accuracy to better account for class skew. The main contributions of the paper are to draw the attention of the community to these methods, present a theoretical analysis of their advantages for context recognition, and illustrate their performance on a real life case study.
Engineering Trustworthy Ontologies: Case Study of Protein Ontology
Authors: Farookh K. Hussain, Amandeep S. Sidhu, Tharam S. Dillon, Elizabeth Chang
Venue: Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (2006)

Biomedical Ontologies are huge. It is not possible for any one person to manage and engineer a complete ontology. They would need the help of Research Assistants and other people to develop and maintain the ontology. In the process of developing and maintaining the ontology the Research Assistants may enter incorrect data, resulting in low quality of the ontology. In this paper we will propose a conceptual framework to solve these ontology management and ontology development issues. There can be N assistants entering data into the ontology. All the data entered initially is stored in an intermediate ontology. The administrator of the ontology has a set of rules, which makes a checklist that checks and validates the data in intermediate ontology for correctness according to the ontology schema. We use the Case Study of Protein Ontology for this proposed approach to develop interfaces for assistants and administrators. The proposed approach can easily be extended to other biomedical ontologies just by tweaking the administrator rule set according to the ontology.
Finding Optimal Join Tree forMulti-Join Stream Queries in a Production System
Authors: Joseph S. Gomes, Heyong-Ah Choi
Venue: Proceedings of the 26th IEEE International ConferenceWorkshops on Distributed Computing Systems (2006)

Data Stream Management Systems (DSMS) handle a particular type of database applications that involve multiple continuous data streams with inputs arriving at highly variable and unpredictable rates. Since data rate fluctuates over time in this type of applications the appropriate join tree is crucial for maintaining high system throughput. We consider the problem of finding optimal join tree for performing count based sliding window multi-joins over continuous streams. We use a unit-time based cost model to evaluate the expected performance for a given join tree. We materialize all intermediate results assuming there is enough main memory to store all partial results and window buffers. We give a polynomial time algorithm that finds the optimal join tree under our cost model for a given noncommuting (single permutation) order of streams. This algorithm can be used in conjunction with any linear order producing heuristic to give the optimal tree for that order. Our algorithm is implemented in the Jess rule engine and an extensive experimental evaluation is provided.
IPv6 as a Practical Solution to Network Management Challenges
Authors: Ciprian Popoviciu, Petre Dini
Venue: Proceedings of the International Multi-Conference on Computing in the Global Information Technology (2006)

Over the paste decade, IPv6 community's efforts to promote the next generation of the IP protocol revolved around generating business models that would justify the migration costs. The context, a depleting global address pool, and the target, global services, missed on one interesting opportunity for IPv6. Larger IP Service Provider and Enterprise networks are running out of IPv4 resources to manage their devices. Alleviating this problem with the help of IPv6 would be more valuable to them in the immediate future than providing user services. This paper reviews the current interest in leveraging IPv6 for management and it analyzes few possible protocol extensions that would enable its use in this role to a larger extent. While the paper discusses some of the challenges faced by these deployment proposals, it contends that this could be a reasonable and practical first step in the early adoption of IPv6 in large networks.
Is neuroscience a learning science?
Authors: Sashank Varma, Daniel L. Schwartz, Bruce McCandliss
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Should education and neuroscience be connected? We review eight arguments against and eight arguments for connecting the two disciplines. We conclude that ultimately, whether education and neuroscience have anything to offer one another is an empirical question -- one that is worth engaging.
Finding Hamiltonian paths in tournaments on clusters
Authors: Chun-Hsi Huang, Sanguthevar Rajasekaran, Laurence Tianruo Yang, Xin He
Venue: Cluster Computing (2006)

This paper presents a general methodology for the communication-efficient parallelization of graph algorithms using the divide-and-conquer approach and shows that this class of problems can be solved in cluster environments with good communication efficiency. Specifically, the first practical parallel algorithm, based on a general coarse-grained model, for finding Hamiltonian paths in tournaments is presented. On any such parallel machines, this algorithm uses only (3log p+1), where p is the number of processors, communication rounds, which is independent of the tournament size, and can reuse the existing linear-time algorithm in the sequential setting. For theoretical completeness, the algorithm is revised for fine-grained models, where the ratio of computation and communication throughputs is low or the local memory size, $$O(\frac{N}{p})$$ , of each individual processor is extremely limited $$(\frac{N}{p} \ge p^\epsilon,$$ for any $$\epsilon > 0)$$ , solving the problem with O(log p) communication rounds, while the hidden constant grows with the scalability factor 1/¿. Experiments have been carried out on a Linux cluster of 32 Sun Ultra5 computers and an SGI Origin 2000 with 32 R10000 processors. The algorithm performance on the Linux Cluster reaches 75% of the performance on the SGI Origin 2000 when the tournament size is about one million.
Real-time Supervisory Control and Scheduling for Complex Industrial Process Based on Integrated Modeling
Authors: Xingmei Feng, Yanping Li, Liang Chen
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)

A complex industrial process is described by means of a new model of process/transition Petri nets with mixed-mark, namely time-varied process/transition Petri nets in this paper. In this model, the running marks and remnant time of sub-process are introduced. Based on logic and timed mark variables, it solved effectively many problems of complex industrial process, such as the integrated modeling of subprocess, the coupling between discrete variables and continuous states and joining between process controls and production control. And real-time supervisory control and scheduling of complex industrial process with multi-working places are studied deeply based on this model. Finally, the approaches to solve optimal strategies of real-time supervisory control, the realtime scheduling and process control are proposed.
Online Data Gathering for Maximizing Network Lifetime in Sensor Networks
Authors: Weifa Liang
Venue: IEEE Transactions on Mobile Computing (2007)

Energy-constrained sensor networks have been deployed widely for monitoring and surveillance purposes. Data gathering in such networks is often a prevalent operation. Since sensors have significant power constraints (battery life), energy efficient methods must be employed for data gathering to prolong network lifetime. We consider an online data gathering problem in sensor networks, which is stated as follows: Assume that there is a sequence of data gathering queries, which arrive one by one. To respond to each query as it arrives, the system builds a routing tree for it. Within the tree, the volume of the data transmitted by each internal node depends on not only the volume of sensed data by the node itself, but also the volume of data received from its children. The objective is to maximize the network lifetime without any knowledge of future query arrivals and generation rates. In other words, the objective is to maximize the number of data gathering queries answered until the first node in the network fails. For the problem of concern, in this paper, we first present a generic cost model of energy consumption for data gathering queries if a routing tree is used for the query evaluation. We then show the problem to be NP-complete and propose several heuristic algorithms for it. We finally conduct experiments by simulation to evaluate the performance of the proposed algorithms in terms of network lifetime delivered. The experimental results show that, among the proposed algorithms, one algorithm that takes into account both the residual energy and the volume of data at each sensor node significantly outperforms the others.
Yet another network simulator
Authors: Mathieu Lacage, Thomas R. Henderson
Venue: Proceeding from the 2006 workshop on ns-2: the IP network simulator (2006)

We report on the design objectives and initial design of a new discrete-event network simulator for the research community. Creating Yet Another Network Simulator (yans, http://yans.inria.fr/yans) is not the sort of prospect network researchers are happy to contemplate, but this effort may be timely given that ns-2 is considering a major revision and is evaluating new simulator cores. We describe why we did not choose to build on existing tools such as ns-2, GTNetS, and OPNET, outline our functional requirements, provide a high-level view of the architecture and core components, and describe a new IEEE 802.11 model provided with yans.
F-Miner: A New Frequent Itemsets Mining Algorithm
Authors: Xiaoyun Chen, Longjie Li, Zhixin Ma, Shenshen Bai, Feng Guo
Venue: Proceedings of the IEEE International Conference on e-Business Engineering (2006)

In this paper, we present a novel algorithm, called FMiner, to mine the complete set of frequent itemsets by pattern growth. The F-Miner algorithm uses two new compact data structures, Ascending FP-Tree (AFP-Tree) and Frequent Pattern Forest (FP-Forest), to represent the conditional databases. When we construct an AFP-Tree, the items in frequent 1-itemset are ordered in frequency ascending order. The AFP-Tree structure is traversed in top-down depth-first order. The root of the AFP-Tree is not "null", but an item which can identify this tree. AFP-Tree has a onedimensional array which stores the counts of every treenode's item except root-node. In F-Miner, we need many AFP-Trees to store a conditional database; these trees construct one forest, called FP-Forest. We test our algorithm versus several other algorithms on real world datasets, such as BMS-POS. The experimental results show that our algorithm is an efficient algorithm on both sparse and dense databases.
Human-Focused Computer Vision Applications
Authors: Massimo Piccardi
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

Proposed abstract: Recent years have seen an increasing number of computer visionhumans as their objects of interest. Such applications include video surveillance, domotics, multimedia semantic annotation and indexing, human-computer interfaces, affective"objects of interest"? A broad range of human-related features: motion, gestures, actions, interactions, activities, attitudes, behaviours, identity. This keynote will offer a survey of this field and present some current work from the speaker and his collaborators in the areas of emotion recognition and people tracking within camera networks.
Toward a decision-theoretic framework for affect recognition and user assistance
Authors: Wenhui Liao, Weihong Zhang, Zhiwei Zhu, Qiang Ji, Wayne D. Gray
Venue: International Journal of Human-Computer Studies (2006)

There is an increasing interest in developing intelligent human-computer interaction systems that can fulfill two functions-recognizing user affective states and providing the user with timely and appropriate assistance. In this paper, we present a general unified decision-theoretic framework based on influence diagrams for simultaneously modeling user affect recognition and assistance. Affective state recognition is achieved through active probabilistic inference from the available multi modality sensory data. User assistance is automatically accomplished through a decision-making process that balances the benefits of keeping the user in productive affective states and the costs of performing user assistance. We discuss three theoretical issues within the framework, namely, user affect recognition, active sensory action selection, and user assistance. Validation of the proposed framework via a simulation study demonstrates its capability in efficient user affect recognition as well as timely and appropriate user assistance. Besides the theoretical contributions, we build a non-invasive real-time prototype system to recognize different user affective states (stress and fatigue) from four-modality user measurements, namely physical appearance features, physiological measures, user performance, and behavioral data. The affect recognition component of the prototype system is subsequently validated through a real-world study involving human subjects.
An Automatic Generation of G^1 Curve Fitting of Arabic Characters
Authors: Fatimah Yahya, Jamaludin Md Ali, Ahmad Abdul Majid, Arsmah Ibrahim
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

An Arabic font is difficult to fit as it is cursive in character, having varying curves and cusps. Here, the Arabic character is represented as an outline font fitted with G^1 rational Bezier cubic curves. As a method in reverse engineering, the Arabic character is created by way of digitizing an image that already exists and then fitting G^1 curves automatically to the outline of the digitized image. The outline font representation is done in several phases - contour extraction of font image, corner point's detection and lastly contour segment fitting. Image is considered as binary and boundary is obtained accordingly. Eigenvalues of covariance matrix and the concept of region of support are employed to search for the corners of the Arabic characters which are of varying degrees of smoothness. G^1 rational Bezier cubics, iteratively determined, are used in the last step. The weights are adjusted automatically to get curves that are as close as need be to the digitized data points. This technique can be extended to visualizing outlines of other contour-based images automatically.
Mining citizen science data to predict orevalence of wild bird species
Authors: Rich Caruana, Mohamed Elhawary, Art Munson, Mirek Riedewald, Daria Sorokina, Daniel Fink, Wesley M. Hochachka, Steve Kelling
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

The Cornell Laboratory of Ornithology's mission is to interpret and conserve the earth's biological diversity through research, education, and citizen science focused on birds. Over the years, the Lab has accumulated one of the largest and longest-running collections of environmental data sets in existence. The data sets are not only large, but also have many attributes, contain many missing values, and potentially are very noisy. The ecologists are interested in identifying which features have the strongest effect on the distribution and abundance of bird species as well as describing the forms of these relationships. We show how data mining can be successfully applied, enabling the ecologists to discover unanticipated relationships. We compare a variety of methods for measuring attribute importance with respect to the probability of a bird being observed at a feeder and present initial results for the impact of important attributes on bird prevalence.
Contrasting cases: what we can learn from students' perceptions of "good" design
Authors: Joan M. T. Walker, Paul H. King
Venue: Proceedings of the 7th international conference on Learning sciences (2006)

Set in the context of an engineering design course, this study used contrasting cases to examine undergraduates' (1) ability to discriminate poor and excellent examples of student design projects, and (2) students' justifications for their ratings. At the beginning of the yearlong course, only 76% of students correctly identified the better project. Toward the end of the course, the majority of students correctly identified the superior example; however, many failed to note serious flaws in the poor example. Analyses of student justifications showed that most students used superficial reasons (e.g., readability) initially and deeper structural reasons (e.g., process) on the post-test. Results are discussed in terms of expert-novice differences, and how educators can support students' ability to notice salient problem features.
Enabling Collaboration in Distributed Requirements Management
Authors: Vibha Sinha, Bikram Sengupta, Satish Chandra
Venue: IEEE Software (2006)

Requirements management, one of the most collaboration-intensive activities in softwaredevelopment, presents significant difficulties when stakeholders are distributed, as in today'sglobal projects. After a review of requirements management in current work practices, the authorsdescribe EGRET, a collaborative requirements management tool for distributed software developmentteams. They present their design motivations for EGRET, a preliminary evaluation of its usability,and directions for further enhancement. This article is part of a special issue on Global Software Development.
RFID Malware: Truth vs. Myth
Authors: Melanie R. Rieback, Bruno Crispo, Andrew S. Tanenbaum
Venue: IEEE Security and Privacy (2006)

On 15 March 2006, our research team at Vrije Universiteit published a paper about RFID malwareentitled "Is Your Cat Infected with a Computer Virus?" as well as a companion Web site(wwww.rfidvirus.org). Our paper introduced the concept of RFID malware and presented an accompanyingproof-of-concept RFID virus. It ultimately resulted in a huge amount of media attention; within 24 hours ofpresenting it at the Fourth Annual IEEE International Conference on Pervasive Computing and Communications(IEEE PerCom), we received more than 200 email messages. Amid this chaos, our research paper received theBest Paper Award for High Impact at the IEEE PerCom conference. In the months that followed, reports ofRFID malware prompted reactions from the RFID industry, the antivirus industry, and the US and Dutchgovernments. In this installment of Crypto Corner, we give our general impression of the paper's aftermath,addressing some important unanswered questions and distinguishing the truths from the myths about the workwe did.
Representation and conversion of Bezier surfaces in multivariate B-form
Authors: Ruomei Wang, Xiaonan Luo, Yi Li
Venue: Journal of Computational and Applied Mathematics (2006)

In this paper, we present the representation and conversion method of Bezier surfaces in Multivariate B-Form. We can obtain the relationship between the surface of the multivariate B-form and the Bézier surface. Then the continuity connection conditions of the Bézier surface in a triangular and a rectangular region are given.