ppxscal/embedding_network huggingface dataset:
Clustering, grouping, and process over networks
Authors: Zhe Dang, Min Sik Kim
Venue:  (2007)

During the last few years there has been a rapid development in computer networks, especially wireless networks which enable mobile applications. Because of the increasing number of devices involved in network applications, it is necessary to investigate approaches to organize those devices based on their application requirements and make them perform the given tasks. The essential functionalities of a computer network is to establish relationships among network nodes, which are called grouping. An initial form of grouping, called clustering, has been observed by researchers whose research goals are to provide a network architecture that can be used to improve the network performance. In this dissertation, we first propose a number of clustering techniques including SMC, BAC, DCC, and TC, which, in some cases, outperform the existing ones.A more sophisticated form of grouping, in contrast to clustering, is to build relationships among network nodes based on the nodes&rsquo; functionalities. To do this, we first propose a specification language, called NetSpec, for studying this more general form of grouping. Using NetSpec, users can describe the desired functionalities of an individual network node, how a subset of nodes, called a group or a bond, are logically connected between each other, and, finally, how such groups evolve. For a network application specified in NetSpec, a compiler is described to translate the specification into a program that will run over a network virtual machine. In the dissertation, we describe the instruction set to support the virtual machine that runs above a physical network. The instruction set is powerful enough to execute the upper layer NetSpec specification while it is simple enough to be efficiently implemented by network protocols running on the under layer physical network. To thread instructions in the instruction set into an execution of the NetSpec specification, we also describe how to implement a non-deterministic scheduler to address fairness, synchronization, group communication control, and concurrency control.Essentially, NetSpec specifies how groups of network nodes evolve. Looking from the angle of each individual node, such an evolution can be characterize as a thread of atomic transitions, each of which is local; e.g., involving two network nodes. Inspired by this view, in the last part of this dissertation, we propose a form of network processes and study, theoretically, its computability and realization on a physical network.
Putting Things in Order: On the Fundamental Role of Ranking in Classification and Probability Estimation
Authors: Peter A. Flach
Venue: Proceedings of the 18th European conference on Machine Learning (2007)

While a binary classifier aims to distinguish positives from negatives, a ranker orders instances from high to low expectation that the instance is positive. Most classification models in machine learning output some score of `positiveness', and hence can be used as rankers. Conversely, any ranker can be turned into a classifier if we have some instance-independent means of splitting the ranking into positive and negative segments. This could be a fixed score threshold; a point obtained from fixing the slope on the ROC curve; the break-even point between true positive and true negative rates; to mention just a few possibilities.These connections between ranking and classification notwithstanding, there are considerable differences as well. Classification performance on n examples is measured by accuracy, an O(n) operation; ranking performance, on the other hand, is measured by the area under the ROC curve (AUC), an O(n logn) operation. The model with the highest AUC does not necessarily dominate all other models, and thus it is possible that another model would achieve a higher accuracy for certain operating conditions, even if its AUC is lower.However, within certain model classes good ranking performance and good classification performance are more closely related than suggested by the previous remarks. For instance, there is evidence that certain classification models, while designed to optimise accuracy, in effect optimise an AUC-based loss function [1]. It has also been known for some time that decision tree yield convex training set ROC curves by construction [2], and thus optimising training set accuracy is likely to lead to good training set AUC. In this talk I will investigate the relation between ranking and classification more closely.I will also consider the connection between ranking and probability estimation. The quality of probability estimates can be measured by, e.g., mean squared error in the probability estimates (the Brier score). However, like accuracy, this is an O(n) operation that doesn't fully take ranking performance into account. I will show how a novel decomposition of the Brier score into calibration loss and refinement loss [3] sheds light on both ranking and probability estimation performance. While previous decompositions are approximate [4], our decomposition is an exact one based on the ROC convex hull. (The connection between the ROC convex hull and calibration was independently noted by [5]). In the case of decision trees, the analysis explains the empirical evidence that probability estimation trees produce well-calibrated probabilities [6].
Ranking of Closeness Centrality for Large-Scale Social Networks
Authors: Kazuya Okamoto, Wei Chen, Xiang-Yang Li
Venue: Proceedings of the 2nd annual international workshop on Frontiers in Algorithmics (2008)

Closeness centrality is an important concept in social network analysis. In a graph representing a social network, closeness centrality measures how close a vertex is to all other vertices in the graph. In this paper, we combine existing methods on calculating exact values and approximate values of closeness centrality and present new algorithms to rank the top-k vertices with the highest closeness centrality. We show that under certain conditions, our algorithm is more efficient than the algorithm that calculates the closeness-centralities of all vertices.
Prototyping and Evaluation for Smart Home Controller Based on Chinese Families Behavior Analysis
Authors: Fang You, Huimin Luo, Yinglei Liang, Jianmin Wang
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

The fast development of Chinese architecture market and the smart home business have caused works on user research in smart home environment to be growing rapidly. Nonetheless, there are some problems related to product in use; and in this paper, we examine two problems that are present in smart home controllers from a user survey: one is the difficult in use for the Elderly; and the other is the complex operations for Nannies. Based on this we have examined and devised two prototypes designed for those two types of users; as well as the task sheet evaluation.
Multimodal authentication based on random projections and source coding
Authors: Sviatoslav Voloshynovskiy, Oleksiy Koval, Thierry Pun
Venue: Proceedings of the 10th ACM workshop on Multimedia and security (2008)

In this paper, we consider an authentication framework for independent modalities based on binary hypothesis testing using source coding jointly with the random projections. The source coding ensures the multimodal signals reconstruction at the decoder based on the authentication data. The random projections are used to cope with the security, privacy, robustness and complexity issues. Finally, the authentication performance is investigated for both direct and random projections domains. The asymptotic performance approximation is derived and compared with the exact solutions. The impact of modality fusion on the authentication system performance is demonstrated.
Two location problems in transportation
Authors: Anthony Chen
Venue:  (2007)

In many cities, traffic congestion is a serious problem due to limited roads and ever-increasing travel demands. Intelligent transportation systems (ITS) take advantages of the latest sensor, communication, and traffic control technologies to combat traffic congestion. These traffic surveillance technologies have been described as the eyes of ITS because they provide knowledge of existing network-wide traffic conditions. Effective traffic management and information systems rely heavily on a well-configured sensor network. The objective of this dissertation is to develop sound mathematical models that systematically and optimally locate two types of traffic sensors in a transportation network. First, this dissertation addresses the traffic counting location (TCL) problem: to determine the number and locations of traffic counting stations for the purpose of origin-destination (O-D) trip table estimation. The proposed model emphasizes using available data including network topology, land use information, and O-D pair structure to determine an appropriate set of traffic counts that better capture the spatial distribution of O-D demands. A customized GIS tool combined with 3D visualization schemes is developed to graphically reveal the impacts of traffic counting locations on the quality of O-D trip table estimates. Second, this dissertation addresses the automatic vehicle identification (AVI) reader location problem: to locate AVI readers to capture a maximum number of trips and a maximum number of O-D pairs using a minimum number of AVI readers for the purpose of collecting travel time information. Variants of the AVI reader location model are also developed to consider time-of-day demand patterns. In addition, a methodology is developed for selecting the most preferred solution from the set of Pareto optimal solutions obtained from solving the multi-objective AVI reader location problem. Two location problems in transportation are illustrated with case studies. The numerical results hold great promise (1) to achieve an equivalent level of accuracy, quality, and quantity of information while using fewer resources, or (2) to achieve a higher level of accuracy, quality, and quantity of information while using the same amount of resources.
Using a relational processor and an XPath processor to evaluate joint queries
Authors: Royi Ronen, Oded Shmueli
Venue: Proceedings of the 2008 EDBT workshop on Database technologies for handling XML information on the web (2008)

Conjunctive queries (CQs) are a common abstraction for many query languages (or significant parts thereof) for relational data, XML data or both, such as SQL, XPath, XQuery, XSLT and SQL4X. This work considers the joint querying of relational and XML data by adding an XPath predicate to the CQ formalism. CQs are a basic building block of query processing understanding, and in that respect, adding an XPath predicate is a natural extension. Relational and XML data are "connected" either via references to XML nodes that are stored in relations (essentially oids, usually the result of previous queries) or via atomic text values. Then, relational and XML data are jointly referenced by allowing variables to be shared by relational and XPath predicates. Our approach is that of co-processing of the query using an XPath processor and a relational data processor which operate separately, each on its type of data. The algorithms use known bindings to variables in the query in order to efficiently use the separate processors. We design and compare two such algorithms for evaluating CQs with XPath predicates. Column-Based On-Demand reduces the query evaluation problem to performing a join over ordinary relations. Quick On-Demand offers a controlled way to explore the evaluation space, using a heuristic procedure in the course of a step-wise evaluation of the query. Both algorithms avoid the need to use a sophisticated cost model as required by a standard evaluation procedure. We experimented with both algorithms on various size databases and query types. Each of the new algorithms performs best for different query types and both appear very promising. To calibrate, we transformed the queries to XQuery. Interestingly, the execution times are often favorable for our (not highly optimized) system.
Joint Study Programme on Accessible Web Design
Authors: Barbara Hengstberger, Klaus Miesenberger, Mario Batusic, Noura Chelbat, Andrés Rodríguez García
Venue: Proceedings of the 11th international conference on Computers Helping People with Special Needs (2008)

This paper presents an international study programme on accessible web design which is under development in the framework of an EU --- Erasmus Project. The paper will discuss the strong need for a Europe-wide academic training programme on accessible web design, the curriculum, the teaching and eLearning tools, the accreditation and the additional benefit of the programme.
A Modal-Logic Based Graph Abstraction
Authors: Jörg Bauer, Iovka Boneva, Marcos E. Kurbán, Arend Rensink
Venue: Proceedings of the 4th international conference on Graph Transformations (2008)

Infinite or very large state spaces often prohibit the successful verification of graph transformation systems. Abstract graph transformation is an approach that tackles this problem by abstracting graphs to abstract graphs of bounded size and by lifting application of productions to abstract graphs. In this work, we present a new framework of abstractions unifying and generalising existing takes on abstract graph transformation. The precision of the abstraction can be adjusted according to the properties to be verified facilitating abstraction refinement. We present a modal logic defined on graphs, which is preserved and reflected by our abstractions. Finally, we demonstrate the usability of the framework by verifying a graph transformation model of a firewall.
An ontological model of device function: industrial deployment and lessons learned
Authors: Yoshinobu Kitamura, Yusuke Koji, Riichiro Mizoguchi
Venue: Applied Ontology (2006)

Functionality is one of the key concepts of knowledge about artifacts. Functional knowledge shows a part of designer's intention (so-called design rationale), and thus its sharing among engineers plays a crucial role in team-activities in engineering practice. Aiming at promoting engineering knowledge management, we have developed an ontological modeling framework of functional knowledge, which includes an ontology of device and function and a controlled vocabulary. This framework has been successfully deployed in a manufacturing company in daily engineering activities. In the first part of this paper, we discuss some ontological issues concerning the functionality of artifacts, and redefine the notion of function as a role. In the second part, we discuss some lessons learned in the actual deployment of this framework and two extensions based on such experience. One extension is a lexical layer for functional terms intended to help engineers select appropriate functional concepts and to facilitate the use of domain-specific terms familiar to them. The other extension is the establishment of ontological modeling guidelines, which help engineers commit to the relevant ontologies and describe models compliant with them.
3-D Motion Estimation for Positioning from 2-D Acoustic Video Imagery
Authors: H. Sekkati, S. Negahdaripour
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part II (2007)

We address the problem of estimating 3-D motion from acoustic images acquired by high-frequency 2-D imaging sonars deployed in underwater. Utilizing a planar approximation to scene surfaces, two-view homography is the basis of a nonlinear optimization method for estimating the motion parameters. There is no scale factor ambiguity, unlike the case of monocular motion vision for optical images. Experiments with real images demonstrate the potential in a range of applications, including target-based positioning in search and inspection operations.
On Scheduling Policies for Streams of Structured Jobs
Authors: Aldric Degorre, Oded Maler
Venue: Proceedings of the 6th international conference on Formal Modeling and Analysis of Timed Systems (2008)

We study a class of scheduling problems which combines the structural aspects associated with task dependencies, with the dynamic aspects associated with ongoing streams of requests that arrive during execution. For this class of problems we develop a scheduling policy which can guarantee bounded accumulation of backlog for all admissible request streams. We show, nevertheless, that no such policy can guarantee bounded latency for all admissible request patterns, unless they admit some laxity.
The Diffusion and Impacts of the Internet and E-Commerce in Taiwan
Authors: Tain-Jy Chen
Venue: I-WAYS - The Journal of E-Government Policy and Regulation (2003)

The most important driver behind e-commerce in Taiwan appears to be international competitive pressure; this is especially evident in the manufacturing sector. E-commerce is more widely diffused in the manufacturing sector in Taiwan, compared to the retail/wholesale and financial sectors, which are more domestic-market oriented. The primary motivating factor behind e-commerce adoption is to better serve customers, and the Internet also allows firms to improve the efficiency of their internal processes and to enhance staff productivity levels. In comparison with manufacturing firms in other countries, Taiwanese firms are more concerned with improving forward linkages to their customers than improving backward linkages to their suppliers. The purpose of the adoption of e-commerce is predominantly to broaden their customer base by exploring new marketing channels, or to create competition for the traditional channels. This stands in sharp contrast to global firms, which tend to use it mainly to improve the traditional marketing channels.
Handling Dynamic Networks Using Evolution in Ant-Colony Optimization
Authors: Christopher Roach, Ronaldo Menezes
Venue: Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence (2008)

Ant Colony Optimization (ACO) is a popular meta-heuristic for solving combinatorial optimization problems. ACO uses the concept of ants foraging for food to find good solutions to these types of problems. ACO has been successfully applied to many problems, from the traveling salesman problem (TSP), to the problem of network routing. However, it has been pointed out that ACO does not perform as well as other heuristics in very dynamic problems. At first, this statement seems strange but a close look reveals that the nature strategy that inspires the ACO meta-heuristic has an important element that is lacking in ACO: evolution. This paper proposes a new algorithm, named Evolutionary Ant Colony Optimization (EACO), that combines ACO with elements of traditional Genetic Algorithms (GA), namely: selection, recombination, and mutation. Individual ants are endowed with a genotype that is allowed to evolve through generations of the population. In doing this, the EACO algorithm adds another element of optimization to the ACO algorithm that allows the individual agents (ants) in the algorithm to improve their behavior over several generations. Our results demonstrate that EACO can indeed overcome the hurdles faced by the original ACO.
A User Model of Psycho-physiological Measure of Emotion
Authors: Olivier Villon, Christine Lisetti
Venue: Proceedings of the 11th international conference on User Modeling (2007)

The interpretation of physiological signals in terms of emotion requires an appropriate mapping between physiological features and emotion representations. We present a user model associating psychological and physiological representation of emotion in order to bring findings from the psychophysiology domain into User-Modeling computational techniques. We discuss results based on an experiment we performed based on bio-sensors to get physiological measure of emotion, involving 40 subjects.
Optimization in 3D Scene Acquisition with Two Mobile Robots
Authors: Nera González, José M. Sebastián, Jorge Artieda
Venue: Proceedings of the 5th international conference on Image Analysis and Recognition (2008)

This article presents a method for cooperative reconstruction of three-dimensional scenes using multiple views. Although the use of multiple views is one of the most applied in the 3D scenes interpretation, its use with a single mobile robot does not guarantee the perfect localization of the environment, due to odometry errors. Also, the reconstruction of dynamic environments is not allowed for a single robot, which takes views in different instants. This work proposes a system formed by multiple robots to get a cooperative reconstruction of the scene. The robots decide the best strategy to acquire the image to get the best reconstruction using an objective function defined. In this function, mainly are considered uncertainty of the reconstruction and view points. The result of this optimization is the next position of the robots.
A General-Purpose Mobile Framework for Situated Learning Services on PDA
Authors: Seong Baeg Kim, Kyoung Mi Yang, Cheol Min Kim
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Recently, as ubiquitous technology has been developed rapidly, a specific application service considering users' situations has been becoming the focus of attention. As a field of a typical situation-based application, we focus on situated learning using a mobile device. A u-learning system can provide learners with individualized learning at any time in any place. In this paper, we propose a general-purpose mobile framework suitable for situated learning on PDA with RFID mobile system. Specially, we examine three aspects in making the framework. First, we investigate how learners obtain and access customized learning contents suitable for them. Second, we construct a mobile middleware for RFID on PDA. Finally, we devise the application-specific system for situated learning.
Decentralized supply chain planning framework for third party logistics partnership
Authors: Hosang Jung, F. Frank Chen, Bongju Jeong
Venue: Computers and Industrial Engineering (2008)

As the complexity of a supply chain continuously increases and the importance of prompt delivery to end customers grows, an independent company, so called a third party logistics provider, to perform all or part of a manufacturer's product distribution function has emerged. In this situation, collaboration between the manufacturer and the third party logistics provider is indispensable in order to generate a supply chain plan. However, information sharing for collaboration between two companies is getting complicated by privacy issues associated with information provided by and shared among different independent companies. In this paper, we propose a decentralized supply chain planning framework based on minimal-information sharing between the manufacturer and the third party logistics provider. Extensive computational tests have shown that the proposed approach generates a good supply chain plan in terms of total costs comparing with the ideal centralized supply chain planning approach.
Integration of Learning and Reasoning Techniques
Authors: Bart Selman
Venue: Inductive Logic Programming: 16th International Conference, ILP 2006, Santiago de Compostela, Spain, August 24-27, 2006, Revised Selected Papers (2007)

Since the early days of AI, automated reasoning has been a rather elusive goal. In fact, up till the early nineties, general inference beyond hundred variable problems appeared infeasible. Over the last decade, we have witness a qualitative change in the field: current reasoning engines can handle problems with over a million variables and several millions of constraints. I will discuss what led to such a dramatic scale-up, and how progress in reasoning technology has opened up a range of new applications in AI and computer science in general. I will also discuss initial progress on the use of learning techniques in reasoning engines and the remaining challenges for obtaining a true integration of learning and reasoning.