ppxscal/embedding_network huggingface dataset:
Information revelation and privacy in online social networks
Authors: Ralph Gross, Alessandro Acquisti, H. John Heinz,  III
Venue: Proceedings of the 2005 ACM workshop on Privacy in the electronic society (2005)

Participation in social networking sites has dramatically increased in recent years. Services such as Friendster, Tribe, or the Facebook allow millions of individuals to create online profiles and share personal information with vast networks of friends - and, often, unknown numbers of strangers. In this paper we study patterns of information revelation in online social networks and their privacy implications. We analyze the online behavior of more than 4,000 Carnegie Mellon University students who have joined a popular social networking site catered to colleges. We evaluate the amount of information they disclose and study their usage of the site's privacy settings. We highlight potential attacks on various aspects of their privacy, and we show that only a minimal percentage of users changes the highly permeable privacy preferences.
Improving Experiential Learning with Mobile Technologies
Authors: Chih Hung Lai, Jie Chi Yang, Tak Wai Chan, Chin Wen Ho, Fei Ching Chen, Jing San Liang
Venue: Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (2005)

The study designed a system and a flow of learning to motivate and guide students to conduct experiential learning with mobile technologies. Students of two classes of fifth-grade at an elementary school participated in the experiment. Thirty-four students of one class conducted learning with PDAs in school garden while thirty-two students of another class conducted in a condition without PDAs. The data shows the advantage of supported with mobile technologies for the acquisition of knowledge. Most of hypotheses are confirmed in the study. These findings show just how important the mobile technology is which helps to improve the learning achievement of experiential learning.
Approximate majorization and fair online load balancing
Authors: Ashish Goel, Adam Meyerson, Serge Plotkin
Venue: ACM Transactions on Algorithms (TALG) (2005)

This article relates the notion of fairness in online routing and load balancing to vector majorization as developed by Hardy et al. [1929]. We define &alpha;-supermajorization as an approximate form of vector majorization, and show that this definition generalizes and strengthens the prefix measure proposed by Kleinberg et al. [2001] as well as the popular notion of max-min fairness.The article revisits the problem of online load-balancing for unrelated 1-&infin; machines from the viewpoint of fairness. We prove that a greedy approach is O(log n)-supermajorized by all other allocations, where n is the number of jobs. This means the greedy approach is globally O(log n)-fair. This may be contrasted with polynomial lower bounds presented by Goel et al. [2001] for fair online routing.We also define a machine-centric view of fairness using the related concept of submajorization. We prove that the greedy online algorithm is globally O(log m)-balanced, where m is the number of machines.
Camera-Based Document Image Retrieval as Voting for Partial Signatures of Projective Invariants
Authors: Tomohiro Nakai, Koichi Kise, Masakazu Iwamura
Venue: Proceedings of the Eighth International Conference on Document Analysis and Recognition (2005)

We propose a method of document image retrieval using digital cameras. The proposed method takes as input a part or the whole of a document acquired as a query by a digital camera, and retrieves a document image that includes the query. For this purpose, it is required to solve the problem of "perspective distortion" of images, as well as to establish a way of matching parts of document images flexibly. These are achieved based on the following characteristics of the proposed method: (1) Indexing of document images using the projective invariants called the "cross-ratios", (2) Retrieval as voting for partial signatures of document images defined by the cross-ratios. From experimental results using digital cameras with high and low resolutions, we demonstrate the effectiveness of the proposed method.
Scalable Grid Service Discovery based on UDDI
Authors: Sujata Banerjee, Sujoy Basu, Shishir Garg, Sukesh Garg, Sung-Ju Lee, Pramila Mullan, Puneet Sharma
Venue: Proceedings of the 3rd international workshop on Middleware for grid computing (2005)

Efficient discovery of grid services is essential for the success of grid computing. The standardization of grids based on web services has resulted in the need for scalable web service discovery mechanisms to be deployed in grids Even though UDDI has been the de facto industry standard for web-services discovery, imposed requirements of tight-replication among registries and lack of autonomous control has severely hindered its widespread deployment and usage. With the advent of grid computing the scalability issue of UDDI will become a roadblock that will prevent its deployment in grids. In this paper we present our distributed web-service discovery architecture, called DUDE (Distributed UDDI Deployment Engine). DUDE leverages DHT (Distributed Hash Tables) as a rendezvous mechanism between multiple UDDI registries. DUDE enables consumers to query multiple registries, still at the same time allowing organizations to have autonomous control over their registries.. Based on preliminary prototype on PlanetLab, we believe that DUDE architecture can support effective distribution of UDDI registries thereby making UDDI more robust and also addressing its scaling issues. Furthermore, The DUDE architecture for scalable distribution can be applied beyond UDDI to any Grid Service Discovery mechanism.
Simulation techniques for travel demand forecasting
Authors: Fred L. Mannering
Venue: ACM SIGSIM Simulation Digest (1981)

The article presents an overview of some simulation techniques that were developed for use in a recent research effort. The objective of the research was to create a modeling system with the power to evaluate the travel-related impacts of various proposed transportation energy contingency plans, such as increased fuel taxes, reduced speed limits, mandatory vehicle modification, and so on. Traditional modeling efforts in this area have had substantial data requirements which have made their use awkward or impossible in many situations. The use of various simulation procedures in the present model has substantially reduced data requirements while maintaining a high level of forecasting capability.
User model-driven architecture for information retrieval in construction project management
Authors: Haiyan Xie
Venue:  (2005)

Numerous software systems are designed to facilitate information retrieval and communication among people in the construction industry. It is arguable that user experiences and preferences are given enough consideration in a lot of them. To design a system serving the information retrieval needs of the construction industry, designers must determine the information that construction personnel need to retrieve from various sources, and in what kinds of formats it has to be displayed. The next problem is how to formalize the user model for a given class of users (such as vice president, project manager, or estimator) to direct information retrieval. Detailed case studies were used to specify and formalize user model(s) for construction personnel. The goal of this research is to improve the level of satisfactory results obtained from a conventional or advanced information retrieval (IR) system by modeling the user's information retrieval approach and leveraging the user model into structured knowledge. The users' needs will be analyzed and modeled by the use-case modeling method, and then the relationships in the use case will be used to address the IR system with a more relevant request. The user model proposed in this research is based on the implementation of user research in software development. The Unified Modeling Language (UML) is implemented to build up a formal user model to generate a fast and smooth transition from the user needs to the software products. Furthermore, the Java object-oriented language is used to build up a configurable navigator pattern to retrieve information. Coding and system programming for information retrieval can be achieved based on these specifications. Five validation cases were designed to test the UMDA system from the aspects of user involvement and satisfaction, usability, sensitivity, search scope, and information retrieval performance. The validation process demonstrated that the UMDA system provides, in all the considered cases, the needed representations that are usable and that it supports effective data access and data collection of project management information. It also demonstrated that the interaction style of the UMDA system allows in many cases for efficient user interaction.
A Multi-Label Voting Algorithm for Neuro-Fuzzy Classifier Ensembles with Applications in Visual Arts Data Mining
Authors: Daniel Neagu, Shuai Zhang, Catalin Balescu
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

The term Visual Arts Data Mining defines a framework for Data Mining techniques applied to learn and discover patterns in Visual Arts collections. Its results can be widely used by Visual Arts market, museums and art galleries. This paper proposes a multi-label voting algorithm to identify similar Visual Arts objects studied using neuro-fuzzy classifiers. The algorithm integrates predictions of experts trained on clusters of heterogeneous collections of data. It combines predictions of the modular ensemble of classifiers by identifying hierarchical votes for most similar classes. Experimental results show better performances than individual global models. Relationships between some Visual Arts patterns are inferred. We also compare the results obtained for few fusion versions of our algorithm with other methods applied on IRIS and Glass benchmarks The results show that our algorithm has at least similar performance to other schemes on all data sets and adds flexibility to cases where classifiers' expertise overlaps on unions of disjunctive sets of the universe of discourse.
Combining Character Classifiers Using Member Classifiers Assessment
Authors: Jerzy Sas, Michal Luzyna
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

In the paper, the method of combining character classifiers for handprinted text recognition is presented. The combination rule is based on member classifiers reliability assessment. The assessment can be based on probabilistic classifier properties or it can use similarity measures individually evaluated for the character currently being recognized. The approach presented here follows soft classification paradigm, where the classifier not merely selects single class, but it provides the vector of support values corresponding to character likelihood. The proposed methods have been tested and compared in recognizing letters from polish alphabet, including nine difficult do recognize diacritic characters.
Developmental learning with applications to attention, task transfer and user presence detection
Authors: Juyang Weng
Venue:  (2005)

How to build an intelligent machine has fascinated researchers for more than half a century. To tackle this problem, scientists have taken one of the four approaches: knowledge-based, learning-based, behavior-based and evolution-based. However, autonomous mental development (AMD) of robots did not receive sufficient attention. Motivated by animal and human autonomous mental development from infancy to adulthood, a developmental paradigm for robots has recently been proposed. With this paradigm, a robot develops its mental skills through real-time, online interactions with the environment. We call such a robot a developmental robot. My work focuses on motivational system and sensorimotor learning. The major contributions of this work include: (1) Proposed and implemented the Developmental, Observation driven, Self-Aware, Self-Effecting. Markov Decision Process (DOSASE MDP) model, which integrates multimodal sensing, action-imposed learning, reinforcement learning, and communicative learning. (2) Integrated novelty and reinforcement learning into a robotic value system (motivational system) for the first time. As an important part of AMD, a value system signals the occurrence of salient sensory inputs, modulates the mapping from sensory inputs to action outputs, and evaluates candidate actions. (3) Proposed and implemented the Locally Balanced Incremental Hierarchical Discriminant Regression (IHDR) algorithm as the engine of cognitive mapping for learning in non-stationary environments. Based upon the above architecture and basic techniques, we have designed and implemented a prototype robot that learns the following cognitive behaviors: (1) Visual attention via novelty and rewards. We treat visual attention as a behavior guided by the value system. No salient feature is predefined but instead novelty based on experience, which is applicable to any task. (2) Covert perceptual capability development for vision-based navigation. An agent develops its covert capability via reinforcement learning through interactions with trainers. (3) Cross-task learning in developmental settings. A developmental robot learns multiple tasks incrementally and uses acquired knowledge to speed up learning new tasks. (4) Audio/Visual User presence detection. The developmental learning paradigm has been applied to a developmental agent, which detects human activities in an office using multimodal context information. The work reported in this thesis serves as a starting point of the on-going research on developmental learning.
On the Approximation of Markov Chains to Determine the Probability of Extinction of a Genotype
Authors: Gabriel V. Orman
Venue: Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications (2005)

As it is known a precise definition of the Brownian motion involves a measure on the path space, such that it is possible to put the Brownian motion on a firm mathematical foundation. In this paper we refer to an appplication of asymptotic theory of stochastic differential equations in mathematical genetics. The construction of the Brownian motion as a limit of a rescaled random walk can be generalized to a class of Markov chains.
Modeling and Reduction of Gate Leakage during Behavioral Synthesis of NanoCMOS Circuits
Authors: Saraju P. Mohanty, Elias Kougianos
Venue: Proceedings of the 19th International Conference on VLSI Design held jointly with 5th International Conference on Embedded Systems Design (2006)

For a nanoCMOS of sub-65nm technology, where the gate oxide (SiO2) thickness is very low, the gate leakage is one of the major components of power dissipation. In this paper, we provide analytical models to describe the tunneling current and propagation delay of behavioral level components considering various physical effects in the absence of foundry data. Subsequently, we explore the use of multiple oxide thickness resources as a technique for the reduction of gate leakage. In particular, we introduce a behavioral datapath scheduler that maximizes the utilization of higher gate oxide thickness resources. We characterize behavioral components for both 65nm and 45nm technologies in order to study the trend of tunneling current as technology scales, and provide them as inputs to the scheduler. We carried out extensive experiments for several benchmarks and observed significant reduction in gate leakage.
An Efficient Placement and Routing Technique for Fault-Tolerant Distributed Embedded Computing
Authors: Roozbeh Jafari, Foad Dabiri, Majid Sarrafzadeh
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

This paper presents an efficient technique for placement and routing of sensors/actuators and processing units in a grid network. The driver application that we present is a medical jacket which requires an extremely high level of robustness and fault tolerance. The power consumption of such jacket is another key technological constraint. Our proposed interconnection network is a mesh of wires. A jacket made of fabric and wires would be susceptible to accidental damage via tears. By modeling the tears, we evaluate the probability of having failures on every segment of wires in our mesh interconnection network. Then we study two problems of placement and routing in the sensor networks such that the fault tolerance is maximized while the power consumption is minimized. We develop efficient integer linear programming (ILP) formulations to address these problems and perform both placement and routing simultaneously. This ensures that the solution is a lower bound for both problems. We evaluate the effectiveness of our proposed techniques on a variety of benchmarks.
Direct Intentions: The Effects of Input Devices on Collaboration around a Tabletop Display
Authors: Vicki Ha, Kori M. Inkpen, Tara Whalen, Regan L. Mandryk
Venue: Proceedings of the First IEEE International Workshop on Horizontal Interactive Human-Computer Systems (2006)

This paper explores users' interpersonal interactions during collaboration around a tabletop display, in order to better understand the affordances offered by this medium. We investigate participants' collaborative interactions, particularly related to the type of input device provided. Stylus, mouse, and touch-based interactions were provided to allow multiple people to simultaneously interact with tabletop systems in a series of studies, and we observed how the choice of direct or indirect input device affected collaboration. In this paper we discuss how direct and indirect input affect natural interactions, ergonomics, territoriality, gestures, and awareness of both intention and action. The findings from our studies are valuable for those who deploy and design tabletop systems, by providing them with guidelines for appropriate choice of input device.
Grido- An Architecture for a Grid-based Overlay Network
Authors: Shirshanka Das, Alok Nandan, Michael G. Parker, Giovanni Pau, Mario Gerla
Venue: Proceedings of the Second International Conference on Quality of Service in Heterogeneous Wired/Wireless Networks (2005)

Grido is an architecture that targets a network operator intending to provide enhanced services to its customers. This is achieved by setting up a "backbone" overlay network. A backbone overlay is a set of Internet hosts dedicated to providing overlay services. A network operator can view Grido as a sandbox for rapid prototyping and market adoption assessment of novel services. In the past, overlay networks have been designed to mitigate deployment issues of functionalities such as multicast and QoS at the network layer. Grido provides a WS-Agreement based negotiation interface complying with the current Global Grid Forum (GGF) standards. We propose to use a novel virtual coordinates-assisted overlay construction and maintenance protocol. We demonstrate using simulations, that Grido incurs a low latency overhead while maintaining sparse connectivity on the backbone overlay. Grido also incurs low overhead for virtual coordinates estimation and chooses the closest 5% overlay node to any IP address, 95% of the time.
Clio: A Schema Mapping Tool for Information Integration
Authors: Mauricio Hernandez, Lucian Popa, Howard Ho, Felix Naumann
Venue: Proceedings of the 8th International Symposium on Parallel Architectures,Algorithms and Networks (2005)

Information integration typically requires the construction of complex artifacts like federated databases, ETL scripts, data warehouses, applications for accessing multiple data sources, and applications that ingest or publish XML. For many companies, it is one of the most complicated IT tasks they face today. To reduce the overall cost, intelligent tools are needed to simplify this difficult task. Clio is a semi-automatic tool for schema mapping and data integration developed at IBM Almaden Research Center over the past few years. It takes source and target schemas as input, which may describe relational or XML data models. Via a graphical SchemaViewer, a user can then interactively specify attribute correspondences between the source and target schemas. An AttributeMatcher component helps suggest such correspondences, based on the similarity of both attribute names and attribute values. Once the user has specified correspondences, Clio generates SQL, SQL/XML, XQuery or XSLT on the fly to implement the specified transformation, which is guaranteed to produce output data that conforms to the target schema. In this talk, we will first describe and demonstrate some basic features of Clio. In particular, we will describe the abstracted problems and the algorithms behind the AttributeMatcher component. Then, we will describe additional research problems abstracted from the area of schema mapping and information integration, with an emphasis on graph algorithms and issues on scalability and parallelism.
Generation of Quiz Objects (QO) with a Quiz Engine Developer (QED)
Authors: Kevin Johnson, Timothy Hall, Derek O'Keeffe
Venue: Proceedings of the IEEE International Workshop on Wireless and Mobile Technologies in Education (2005)

This paper introduces a novel open source platform independent Quiz Engine Developer (QED). This is a standards compliant (IMS QTI) system which permits the user to develop questions at the lowest level of granularity (termed Quiz Objects). Quizzes are a natural symbiotic partner to learning and therefore are equally as important to complete the learning experience. These Quiz Objects are structured similarly to Learning Objects (IEEE LOM) and similarly this object-orientated approach supports interoperability and reusability by the development of quiz banks that are searchable and shareable between independent developers. The quiz engine that has been designed is web-based, cross platform (mobile & desktop) and feature rich and allows several modes of interaction with the user (e.g. template driven, power user). An important aspect of the system is its ability to search individual quiz objects, which allows greater reuse of questions.
Correlating intrusion detection events: a data mining and profiling approach
Authors: Michael C. Johnson
Venue:  (2005)

In an increasingly connected and networked world, the need to secure computers, networks, and the information that they contain, maintain and transport is growing rapidly. Information security professionals attempt to meet this need by implementing protective systems to keep unauthorized personnel and organizations out, monitoring systems to detect unauthorized activity that gets by the protective systems, and reactive systems to help recover gracefully as well as to continuously improve all the systems in the Protect - Detect - React cycle. This dissertation focuses on the detection phase and discusses a novel approach to intrusion detection involving correlation of low level events from multiple sources into higher-level events and scenarios followed by analysis of the scenarios using profiling and data mining approaches. A prototype using events from a network sensor and events from a host sensor was implemented to test the feasibility of the proposed approach.