ppxscal/embedding_network huggingface dataset:
A Knowledge Management Optimization Problem Using Marginal Utility in a Metric Space with Conceptual Graphs
Authors: Jeffrey A. Schiffel
Venue: Proceedings of the 15th international conference on Conceptual Structures: Knowledge Architectures for Smart Applications (2007)

Knowledge management has emerged as a field blending a systems approach with methods drawn from organizational management and learning. In contrast, knowledge representation, a branch of artificial intelligence, is grounded in formal methods. Research in the separate behavioral and the structural disciplines - knowledge management and knowledge engineering - have not traditionally cross-pollinated, preventing the development of many practical uses. Organization managers lack guidance in where to direct improvement efforts targeted at specific groups of knowledge workers. Demonstrated here is Knowledge Improvement Measurement System, an optimization solution that employs marginal utility theory in a metric space, and formal reasoning via software agents realized in conceptual graphs. This allows for repeated evaluation of knowledge improvement measurements. The KIMS method can measure activities that organize and encourage knowledge sharing to achieve competitive advantage. The solution takes into account the body of knowledge related to human understanding and learning, and formal methods of knowledge organization.
A context-aware personal desktop assistant
Authors: Hung H. Bui, Federico Cesari, Daniel Elenius, David N. Morley, Sriraam Natarajan, Shahin Saadati, Eric Yeh, Neil Yorke-Smith
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems: demo papers (2008)

We demonstrate an intelligent personal assistant agent that has been developed to aid a busy knowledge worker in managing time commitments and performing tasks. The PExA agent draws on a diverse set of AI technologies that are linked within the SPARK BDI agent framework. We focus on our agent's ability to provide assistance within the context of current user activities, based on its recognition of user workflows and their progress, and on its context-sensitive proactive suggestions. We have instrumented a common suite of desktop applications so that, endowed with a sophisticated workflow tracker, PExA has the ability to pervasively monitor the user's desktop activities. PExA follows and responds to the user's progress on shared tasks, and is highly user-centric in its support for user needs and its adaptivity to user working style and preferences.
List colorings with measurable sets
Authors: Jan Hladký, Daniel Kráal, Jean-Sébastien Sereni, Michael Stiebitz
Venue: Journal of Graph Theory (2008)

The measurable list chromatic number of a graph G is the smallest number &xi; such that if each vertex v of G is assigned a set L(v) of measure &xi; in a fixed atomless measure space, then there exist sets $c(v)\subseteq L(v)$ such that each c(v) has measure one and $c(v)\cap c(v') = \emptyset$ for every pair of adjacent vertices v and v'. We provide a simpler proof of a measurable generalization of Hall's theorem due to Hilton and Johnson [J Graph Theory 54 (2007), 179&ndash;193] and show that the measurable list chromatic number of a finite graph G is equal to its fractional chromatic number. &copy; 2008 Wiley Periodicals, Inc. J Graph Theory 59: 229&ndash;238, 2008
Non-stationary Signal Noise Suppression Based on Wavelet Analysis
Authors: Wei Qu, Xin Jia, Shibing Pei, Jie Wu
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

This paper addresses the problem of non-stationary signal noise suppression, represents the conception of wavelet transformation and puts forward two kinds of measurements to evaluate the effectiveness of noise suppression. Comparison experiments for noise suppression are made using Fourier analysis and Wavelet analysis. Simulation result shows that Wavelet analysis is more suitable for non-stationary analysis.
Opening Up Education: The Collective Advancement of Education through Open Technology, Open Content, and Open Knowledge
Authors: Toru Iiyoshi, M. S. Vijay Kumar
Venue:  (2008)

Given the abundance of open education initiatives that aim to make educational assets freely available online, the time seems ripe to explore the potential of open education to transform the economics and ecology of education. Despite the diversity of tools and resources already availablefrom well-packaged course materials to simple games, for students, self-learners, faculty, and educational institutionswe have yet to take full advantage of shared knowledge about how these are being used, what local innovations are emerging, and how to learn from and build on the experiences of others. Opening Up Education argues that we must develop not only the technical capability but also the intellectual capacity for transforming tacit pedagogical knowledge into commonly usable and visible knowledge: by providing incentives for faculty to use (and contribute to) open education goods, and by looking beyond institutional boundaries to connect a variety of settings and open source entrepreneurs. These essays by leaders in open education describe successes, challenges, and opportunities they have found in a range of open education initiatives. They approachfrom both macro and micro perspectivesthe central question of how open education tools, resources, and knowledge can improve the quality of education. The contributors (from leading foundations, academic institutions, associations, and projects) discuss the strategic underpinnings of their efforts first in terms of technology, then content, and finally knowledge. They also address the impact of their projects, and how close they come to achieving a vision of sustainable, transformative educational opportunities that amounts to much more than pervasive technology. Contributors: Richard Baraniuk, Randy Bass, Trent Batson, Dan Bernstein, John Seely Brown, Barbara Cambridge, Tom Carey, Catherine Casserly, James Dalziel, Bernadine Chuck Fong, Richard Gale, Gerard Hanley, Diane Harley, Mary Huber, Pat Hutchings, Toru Iiyoshi, David Kahle, M. S. Vijay Kumar, Andy Lane, Diana Laurillard, Stuart Lee, Steve Lerman, Marilyn Lombardi, Phil Long, Clifford Lynch, Christopher Mackie, Anne Margulies, Owen McGrath, Flora McMartin, Shigeru Miyagawa, Diana Oblinger, Neeru Paharia, Cheryl Richardson, Marshall Smith, Candace Thille, Edward Walker, and David Wiley Through the support of the Carnegie Foundation for the Advancement of Teaching, an electronic version of this book is openly available under a Creative Commons license on The MIT Press website.
Exploratory investigation of student attitudes toward technology based on Wi-Fi usage
Authors: Yong Lu, A. Rao Korukonda
Venue: International Journal of Mobile Learning and Organisation (2008)

The purpose of this study was to investigate how college students use Wi-Fi technology and to address relative benefits and barriers of Wi-Fi in student mobile learning. This research combined qualitative and quantitative research methods and the participants were college students. Preliminary findings indicated students who used the Wi-Fi in class held significantly more positive attitudes toward this technology compared to students who had not yet used it. No significant differences were found between graduate students and undergraduate students. The study also found that Wi-Fi technology can promote student-centred learning in five areas: mobility, learning environment, flexibility, collaboration, and communication.
Precise Eye Localization with AdaBoost and Fast Radial Symmetry
Authors: Wencong Zhang, Hong Chen, Peng Yao, Bin Li, Zhenquan Zhuang
Venue: Computational Intelligence and Security: International Conference, CIS 2006, Guangzhou, China, November 3-6, 2006, Revised Selected Papers (2007)

The accuracy of face alignment affects greatly the performance of a face recognition system. Since the face alignment is usually conducted using eye positions, the algorithm for accurate eye localization is therefore essential for the accurate face recognition. In this paper, we propose a novel algorithm for eye localization. Based on the special gray distribution in the eye region, proper AdaBoost detection is adaptively trained to segment the eye region. After getting the region of eyes, a fast radial symmetry operator is used to precisely locate the center of eyes. Experimental results show that the method can accurately locate the eyes, and it is robust to the variations of face poses, expressions, illuminations and accessories.
An RTP/RTCP based approach for multimedia group and inter-stream synchronization
Authors: Fernando Boronat Seguí, Juan Carlos Guerri Cebollada, Jaime Lloret Mauri
Venue: Multimedia Tools and Applications (2008)

Most multimedia group and inter-stream synchronization techniques define or use proprietary protocols with new control messages. Many multimedia applications have been developed using RTP/RTCP as the standard for transmission of multimedia streams over IP networks. Instead of defining a new protocol, we propose the use of RTP/RTCP to provide synchronization. We take advantage of the feedback capabilities provided by RTCP and the ability to extend the protocol by extending and creating RTCP messages containing synchronization information. We have implemented our proposal and tested it in our University WAN. Our experiments have shown that network load resulting from synchronization is minimized and that asynchronies are within acceptable limits for multimedia applications.
Sheet metal forming global control system based on artificial vision system and force-acoustic sensors
Authors: P. Fillatreau, F. X. Bernard, A. Aztiria, E. Sáenz de Argandoña, C. García, N. Arana, A. Izaguirre
Venue: Robotics and Computer-Integrated Manufacturing (2008)

Forming processes are manufacturing processes based on deformation of raw material applying pressure in one or several stages until getting the final product. This process depends on many factors, e.g. process parameters, material properties or lubrication, leading to possible defective parts. Correct forming of parts is very important as any defective part may result in big economical losses, e.g. the return of a complete set of parts or the loss of some clients. Thus, in our European Craft Pro2Control project, leading German, French, Italian and Spanish companies, universities and forming industries are defining and implementing a zero-defect forming control system, minimizing costs and maximizing the throughput of parts. Commonly integrated sensors (force and acoustic) do not allow to detect all types of faults in this kind of applications. Thus, we consider a multisensor approach, associating artificial vision to the previous sensors. Vision may allow better understanding and/or characterizing of force and acoustic measures, while it can detect faults that the other sensors may not. The design of the artificial vision system has been separated into a pre- and post-processing part. The former consists of a proprietary intelligent camera built up by one of the project leaders (Delta Technologies Sud-Ouest or DTSO), which contains a CMOS sensor, FPGAs, RAMs and a USB 2.0 connection, and where parallelizable bottlenecked image-processing algorithms are implemented (whenever image-processing algorithms can be implemented on FPGAs, processing times will be about 100 times faster than on a standard microprocessor). The latter consists of proprietary non-bottlenecked image-processing algorithms, implemented on a regular PC, using open source libraries. This approach provides a fully mastered development, and guarantees durability and maintainability of the system (non-dependence on commercial items), as well as a new scale of production throughputs. The system is customizable, and the multisensor approach will improve fault detection robustness.
Flow-Sensitive Loop-Variant Variable Classification in Linear Time
Authors: Yixin Shou, Robert Engelen, Johnnie Birch
Venue: Languages and Compilers for Parallel Computing: 20th International Workshop, LCPC 2007, Urbana, IL, USA, October 11-13, 2007, Revised Selected Papers (2007)

This paper presents an efficient algorithm for classifying generalized induction variables and more complicated flow-sensitive loop-variant variables that have arbitrary conditional update patterns along multiple paths in a loop nest. Variables are recognized and translated into closed-form functions, such as linear, polynomial, geometric, wrap-around, periodic, and mixer functions. The remaining flow-sensitive variables (those that have no closed forms) are bounded by tight bounding functions on their value sequences by bounds derived from our extensions of the Chains of Recurrences (CR#) algebra. The classification algorithm has a linear worst-case execution time in the size of the SSA region of a loop nest. Classification coverage and performance results for the SPEC2000 benchmarks are given and compared to other methods.
A randomized algorithm for the joining protocol in dynamic distributed networks
Authors: Colin Cooper, Ralf Klasing, Tomasz Radzik
Venue: Theoretical Computer Science (2008)

We describe a randomized algorithm for assigning neighbours to vertices joining a dynamic distributed network. The aim of the algorithm is to maintain connectivity, low diameter and constant vertex degree. On joining each vertex donates a constant number of tokens to the network. These tokens contain the address of the donor vertex. The tokens make independent random walks in the network. A token can be used by any vertex it is visiting to establish a connection to the donor vertex. This allows joining vertices to be allocated a random set of neighbours although the overall vertex membership of the network is unknown. The network we obtain in this way is robust under adversarial deletion of vertices and edges and actively reconnects itself. One model we consider is a network constructed in this fashion, in which vertices join but never leave. If t is the size of the network, then the diameter of the network is O(logt) for all t, with high probability. As an example of the robustness of this model, suppose an adversary deletes edges from the network leaving components of size at least t^1^/^2^+^@d. With high probability the network reconnects itself by replacing lost edges using tokens from the token pool.
A high performance parallel Radon based OFDM transceiver design and simulation
Authors: Waleed Al-Jawhar, Abbas Hasan Kattoush, Sulaiman M. Abbas, Ali T. Shaheen
Venue: Digital Signal Processing (2008)

A major goal of the next-generation wireless communication systems is the development of a reliable high-speed wireless communication system that supports high user mobility. They must focus on increasing the link throughput and the network capacity. In this paper a novel, spectral efficient system is proposed for generating and transmitting two-dimensional (2-D) orthogonal frequency division multiplexing (OFDM) symbols through 2-D inter-symbol interference (ISI) channel. Instead of conventional data mapping techniques, discrete finite Radon transform (FRAT) is used as a data mapping technique due to the increased orthogonality offered. As a result, the proposed structure gives a significant improvement in bit error rate (BER) performance. The new structure was tested and a comparison of performance for serial one-dimensional (1-D) Radon based OFDM and parallel 2-D Radon based OFDM is made under additive white Gaussian noise (AWGN), flat, and multi-path selective fading channels conditions. It is found that Radon based parallel 2-D OFDM has better speed and performance than serial 1-D Radon based OFDM.
Privacy Preserving Data Mining Research: Current Status and Key Issues
Authors: Xiaodan Wu, Chao-Hsien Chu, Yunfeng Wang, Fengli Liu, Dianmin Yue
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Recent advances in the Internet, in data mining, and in security technologies have gave rise to a new stream of research, known as privacy preserving data mining (PPDM). PPDM technologies allow us to extract relevant knowledge from a large amount of data, while hide sensitive data or information from disclosure. Several research questions have often being asked: (1) what kind of option available for privacy preserving? (2) Which method is more popular? (3) how to measure the performance of these algorithms? And (4) how effective of these algorithms in preserving privacy? To help answer these questions, we conduct an extensive review of 29 recent references from years 2000 to 2006 for analysis.
A new constructive approximation in log-map turbo decoder
Authors: Shahab Asoodeh
Venue: Proceedings of the 7th WSEAS International Conference on Electronics, Hardware, Wireless and Optical Communications (2008)

Although the Log-MAP algorithm has a high capability in correcting errors amongst turbo decoding algorithms, but the existence of ln(ċ) and exp(ċ) functions in this algorithm, decreases the speed and makes its implementation difficult. For solving this problem, new methods for approximating these two complex functions has been suggested. A new method in this area has been proposed in this paper that can estimate the functions with high accuracy and minimum computational complexity. Furthermore in order to prevent overflowing of the amounts of short variables during decoding, a new and simple method about normalizing the amounts of forward and backward metrics has been presented in this paper.
Digital Breast Tomosynthesis Parenchymal Texture Analysis for Breast Cancer Risk Estimation: A Preliminary Study
Authors: Despina Kontos, Predrag R. Bakic, Andrea B. Troxel, Emily F. Conant, Andrew D. Maidment
Venue: Proceedings of the 9th international workshop on Digital Mammography (2008)

Studies with mammograms have demonstrated a relationship between parenchymal texture and breast cancer risk. Although promising, texture analysis in mammograms is limited by the effect of tissue superimposition. Digital Breast Tomosynthesis (DBT) is a novel tomographic x-ray breast imaging modality that alleviates the effect of tissue superimposition. We explore the potential advantages of DBT texture analysis for breast cancer risk estimation. We analyzed bilateral DBT and DM images from 39 women, and compared the performance of the computed texture features in (i) reflecting characteristic parenchymal properties, and (ii) correlating to mammographic breast density, an established surrogate of breast cancer risk. Strong texture correlation was observed between contralateral and ipsilateral breasts, indicating that parenchymal properties are potentially inherent to an individual woman. Compared to DM, DBT texture features demonstrated a stronger correlation with breast density. Although preliminary, our results show that DBT texture analysis could potentially improve breast cancer risk estimation.
Design and Synthesis of a High-Speed Hardware Linked-List for Digital Image Processing
Authors: Jinbo Xu, Yong Dou, Jian Song, Yang Zhang, Fei Xia
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

To deal with the problem of maintaining variable data set in digital image processing, this paper brings forward a general hardware structure for linked-list. It is designed to accomplish the commonly used functions and some more complicated functions of the linked-list data structure. In order to fully utilize the limited memory resources in embedded hardware platform, we propose a memory recycle scheme to reuse the memory space where the data have been deleted. In our work, the length of the linked-list is parameterized and can be reconfigured. The structure is mapped onto an FPGA chip. Experimental results show that our proposal works functionally well. Only few hardware resources are used and it consumes pretty low power. According to the length of the list, clock speed from 100MHzup to 200MHz is achieved. Compared with the software linked-list structure in PC, our proposal in FPGA achieves 170.4 times of speedup in average. Our design has been utilized into people tracking system successfully.
Fast discovery of sequential patterns in large databases using effective time-indexing
Authors: Ming-Yen Lin, Sue-Chen Hsueh, Chia-Wen Chang
Venue: Information Sciences: an International Journal (2008)

Sequential pattern mining algorithms can often produce more accurate results if they work with specific constraints in addition to the support threshold. Many systems implement time-independent constraints by selecting qualified patterns. This selection cannot implement time-dependent constraints, because the support computation process must validate the time attributes of every data sequence during mining. Therefore, we propose a memory time-indexing approach, called METISP, to discover sequential patterns with time constraints including minimum-gap, maximum-gap, exact-gap, sliding window, and duration constraints. METISP scans the database into memory and constructs time-index sets for effective processing. METISP uses index sets and a pattern-growth strategy to mine patterns without generating any candidates or sub-databases. The index sets narrow down the search space to the sets of designated in-memory data sequences, and speed up the counting of potential items within the indicated ranges. Our comprehensive experiments show that METISP has better efficiency, even with low support and large databases, than the well-known GSP and DELISP algorithms. METISP scales up linearly with respect to database size.
Band criteria and recursive tests of complete controllability and observability of linear algebraic-differentiable systems
Authors: M. Sh. Misrikhanov, V. N. Ryabchenko
Venue: Automation and Remote Control (2008)

New criteria are introduced of complex controllability and observability of controllable linear stationary algebraic-differentiable systems with many inputs and outputs, which reduce to the calculation of the rank of special band matrices. Recursive tests are set up, which permit reducing computational expenses in the verification for the fulfillment of the conditions of complete controllability and observability of algebraic-differentiable systems of a large dimension.
An Autonomous Clustering-Based Hierarchical Routing Using Decentralized Route Information Management Scheme for Mobile Ad Hoc Networks
Authors: Ryotaro Oda, Tomoyuki Ohta, Yoshiaki Kakuda
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

Many clustering schemes and hierarchical routing protocols have been proposed in order to manage large-scaled ad hoc networks efficiently. However, there is the possibility that in hierarchical routings based on the clustering scheme a node called a clusterhead which manages the cluster has much overhead because it must handle all the information on the routing tables for intra-routing and inter-rouging, and the cluster structure. As a result, many packets are lost in the vicinity of the clusterhead, and they cannot provide the stable packet delivery. Therefore, we have proposed the clustering scheme called autonomous clustering, hierarchical routing protocols based on the autonomous clustering, and the decentralized route information management scheme for hierarchical routing protocols to mitigate the overhead of clusterheads. This paper presents the autonomous clustering-based hierarchical routing using the decentralized route information management scheme and shows the effectiveness through the simulation experiments.