ppxscal/embedding_network huggingface dataset:
Requirements for Supporting Individual Human Creativity in the Design Domain
Authors: Uta Lösch, Julie Dugdale, Yves Demazeau
Venue: Proceedings of the 8th International Conference on Entertainment Computing (2009)

Creativity is an important activity in many professional and leisure domains. This article presents a first step towards a system which will provide a set of tools for enhancing the individual creative abilities of the user in a design task. We have identified aspects which are characterise individual creativity: motivation, domain knowledge, externalization, inspiration and analogies, and requirements handling. Based on these aspects we have defined requirements and suggest associated system functionalities.
Game-Like Simulations for Online Adaptive Learning: A Case Study
Authors: Javier Torrente, Pablo Moreno-Ger, Baltasar Fernández-Manjón, Ángel Blanco
Venue: Proceedings of the 4th International Conference on E-Learning and Games: Learning by Playing. Game-based Education System Design and Development (2009)

Serious games are becoming a powerful tool in education. However, there are still open issues needing further research to generalize the use of videogames and game-like simulations in the educational system. On the one hand, how to take advantage of the videogames' inherent adaptation behaviour in order to maximize the effectiveness of the learning experiences is still a world worth to be explored. On the other, there is still a need to develop mechanisms to track and evaluate the performance of the students when they use these learning tools. Finally, it is necessary to elaborate further game-based learning architectures that facilitate the delivery and distribution of the games to the students. In this paper we propose how to deal with all these issues taking also into account other relevant aspects such as development cost and instructor implication. This is exemplified with the HCT game, produced in cooperation with professors of the Complutense University School of Medicine at Madrid.
An Enhanced Statistical Approach to Identifying Photorealistic Images
Authors: Patchara Sutthiwan, Jingyu Ye, Yun Q. Shi
Venue: Proceedings of the 8th International Workshop on Digital Watermarking (2009)

Computer graphics identification has gained importance in digital era as it relates to image forgery detection and enhancement of high photorealistic rendering software. In this paper, statistical moments of 1-D and 2-D characteristic functions are employed to derive image features that can well capture the statistical differences between computer graphics and photographic images. YCbCr color system is selected because it has shown better performance in computer graphics classification than RGB color system and it has been adopted by the most popularly used JPEG images. Furthermore, only Y and Cb color channels are used in feature extraction due to our study showing features derived from Cb and Cr are so highly correlated that no need to use features extracted from both Cb and Cr components, which substantially reduces computational complexity. Concretely, in each selected color component, features are extracted from each image in both image pixel 2-D array and JPEG 2-D array (an 2-D array consisting of the magnitude of JPEG coefficients), their prediction-error 2-D arrays, and all of their three-level wavelet subbands, referred to as various 2-D arrays generated from a given image in this paper. The rationale behind using prediction-error image is to reduce the influence caused by image content. To generate image features from 1-D characteristic functions, the various 2-D arrays of a given image are the inputs, yielding 156 features in total. For the feature generated from 2-D characteristic functions, only JPEG 2-D array and its prediction-error 2-D array are the inputs, one-unit-apart 2-D histograms of the JPEG 2-D array along the horizontal, vertical and diagonal directions are utilized to generate 2-D characteristic functions, from which the marginal moments are generated to form 234 features. Together, the process then results in 390 features per color channel, and 780 features in total Finally, Boosting Feature Selection (BFS) is used to greatly reduce the dimensionality of features while boosts the machine learning based classification performance to fairly high.
Privacy-Preserving Telemonitoring for eHealth
Authors: Mohamed Layouni, Kristof Verslype, Mehmet Tahir Sandıkkaya, Bart Decker, Hans Vangheluwe
Venue: Proceedings of the 23rd Annual IFIP WG 11.3 Working Conference on Data and Applications Security XXIII (2009)

Advances in communication technology have opened a myriad of new possibilities for the remote delivery of healthcare. This new form of service delivery, not only contributes to the democratization of healthcare, by reaching far-away populations, but also makes it possible for elderly and chronically-ill patients to have their health monitored while in the comfort of their homes. Despite all of these advantages, however, patients are still resisting the idea of medical telemonitoring. One of the main obstacles facing the adoption of medical telemonitoring, is the concern among patients that their privacy may not be properly protected. We address this concern, and propose a privacy-preserving telemonitoring protocol for healthcare. Our protocol allows patients to selectively disclose their identity information, and guarantees that no health data is sent to the monitoring centre without the patients' prior approval. The approval process can be automated, and requires only an initial configuration by the patient.
Suitability of Using Self-Organizing Neural Networks in Configuring P-System Communications Architectures
Authors: Abraham Gutiérrez, Soledad Delgado, Luis Fernández
Venue: Advances in Neuro-Information Processing: 15th International Conference, ICONIP 2008, Auckland, New Zealand, November 25-28, 2008, Revised Selected Papers, Part II (2009)

Nowadays, it is possible to find out different viable architectures that implements P Systems in a distributed cluster of processors. These proposed architectures have reached a certain compromise between the massively parallelism character of the system and the evolution step times. They are based in the distribution of several membranes in each processor, the use of proxies to control the communication between membranes and mainly, the suitable distribution of the architecture in a balanced tree of processors. For a given P-system and K processors, there exists a great volume of possible distributions of membranes over these. The main disadvantage related with these architectures is focused in the selection of the distribution of membranes that minimizes the external communications between them and maximizes the parallelism grade. In this paper, we suggest the use of Self-Organizing Neural Networks (SONN) with growing capability to help in this selection process for a given P-system.
Designing function blocks for distributed process planning and adaptive control
Authors: Lihui Wang, Yijun Song, Qiaoying Gao
Venue: Engineering Applications of Artificial Intelligence (2009)

The objective of this research is to develop methodologies and a framework for distributed process planning and adaptive control using function blocks. Facilitated by a real-time monitoring system, the proposed methodologies can be applied to integrate with functions of dynamic scheduling in a distributed environment. A function block-enabled process planning approach is proposed to handle dynamic changes during process plan generation and execution. This paper focuses mainly on distributed process planning, particularly on the development of a function block designer that can encapsulate generic process plans into function blocks for runtime execution. As function blocks can sense environmental changes on a shop floor, it is expected that a so-generated process plan can adapt itself to the shop floor environment with dynamically optimized solutions for plan execution and process monitoring.
Surviving the War for Talent in Asia: How Innovation Can Help, 1st edition
Authors: Christina Ooi
Venue:  (2009)

Find and Keep the Outstanding Leaders You Need to Win in Asia! Specific solutions for recruiting and retaining great people in North Asia, South Asia, Australia, and New Zealand Seven new case studies, plus in-depth insight into IBMs experience For every CxO, director, manager, HR leader, strategist, or consultant working with or for companies in Asia Right now, even as Western economies struggle, Asia is experiencing an unprecedented war for talent. Organizations are competing ever more aggressively to find the right people, motivate them, and retain their highest performers. Theres only one route to success in todays Asian talent wars: innovation. In this book, one of IBMs top Asia Pacific managers identifies powerful talent management innovations that are working in Asia right now for dozens of the regions most forward-looking enterprises. Christina SS Ooi begins by revealing why Asian talent shortages are even worse than they appear. Next, she presents breakthrough solutions from industries ranging from IT to hospitality, manufacturing to telecommunications. Learn how winning companies are recruiting more effectively through partnerships and word-of-mouth...bringing innovation to onboarding and training...understanding the changing needs and diverse lifestyles of todays Asian employees...shaping corporate culture and engaging their employees...developing great leaders and keeping them.
A Study on CRM Technology Implementation and Application Practices
Authors: ChunNian Liu, XiaoWen Zhu
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 02 (2009)

CRM is a multi-disciplinary concept. Its successful implementation involves many aspects. This paper highlights the implementation from the technology level and contributes to some successful factors in CRM application. At last, it gives some guidance for future study on CRM.
On a pair of job-machine assignment problems with two stages
Authors: A. Volgenant, C. W. Duin
Venue: Computers and Operations Research (2010)

We consider two assignment problems in which a number of jobs are assigned to the same number of machines that operate in parallel, but in two stages. They are known as the '2-stage time minimizing assignment problem' and the 'bi-level time minimizing assignment problem'. These problems have the following characteristics in common: *Each of the machines processes one job (non-preemptively, without help of other machines). *The job-machine assignments are partitioned into two successive stages of parallel processing. *The objective is to minimize the makespan, the sum of the primary and the secondary completion time. Both problems can be solved by (a series of) assignment problems. We improve the related computational complexities by applying reoptimization. Under some conditions a quadratic complexity is derived. We introduce a parameter weighing the relative importance of the primary and the secondary cost per time unit. The parametric problems can be solved, for all parameter values simultaneously, within the same reduced time complexity bounds. Scope and purpose: As it is often important to solve problems quickly, it is essential to reduce the computational complexity of available algorithms, as far as possible. We consider two problems which arise when parallel scheduling is done in two successive stages; they can be tackled by solving a series of linear assignment problems. We show that they can be solved more efficiently, using properties of the classical linear assignment problem. In practice, the cost per time unit in the two stages need not be equal. A parameter controlling the ratio between these costs defines a parametric version of each problem. The algorithms of reduced time complexity can be extended to these parametric problem versions.
Short Communication: Generating subproblems in branch and bound algorithms for parallel machines scheduling problem
Authors: Sang-Oh Shim
Venue: Computers and Industrial Engineering (2009)

A branch and bound algorithm (B&B) has been widely used in various discrete and combinatorial optimization fields. To obtain optimal solutions as soon as possible for scheduling problems, three tools, which are branching, bounding and dominance rules, have been developed in the B&B algorithm. One of these tools, a branching is a method for generating subproblems and directly determines size of solution to be searched in the B&B algorithm. Therefore, it is very important to devise effective branching scheme for the problem. In this note, a survey of branching schemes is performed for parallel machines scheduling (PMS) problems with n independent jobs and m machines and new branching schemes that can be used for identical and unrelated PMS problems, respectively, are suggested. The suggested branching methods show that numbers of generated subproblems are much smaller than that of other methods developed earlier and therefore, it is expected that they help to reduce a lot of CPU time required to obtain optimal solutions in the B&B algorithm.
A Fast Algorithm for Computing a Nearly Equitable Edge Coloring with Balanced Conditions
Authors: Akiyoshi Shioura, Mutsunori Yagiura
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

We discuss the nearly equitable edge coloring problem on a multigraph and propose an efficient algorithm for solving the problem, which has a better time complexity than the previous algorithms. The coloring computed by our algorithm satisfies additional balanced conditions on the number of edges used in each color class, where conditions are imposed on the balance among all edges in the multigraph as well as the balance among parallel edges between each vertex pair. None of the previous algorithms are guaranteed to satisfy these balanced conditions simultaneously.
ChangeRefinery: Assisted Refinement of High-Level IT Change Requests
Authors: David Trastour, Robert Fink, Fen Liu
Venue: Proceedings of the 2009 IEEE International Symposium on Policies for Distributed Systems and Networks (2009)

The IT Infrastructure Library (ITIL) is a set of best practices that are widely accepted for IT service management. Change management is a core ITIL process that oversees the handling of IT changes and ensures that all change requests are carefully prioritized and authorized, that business and technical impacts are understood, and that required resources are available. During this process, IT operations teams first need to understand the change requests that are generated by business and IT personnel. They must then develop and execute concrete IT change plans for each request. The increasingly large and complex IT environment (people, technology and processes) presents a number of challenges to the efficient and effective design of the ever higher volume of IT changes: Change requests can be ill-defined, company policies and best practices are not systematically captured and enforced, manually designing changes is time consuming and error-prone. To overcome these issues we propose in this paper an automated planning based approach to change design. We illustrate how change knowledge can be represented to encode best practices and how to refine high-level change requests into concrete plans. A prototypical implementation shows the feasibility of the approach and demonstrates the concept of a change catalogue that can be presented to business users.
Web Application Tests with Selenium
Authors: Andreas Bruns, Andreas Kornstadt, Dennis Wichmann
Venue: IEEE Software (2009)

Using Selenium, Web acceptance-test designers have a tool that programmatically reflects business structure much better than protocol-level tools would, while avoiding the pitfalls of capture-and-replay tools.
Test collection management and labeling system
Authors: Eunyee Koh, Andruid Kerne, Sarah Berry
Venue: Proceedings of the 9th ACM symposium on Document engineering (2009)

In order to evaluate the performance of information retrieval and extraction algorithms, we need test collections. A test collection consists of a set of documents, a clearly formed problem that an algorithm is supposed to provide solutions to, and the answers that the algorithm should produce when executed on the documents. Defining the association between elements in the test collection and answers is known as labeling. For mainstream information retrieval problems, there are publicly available test collections which have been maintained for years. However, the scope of these problems, and thus the associated test collections, is limited. In other cases, researchers need to build, label, and manage their own test collections, which can be a tedious and error-prone task. We were building test collections of HTML documents, for problems in which the answers that the algorithm supplies is a sub-tree of the DOM (Document Object Model). To lighten the burden of this task, we developed a test collection management and labeling system (TCMLS), to facilitate usability in the process of building test collections, applying them to validate algorithms, and potentially sharing them across the research community.
Using a probabilistic model of discourse relations to investigate word order variation
Authors: Cassandre Creswell
Venue: Proceedings of the 2004 ACL Workshop on Discourse Annotation (2004)

Like speakers of any natural language, speakers of English potentially have many different word orders in which to encode a single meaning. One key factor in speakers' use of certain non-canonical word orders in English is their ability to contribute information about syntactic and semantic discourse relations. Explicit annotation of discourse relations is a difficult and subjective task. In order to measure the correlations between different word orders and various discourse relations, this project utilizes a model in which discourse relations are approximated using a set of lower-level linguistic features, which are more easily and reliably annotated than discourse relations themselves. The featural model provides statistical evidence for the claim that speakers use non-canonicals to communicate information about discourse structure.
Dynamic Dual-Tracer PET Reconstruction
Authors: Fei Gao, Huafeng Liu, Yiqiang Jian, Pengcheng Shi
Venue: Proceedings of the 21st International Conference on Information Processing in Medical Imaging (2009)

Although of important medical implications, simultaneous dual---tracer positron emission tomography reconstruction remains a challenging problem, primarily because the photon measurements from dual tracers are overlapped. In this paper, we propose a simultaneous dynamic dual---tracer reconstruction of tissue activity maps based on guidance from tracer kinetics. The dual---tracer reconstruction problem is formulated in a state---space representation, where parallel compartment models serve as continuous---time system equation describing the tracer kinetic processes of dual tracers, and the imaging data is expressed as discrete sampling of the system states in measurement equation. The image reconstruction problem has therefore become a state estimation problem in a continuous---discrete hybrid paradigm, and H ¿ filtering is adopted as the estimation strategy. As H ¿ filtering makes no assumptions on the system and measurement statistics, robust reconstruction results can be obtained for the dual-tracer PET imaging system where the statistical properties of measurement data and system uncertainty are not available a priori, even when there are disturbances in the kinetic parameters. Experimental results on digital phantoms, Monte Carlo simulations and physical phantoms have demonstrated the superior performance.
Printing spatially-varying reflectance
Authors: Wojciech Matusik, Boris Ajdin, Jinwei Gu, Jason Lawrence, Hendrik P. A. Lensch, Fabio Pellacini, Szymon Rusinkiewicz
Venue: ACM SIGGRAPH Asia 2009 papers (2009)

Although real-world surfaces can exhibit significant variation in materials --- glossy, diffuse, metallic, etc. --- printers are usually used to reproduce color or gray-scale images. We propose a complete system that uses appropriate inks and foils to print documents with a variety of material properties. Given a set of inks with known Bidirectional Reflectance Distribution Functions (BRDFs), our system automatically finds the optimal linear combinations to approximate the BRDFs of the target documents. Novel gamut-mapping algorithms preserve the relative glossiness between different BRDFs, and halftoning is used to produce patterns to be sent to the printer. We demonstrate the effectiveness of this approach with printed samples of a number of measured spatially-varying BRDFs.
Next-Generation Passive Optical Network Based on OFDM Transmission
Authors: Zhihua Zheng, Zongjue Qian, Guochu Shou, Yihong Hu
Venue: Proceedings of the 2009 WASE International Conference on Information Engineering - Volume 01 (2009)

We investigate passive optical network (PON) based on optical orthogonal frequency division multiplexing (OFDM) transmission as a solution for next-generation optical access network. Compared with other PONs, the system improves the bandwidth efficiency and increases the flexibility to allocate resource dynamically among various services. We present simulation results on the bit error rate (BER) performance of OFDM signal with quadrature amplitude modulation (QAM) after 20km fiber transmission. It is shown that significant progress mainly relies on the implementation of high-speed digital signal processing (DSP).
Bound consistency for binary length-lex set constraints
Authors: Pascal Van Hentenryck, Justin Yip, Carmen Gervet, Grégoire Dooms
Venue: Proceedings of the 23rd national conference on Artificial intelligence - Volume 1 (2008)

The length-lex representation has been recently proposed for representing sets in Constraint Satisfaction Problems. The length-lex representation directly captures cardinality information, provides a total ordering for sets, and allows bound consistency on unary constraints to be enforced in time Õ(c), where c is the cardinality of the set. However, no algorithms were given to enforce bound consistency on binary constraints. This paper addresses this open issue. It presents algorithms to enforce bound consistency on disjointness and cardinality constraints in time O(c3). Moreover, it presents a generic bound-consistency algorithm for any binary constraint S which requires Õ(c2) calls to a feasibility subroutine for S.
A direct proof of the confluence of combinatory strong reduction
Authors: René David
Venue: Theoretical Computer Science (2009)

I give a proof of the confluence of combinatory strong reduction that does not use the one of @l-calculus. I also give simple and direct proofs of a standardization theorem for this reduction and the strong normalization of simply typed terms.
A new way of thinking about computational thinking
Authors: Owen Astrachan
Venue: Journal of Computing Sciences in Colleges (2009)

Computational Thinking has emerged as an enduring metaphor in teaching and thinking about Computer Science since Jeanette Wing brought the term to our attention in a 2006 CACM article. Computational thinking involves abstraction, but a definition that is too abstract does not help in explaining computational thinking to someone who doesn't already have an intuitive idea of what it is: