ppxscal/embedding_network huggingface dataset:
Classifiers for Vegetation and Forest Mapping with Low Resolution Multiespectral Imagery
Authors: Marcos Ferreiro-Armán, Lourenço P. Bandeira, Julio Martín-Herrero, Pedro Pina
Venue: Proceedings of the 3rd Iberian conference on Pattern Recognition and Image Analysis, Part I (2007)

This paper deals with the evaluation of the performance of a set of classifiers on multispectral imagery with low dimensionality and low spatial and spectral resolutions. The original Landsat TM images and other 4 transformed sets are classified by 5 supervised and 2 unsupervised methods. The results for 7 land cover classes are compared and the performances of the methods for each set of input data are discussed.
Culture-Specific First Meeting Encounters between Virtual Agents
Authors: Matthias Rehm, Yukiko Nakano, Elisabeth André, Toyoaki Nishida
Venue: Proceedings of the 8th international conference on Intelligent Virtual Agents (2008)

We present our concept of integrating culture as a computational parameter for modeling multimodal interactions with virtual agents. As culture is a social rather than a psychological notion, its influence is evident in interactions, where cultural patterns of behavior and interpretations mismatch. Nevertheless, taking culture seriously its influence penetrates most layers of agent behavior planning and generation. In this article we concentrate on a first meeting scenario, present our model of an interactive agent system and identify, where cultural parameters play a role. To assess the viability of our approach, we outline an evaluation study that is set up at the moment.
Template Semantics for Model-Based Notations
Authors: Jianwei Niu, Joanne M. Atlee
Venue: IEEE Transactions on Software Engineering (2003)

We propose a template-based approach to structuring the semantics of model-based specification notations. The basic computation model is a nonconcurrent, hierarchical state-transition machine (HTS), whose execution semantics are parameterized. Semantics that are common among notations (e.g., the concept of an enabled transition) are captured in the template, and a notation's distinct semantics (e.g., which states can enable transitions) are specified as parameters. The template semantics of composition operators define how multiple HTSs execute concurrently and how they communicate and synchronize with each other by exchanging events and data. The definitions of these operators use the template parameters to preserve notation-specific behavior in composition. Our template is sufficient to capture the semantics of basic transition systems, CSP, CCS, basic LOTOS, a subset of SDL88, and a variety of statecharts notations. We believe that a description of a notation's semantics using our template can be used as input to a tool that automatically generates formal analysis tools.
Web services for digital rights management and copyright protection in digital media
Authors: Dimitrios K. Tsolis, Theodore S. Papatheodorou
Venue: Proceedings of the 3rd international conference on Digital Interactive Media in Entertainment and Arts (2008)

The paper focuses on the implementation of an advanced digital rights management (DRM) system which supported by web services offers copyright protection and management of digital media. The main components of the DRM system are a digital image library, which offers specialized services for storing and searching and a copyright protection and digital rights management subsystem for the digitized media based on innovative watermarking and web technologies.
Investigating the Use of Voice and Text Chat in a Social Television System
Authors: Joe Tullio, Gunnar Harboe, Noel Massey
Venue: Proceedings of the 6th European conference on Changing Television Environments (2008)

We tested a social television system with both voice and text communication in the field for one week, in four households. Participants expressed a preference for the freeform communication features over an earlier system with restricted communication options. Use of the communication features was nevertheless sporadic. Text was used more often than voice communication. However, both were usually used in combination. The in-home context had marked effects on the usage patterns, and we observed issues of privacy and identity verification.
Multicriteria programming in medical diagnosis and treatments
Authors: Crina Grosan, Ajith Abraham, Stefan Tigan
Venue: Applied Soft Computing (2008)

This paper deals with a special case of multicriteria optimization problems. The problems studied come from the medical domain and are of a very important practical relevance. One of the problems refers to the ranking of treatments for the Trigeminal Neuralgia. The second problem refers to a hierarchy of risk factors for Bronchial Asthma. The most common way to deal with a multiobjective optimization problem is to apply Pareto dominance relationship between solutions. But in the cases studied here, a decision cannot be made just by using Pareto dominance. In one of the experiments, all the potential solutions are nondominated (and we need to clearly find a hierarchy of these solutions) and in the second experiment most of the solutions are nondominated between them. We propose a novel multiple criteria procedure and then an evolutionary scheme is applied for solving the problems. Results obtained by the proposed approach in a very simple way are same as the results (or even better) obtained by applying weighted-sum method. The advantage of the proposed technique is that it does not require any additional information about the problem (like weights for each criteria in the case of weighted-sumapproach).
Short-time independent component analysis for blind separation of speech sources
Authors: Ching Pak Chung
Venue:  (2007)

Independent Component Analysis (ICA) has long been regarded as a powerful technique for speech source separation. In practice, however, speaker moving or reverberant environments may necessitate ICA to be implemented in short time intervals, which makes the fundamental assumption of sources' independence collapse in ICA. This leads to two important but often overlooked problems, namely: (1) excursion of global optimum from the desired solution and (2) diffusion of local optima in search of the de-mixing matrix. These two problems occur in most practical situations and greatly degrade the performance of the existing ICA algorithms. Based on the insight into the effect on the aforementioned problems by the input sources as well as the mixing channel, three basic short time Local Optima Distribution (LOD) types are investigated. Information is derived from the characteristics of these LOD types for: (1) choosing simultaneous or sequential ICA algorithm; (2) shrinking feasible search region; and (3) producing possible initial points in search of the de-mixing matrix. As a result, the technique of LOD-based ICA is developed in this thesis to assign different procedures according to the LOD type of the observed short time mixtures. The analytical and simulation results demonstrated that more accurate de-mixing matrix estimation could be obtained; thereby producing improved separation performance. Among all the three LOD types, the Dominant LOD manifests to be with comparatively higher efficiency in yielding accurate separation performance. The production mechanism of the Dominant LOD indicates that higher energy ratio of sources helps to build this type of LOD. Considering the sparse energy distribution of speech signals in the time-frequency domain, the Dominant LOD may arise in some short time subbands even though it appears to be Non-dominant LOD in its fullband. Therefore the proposed LOD-based ICA is extended to the frequency subbands for more opportunities to attain such Dominant LOD type. The effectiveness of the proposed short time LOD-based ICA is validated by applying it to a speaker-moving model and a mixing system with abrupt changes, which approaches the practical applications better since the mixing system is not always constant as in standard ICA model. We have also explored the separation task with noise-contaminated speech signals. This suggests us that: other than the long time analysis, the short time analysis may provide an alternative means with extra information for separation when the independence information is impaired and subsequently fails to yield the desirable separation performance.
Efficiently Testing Sparse GF(2) Polynomials
Authors: Ilias Diakonikolas, Homin K. Lee, Kevin Matulef, Rocco A. Servedio, Andrew Wan
Venue: Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I (2008)

We give the first algorithm that is both query-efficient and time-efficient for testing whether an unknown function f: {0,1}n &rarr;{0,1} is an s-sparse GF(2) polynomial versus &epsilon;-far from every such polynomial. Our algorithm makes poly(s,1/&epsilon;) black-box queries to f and runs in time n &middot;poly(s,1/&epsilon;). The only previous algorithm for this testing problem [DLM + 07] used poly(s,1/&epsilon;) queries, but had running time exponential in s and super-polynomial in 1/&epsilon;. Our approach significantly extends the "testing by implicit learning" methodology of [DLM + 07]. The learning component of that earlier work was a brute-force exhaustive search over a concept class to find a hypothesis consistent with a sample of random examples. In this work, the learning component is a sophisticated exact learning algorithm for sparse GF(2) polynomials due to Schapire and Sellie [SS96]. A crucial element of this work, which enables us to simulate the membership queries required by [SS96], is an analysis establishing new properties of how sparse GF(2) polynomials simplify under certain restrictions of "low-influence" sets of variables.
Integrated simulation method for investment decisions of micro production systems
Authors: Bernd Scholz-Reiter, Michael L&#x00fc;tjen, Jens Heger
Venue: Microsystem Technologies (2008)

From a production logistics point of view, micro production systems need special methods due to their special requirements and characteristics. In this paper a new approach for the assessment of different investment scenarios during the planning period with integrated cost simulation is presented. In particular, the use of single-purpose and multi-purpose machines and the cost effectiveness of function integration are examined. Thereby alternative machine pool configurations and optimal costs can be analysed, determined and taken into consideration for investment decisions.
Knowledge-Supported Segmentation and Semantic Contents Extraction from MPEG Videos for Highlight-Based Annotation, Indexing and Retrieval
Authors: Jinchang Ren, Juan Chen, Jianmin Jiang, Stan S. Ipson
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Automatic recognition of highlights from videos is a fundamental and challenging problem for content-based indexing and retrieval applications. In this paper, we propose techniques to solve this problem by using knowledge supported extraction of semantic contents, and compressed-domain processing is employed for efficiency. Firstly, video shots are detected by using knowledge-supported rules. Then, human objects are detected via statistical skin detection. Meanwhile, camera motion like zoom in is identified. Finally, highlights of zooming in human objects are extracted and used for annotation, indexing and retrieval of the whole videos. Results from large data of test videos have demonstrated the accuracy and robustness of the proposed techniques.
Pushing Anderson's Envelope: The Modal Logic of Ascription
Authors: Davide Grossi
Venue: Proceedings of the 9th international conference on Deontic Logic in Computer Science (2008)

The paper proposes a formal analysis of the ascriptive view of norms as resulting from pulling together Anderson's reductionist approach, the analysis of counts-as, and a novel modal approach to the formal representation of languages in logic. This unifying attempt results in the definition of a new form of reduction of deontic logic based on counts-as statements. Such result is discussed also in the light of Jørgensen's dilemma.
Dynamic Process Visualization
Authors: James Foley, Charles McMath
Venue: IEEE Computer Graphics and Applications (1986)

An increasingly important use of computer graphics is to monitor such real-world processes as manufacturing plants, power plants, and refineries. As in many uses of computer graphics, the development of this application area has been programmer-intensive. As a consequence, system are being developed more slowly than is desired and they cost more than necessary. This article discusses some of the key issues and requirements involved in designing productivity tools for use in constructing monitoring systems. We have developed a prototype Process Visualization System (PVS) that allows nonprogrammers to construct graphics displays, and to establish relationships between these displays and changes in the data describing the process being monitored. With this system, customized, dynamically updated scenes can be created. The PVS allows users to construct symbols, to place them on the screen, and to connect them to data items from the monitored processes' database. Using this system frees the end-user from reliance on programmers, and allows the user to quickly display the data items of interest.
Mathematical models for surface characterization of machining processes
Authors: Peter Maass, Bernd Kuhfu&#x00df;, Oltmann Riemer
Venue: Microsystem Technologies (2008)

The reliable production of micro-parts by cold forming requires the optimization of all steps of this process chain. The quality of the final products in particular depends on the tribological properties of the moulds. Mathematical models for describing the cutting process as well as for characterizing the resulting tribological surface properties are needed for assisting the production of suitable moulds. Classical models for cutting processes are based on a description of the static behaviour. However, the high-quality demands of production processes in the micro-range require to include the influence of vibrations based on a dynamic model. The main sources for vibrations are imbalances in the rotating parts of the machinery and external forces which are introduced during the production process itself, e.g. impact forces due to interrupted cuts. This article describes a basic model, which includes the influence of vibrations. In addition, a non-standard approximation technique is used for characterizing surfaces.
On solvable groups and Cayley graphs
Authors: Edward Dobson
Venue: Journal of Combinatorial Theory Series B (2008)

Let @f be Euler's phi function. Let n be a square-free positive integer such that gcd(n,@f(n))=q, q a prime, and if p|n is prime, then q^2@?(p-1). We prove that a vertex-transitive graph @C of order n is isomorphic to a Cayley graph of order n if and only if Aut(@C) contains a transitive solvable subgroup.
Surface reconstruction from imperfect point models
Authors: Arie E. Kaufman
Venue:  (2007)

This thesis presents work on surface reconstruction from imperfect point models. Here "imperfections" refer to the cases such as missing information about point nomials, unknown level of noise, irregular sampling, and/or non-manifold surfaces, resulting in incorrect reconstruction results using existing approaches. Due to the diversity of point acquisition approaches (laser range finders, computer vision methods, etc), imperfections occur often in practice and pose a great challenge to surface reconstruction algorithms. In this thesis, several novel algorithms, targeted towards different imperfections, are proposed. To recover the geometry and the texture of insufficiently sampled regions, we exploit user knowledge about the planarity and the symmetry of man-made objects in indoor scenes and fill the holes in a natural way. After that, there might still be some remaining holes. We then develop a hole filling algorithm as a post processing module to complete the resulting mesh. This algorithm interpolates the interior of a hole based on its vicinity. It can also be used as an independent module for mesh repairing. In addition, we propose a distance-field based algorithm to handle very noisy points without point normals. A global distance field is constructed by propagating the information from interior/exterior regions in a hierarchical and adaptive way. A mesh is extracted later as the zero-set surface of the distance field. Furthermore, a generalized approach is introduced to naturally handle both manifold and non-manifold surfaces, including both non-orientable surfaces and surfaces with boundaries. The input points are first voxelized, enabling easy classification of the local shape for each point. We then locate non-manifold regions (junctions and boundaries) and take special care to mesh them. We also propose to enforce the regularity of the resulting mesh reconstructed from point models. Using a nearly isometric point parameterization, we are capable of controlling the shape of output triangles. The aforementioned algorithms cover a wide range of imperfections and we believe they could handle many problems encountered in practice.
Transnational Education Programs: Student Reflections on a Fully-Online Versus a Hybrid Model
Authors: Iwona Miliszewska
Venue: Proceedings of the 1st international conference on Hybrid Learning and Education (2008)

With rapid expansion of the transnational education market, more and more universities join the ranks of transnational education providers, or expand their transnational education offerings. Many of those providers regard online provision of their programs as an economic alternative to face-to-face teaching. Do the transnational students support this view? This paper discusses student responses to the fully-online provision of education programs in several important transnational markets: Hong Kong, Malaysia, Singapore, and Vietnam. The paper reports on a study of the perceptions of transnational students in those locales of the importance of the hybrid learning environment with an emphasis on face-to-face interaction in their courses, and discusses the importance of cultural sensitivities on those perceptions. The paper concludes by considering the future of the hybrid education model in the transnational context.
A Model Transformation from the Palladio Component Model to Layered Queueing Networks
Authors: Heiko Koziolek, Ralf Reussner
Venue: Proceedings of the SPEC international workshop on Performance Evaluation: Metrics, Models and Benchmarks (2008)

For component-based performance engineering, software component developers individually create performance specifications of their components. Software architects compose these specifications to architectural models. This enables assessing the possible fulfilment of performance requirements without the need to purchase and deploy the component implementations. Many existing performance models do not support component-based performance engineering but offer efficient solvers. On the other hand, component-based performance engineering approaches often lack tool support. We present a model transformation combining the advanced component concepts of the Palladio Component Model (PCM) with the efficient performance solvers of Layered Queueing Networks (LQN). Joining the tool-set for PCM specifications with the tool-set for LQN solution is an important step to carry component-based performance engineering into industrial practice. We validate the correctness of the transformation by mapping the PCM model of a component-based architecture to an LQN and conduct performance predictions.
The Max-Relevance and Min-Redundancy Greedy Bayesian Network Learning Algorithm
Authors: Feng Liu, Qiliang Zhu
Venue: Proceedings of the 2nd international work-conference on The Interplay Between Natural and Artificial Computation, Part I: Bio-inspired Modeling of Cognitive Tasks (2007)

Existing algorithms for learning Bayesian network require a lot of computation on high dimensional itemsets which affects reliability, robustness and accuracy of these algorithms and takes up a large amount of time. To address the above problem, we propose a new Bayesian network learning algorithm MRMRG, Max Relevance-Min Redundancy Greedy. MRMRG algorithm is a variant of K2 which is a well-known BN learning algorithm. We also analyze the time complexity of MRMRG. The experimental results show that MRMRG algorithm has much better efficiency. It is also shown that MRMRG algorithm has better accuracy than most of existing learning algorithms for limited sample datasets.
Administration Models and Management Tools
Authors: R. Hai, T. Heer, M. Heller, M. Nagl, R. Schneider, B. Westfechtel, R. Wörzberger
Venue: Collaborative and Distributed Chemical Engineering. From Understanding to Substantial Design Process Support: Results of the IMPROVE Project (2008)

One of the vertical columns in the overall process/product model deals with the cooperation of subprojects I1 and B4. Both study the support for reactive process management in dynamic development processes. In this section we highlight the transition from application models developed in subproject I1 to tool models for reactive management of subproject B4. We summarize our findings w.r.t. the development of management tool models as well as their connections to application models. The section focuses on a process-oriented viewpoint. Products and resources of development processes can be discussed analogously. We identify the missing parts which need to be further investigated in order to get a comprehensive and integrated process/product model, here for reactive management.
Discovering Knowledge in a Large Organization through Support Vector Machines
Authors: J. A. Gutiérrez De Mesa, L. Bengochea Martínez
Venue: Proceedings of the 8th international conference on Computational Science, Part III (2008)

Much of the information used by an organization is collected in the form of manuals, regulations, news etc. These are grouped into controlled documentary collections, which are normally digitized and accessible via a content management system. However, obtaining new knowledge from collected documents in an organization requires not only sound search and retrieval of information tools, but also the techniques to establish relationships, discover patterns and provide overall descriptions of the entire contents of the collection. This article explores the nature of knowledge and the role that occupy the documentary collections as a source of obtaining him knowledge. It also describes the collection of documents will be used along the exposure of this study and the techniques of processing information in order to obtain the desired results. This paper describes the use of computational methods, support vector machines in particular, in a large organisation for document classification.
Robustness and Randomness
Authors: Dominique Michelucci, Jean Michel Moreau, Sebti Foufou
Venue: Reliable Implementation of Real Number Algorithms: Theory and Practice: International Seminar Dagstuhl Castle, Germany, January 8-13, 2006 Revised Papers (2008)

The study of robustness problems for computational geometry algorithms is a topic that has been subject to intensive research efforts from both computer science and mathematics communities. Robustness problems are caused by the lack of precision in computations involving floating-point instead of real numbers. This paper reviews methods dealing with robustness and inaccuracy problems. It discusses approaches based on exact arithmetic, interval arithmetic and probabilistic methods. The paper investigates the possibility to use randomness at certain levels of reasoning to make geometric constructions more robust.