ppxscal/embedding_network huggingface dataset:
Rotation-Invariant and Scale-Invariant Steerable Pyramid Decomposition for Texture Image Retrieval
Authors: Javier A. Montoya-Zegarra, Neucimar J. Leite, Ricardo da S. Torres
Venue: Proceedings of the XX Brazilian Symposium on Computer Graphics and Image Processing (2007)

This paper proposes a new rotation-invariant and scale-invariant representation for texture image retrieval based on Steerable Pyramid Decomposition. By calculating the mean and standard deviation of decomposed image subbands, the texture feature vectors are extracted. To obtain rotation or scale invariance, the feature elements are aligned by considering either the dominant orientation or dominant scale of the input textures. Experiments were conducted on the Brodatz database aiming to compare our approach to the conventional Steerable Pyramid Decomposition, and a recent proposal for texture characterization based on Gabor Wavelets with regard to their retrieval effectiveness. Results demonstrate the superiority of the proposed method in rotated and scaled image datasets.
Identification Information Analysis of Sample Train Set Subspace
Authors: XiangFei Fu, Jiliu Zhou, FangNian Lang
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

Principal Component Analysis (PCA) which is widely used in pattern recognition field aims at reducing the dimension of sample. PCA replaces variables in the original sample vectors that have redundant information with fewer integrative variables. The recognition ability used author's algorithm is tested in the paper. It is proved that zerospace do not include any identification information which would be useful for distinguishing different samples. Experiment results based of our lab's facebase and ORL facebase shows the theory is right.
Transforming 3D coloured pixels into musical instrument notes for vision substitution applications
Authors: Guido Bologna, Benoît Deville, Thierry Pun, Michel Vinckenbosch
Venue: Journal on Image and Video Processing (2007)

The goal of the See ColOr project is to achieve a noninvasive mobility aid for blind users that will use the auditory pathway to represent in real-time frontal image scenes. We present and discuss here two image processing methods that were experimented in this work: image simplification by means of segmentation, and guiding the focus of attention through the computation of visual saliency. A mean shift segmentation technique gave the best results, but for real-time constraints we simply implemented an image quantification method based on the HSL colour system. More particularly, we have developed two prototypes which transform HSL coloured pixels into spatialised classical instrument sounds lasting for 300 ms. Hue is sonified by the timbre of a musical instrument, saturation is one of four possible notes, and luminosity is represented by bass when luminosity is rather dark and singing voice when it is relatively bright. The first prototype is devoted to static images on the computer screen, while the second has been built up on a stereoscopic camera which estimates depth by triangulation. In the audio encoding, distance to objects was quantified into four duration levels. Six participants with their eyes covered by a dark tissue were trained to associate colours with musical instruments and then asked to determine on several pictures, objects with specific shapes and colours. In order to simplify the protocol of experiments, we used a tactile tablet, which took the place of the camera. Overall, colour was helpful for the interpretation of image scenes. Moreover, preliminary results with the second prototype consisting in the recognition of coloured balloons were very encouraging. Image processing techniques such as saliency could accelerate in the future the interpretation of sonified image scenes.
Load balancing for video streaming services in hierarchical wireless networks
Authors: Joon-Sang Park, Seung-Jae Han
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2008)

Wireless networks have focused on voice call services or wireless Internet access services. These days, the application service domain of wireless networks is rapidly expanding, and a wide variety of new services is emerging. Video streaming service is one of the most promising examples, evidenced by 3GPP's MBMS (Multimedia Broadcast Multicast Service) and IMS (IP Multimedia Subsystem). In this paper, we consider the provision of video streaming services in hierarchical wireless networks with multiple layers of cells. We particularly focus on optimal load balancing among the cells, aiming at the minimization of frame drop ratio for given video streaming sessions. From this objective function, we derive the optimal load balancing condition. Load balancing is essentially the issue of which users are assigned to which cell, i.e., the user assignment problem. In our user assignment algorithm, we compute thresholds to divide users into groups according to the user characteristics, and map the user groups to proper cells. The optimal load balancing condition can be reached by adaptively adjusting the threshold at run time. This process does not require prior knowledge about the system status, such as the system capacity or user traffic requests, which warrants the practicality of the proposed scheme. Via simulations, we demonstrate that the proposed scheme achieves optimal load balancing in various realistic environments.
Video Objects Segmentation by Robust Background Modeling
Authors: Andrea Colombari, Andrea Fusiello, Vittorio Murino
Venue: Proceedings of the 14th International Conference on Image Analysis and Processing (2007)

This paper deals with the problem of segmenting a video shot into a background (still) mosaic and one or more foreground moving objects. The method is based on ego-motion compensation and background estimation. In order to be able to cope with sequences where occluding objects persist in the same position for a considerable portion of time, the papers concentrates on robust background estimation method. First the sequence is subdivided in patches that are clustered along the time-line in order to narrow down the number of background candidates. Then the background is grown incrementally by selecting at each step the best continuation of the current background, according to the principles of visual grouping. The method rests on sound principles in all its stages, and only few, intelligible parameters are needed. Experiments with real sequences illustrate the approach.
Evaluating Software Project Control Centers in Industrial Environments
Authors: M. Ciolkowski, J. Heidrich, J. Munch, F. Simon, M. Radicke
Venue: Proceedings of the First International Symposium on Empirical Software Engineering and Measurement (2007)

Many software development organizations still lack support for detecting and reacting to critical project states in order to achieve planned goals. One means to institutionalize project control, systematic quality assurance, and management support on the basis of measurement and explicit models is the establishment of so-called Software Project Control Centers. However, there is only little experience reported in the literature with respect to setting up and applying such control centers in industrial environments. One possible reason is the lack of appropriate evaluation instruments (such as validated questionnaires and appropriate analysis procedures). Therefore, we developed an initial measurement instrument to systematically collect experience with respect to the deployment and use of control centers. Our main research goal was to develop and evaluate the measurement instrument. The instrument is based on the Technology Acceptance Model (TAM) and customized to project controlling. This article illustrates the application and evaluation of this measurement instrument in the context of industrial case studies and provides lessons learned for further improvement. In addition, related work and conclusions for future work are given.
Numerical solutions of time-varying TS-fuzzy-model-based time-delay dynamic equations via orthogonal functions
Authors: M.-R. Hsu, W.-H. Ho, J.-H. Chou
Venue: International Journal of Systems Science (2007)

In this paper, the approach of orthogonal functions is presented to solve the time-varying Takagi-Sugeno (TS) fuzzy-model-based time-delay dynamic equations (time-varying TSFMTDE). The new method simplifies the procedure of solving the time-varying TSFMTDE into the successive solution of a system of recursive formulae only involving matrix algebra. Based on the presented recursive formulae, an algorithm only including straightforward algebraic computation is also proposed in this paper. The new proposed approach is non-iterative, non-differential, non-integral, straightforward, and well-adapted to computer implementation. Hence, the computational complexity is considerably reduced. The first illustrated example shows that the proposed method, based on the orthogonal functions, can obtain satisfactory results. The second illustrated example, for the pendulum time-delay system with the vibration in the vertical direction on the pivot point having a fuzzy parallel-distributed-compensation controller, is given to demonstrate the application of the proposed approach.
Scaling IP Routing with the Core Router-Integrated Overlay
Authors: Xinyang Zhang, Paul Francis, Jia Wang, Kaoru Yoshida
Venue: Proceedings of the Proceedings of the 2006 IEEE International Conference on Network Protocols (2006)

IP routing scalability is based on hierarchical routing, which requires that the IP address hierarchy be aligned with thephysical topology. Both site multi-homing and switching ISPs without renumbering break this alignment, resulting in largerouting tables. This paper presents CRIO: a new approach to IP scalability for both global and VPN routing. Using tunnelingand virtual prefixes, CRIO decouples address hierarchy and physical topology, effectively giving ISPs the ability to trade-offrouting table size for path length. Though CRIO is a new routing architecture, it works with existing data-plane router mechanisms.Through static simulation on a Rocketfuel-measured Internet topology and traffic data from a Tier 1 ISP, we show that CRIOcan shrink the BGP RIB by nearly two orders of magnitude, the global FIB by one order of magnitude, and the VPN FIB by tento twenty times, all with very little increase in overall path length.
CookieFlavors: Rapid Composition Framework for Tangible Media
Authors: Hiroaki Kimura, Yohei Okuda, Tatsuo Nakajima
Venue: Proceedings of the The 2007 International Conference on Next Generation Mobile Applications, Services and Technologies (2007)

We propose an effective design process for tangible media using a novel framework "CookieFlavors". CookieFlavors provides developers with some abstractions which hide cumbersome implementation phase to develop tangible media. Moreover the framework supports developers to do prototyping them easily. From three case studies to develop tangible media using our framework, we have confirmed our design process and derived some future works of our framework.
A Classifier of Similar Characters using Compound Mahalanobis Function based on Difference Subspace
Authors: Junichi Hirayama, Hidehisa Nakayama, Nei Kato
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

To distinguish similar characters, it is preferable to construct a classifier using a projective feature space which differentiates two similar categories. The classifier CMF has been proposed for a discriminant function, in similar characters recognition. In the CMF, a subspace is constructed by some eigenvectors, that corresponds to the smallest eigenvalues, is applied as projective feature space. A difference vector of two class-mean feature vectors are assumed as the difference between two similar categories, the CMF is constructed by projecting a feature vector onto this difference vector. In this paper, we propose new discriminant function expanding the CMF. In proposed method, we treat the Difference Subspace, which is difference between two subspaces as difference between two similar categories. The efficiency of the proposed new discriminant function has been demonstrated in similar characters recognition through extensive experiments on hand-written Japanese characters derived from the ETL9B database.
Clustering Without Prior Knowledge Based on Gene Expression Programming
Authors: Yu Chen, Changjie Tang, Jun Zhu, Chuan Li, Shaojie Qiao, Rui Li, Jiang Wu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 03 (2007)

Most existing clustering methods require prior knowledge, such as the number of clusters and thresholds. They are difficult to determine accurately in practice. To solve the problem, this study proposes a novel clustering algorithm named GEP-Cluster based on Gene Expression Programming (GEP) without prior knowledge. The main contributions include: (1) a new concept named Clustering Algebra is proposed that makes clustering as algebraic operation, (2) a GEP-Cluster algorithm is proposed to find the best clustering information automatic by GEP and discover the best clustering solution without any prior knowledge, (3) an AMCA (Automatic Merging Cluster Algorithm) algorithm is proposed to merge clustering automatically. Extensive experiments demonstrate that GEP-Cluster algorithm is effective in clustering without any prior knowledge on various data sets.
Diva: a variance-based clustering approach for multi-type relational data
Authors: Tao Li, Sarabjot Singh Anand
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

Clustering is a common technique used to extract knowledge from a dataset in unsupervised learning. In contrast to classical propositional approaches that only focus on simple and flat datasets, relational clustering can handle multi-type interrelated data objects directly and adopt semantic information hidden in the linkage structure to improve the clustering result. However, exploring linkage information will greatly reduce the scalability of relational clustering. Moreover, some characteristics of vector data space utilized to accelerate the propositional clustering procedure are no longer valid in relational data space. These two disadvantages restrain the relational clustering techniques from being applied to very large datasets or in time-critical tasks, such as online recommender systems. In this paper we propose a new variance-based clustering algorithm to address the above difficulties. Our algorithm combines the advantages of divisive and agglomerative clustering paradigms to improve the quality of cluster results. By adopting the idea of Representative Object, it can be executed with linear time complexity. Experimental results show our algorithm achieves high accuracy, efficiency and robustness in comparison with some well-known relational clustering approaches.
Evaluation of computer-based instructional material: intent and procedures
Authors: Bobby R. Brown, Robert S. Ellinger
Venue: ACM SIGCUE Outlook (1978)

In this paper the authors address some of the benefits to be derived through evaluation in the development and the dissemination of computer based instructional materials. Formative evaluation is discussed as a practical and worthwhile means of improving quality and effectiveness of instructional material. The importance of summative evaluation and documentation for intelligent selection and use of disseminated instructional material is discussed. Procedural suggestions are offered for employing both formative and summative evaluation within the context of systematic instructional design. An example is presented in which these suggested procedures were employed.
On the Impossible Class of Faulty Functions in Logic Networks Under Short Circuit Faults
Authors: B. B. Bhattacharya
Venue: IEEE Transactions on Computers (1986)

The important problem of recognizing a priori the class of Boolean functions which are never obtainable from a given combinational network under short circuit faults is almost unexplored, primarily due to lack of understanding of the functional and structural factors that influence the fault behavior in the network. In view of this, a new concept of impossible class of faulty functions (ICFF) is introduced in this correspondence. Several intriguing properties of ICFF are uncovered, namely, the undetectability of input bridging faults, the impossibility of the transformation of a fault free function Fo to a subset or superset of Fo, and to other functions belonging to the same P-and N-equivalence classes of Fo, etc. The closure amongst the fan-out-free and unate functions under bridging faults is investigated. The impact of ICFF on the testability of the network is also discussed.
Most common courses of specializations in artificial intelligence, computer systems, and theory
Authors: Sami Surakka
Venue: Proceedings of the 6th Baltic Sea conference on Computing education research: Koli Calling 2006 (2006)

The degree requirements of American institutions offering top-level graduate programs in computer science were analyzed. The sample size was 59 institutions for undergraduate and 32 for graduate programs. The purpose was to solve which courses were the most commonly offered in the specializations of Artificial Intelligence, Computer Systems, and Theory. The results can be useful to professors who are responsible for any of these three specializations.
Learning correlations using the mixture-of-subsets model
Authors: Manas Somaiya, Christopher Jermaine, Sanjay Ranka
Venue: ACM Transactions on Knowledge Discovery from Data (TKDD) (2008)

Using a mixture of random variables to model data is a tried-and-tested method common in data mining, machine learning, and statistics. By using mixture modeling it is often possible to accurately model even complex, multimodal data via very simple components. However, the classical mixture model assumes that a data point is generated by a single component in the model. A lot of datasets can be modeled closer to the underlying reality if we drop this restriction. We propose a probabilistic framework, the mixture-of-subsets (MOS) model, by making two fundamental changes to the classical mixture model. First, we allow a data point to be generated by a set of components, rather than just a single component. Next, we limit the number of data attributes that each component can influence. We also propose an EM framework to learn the MOS model from a dataset, and experimentally evaluate it on real, high-dimensional datasets. Our results show that the MOS model learned from the data represents the underlying nature of the data accurately.
Reconsideration of Software Reliability Measurements
Authors: Shiyi Xu
Venue: Proceedings of the 16th Asian Test Symposium (2007)

In this paper, we discuss the major weaknesses of the software reliability measurements currently used and propose a new model of software reliability estimation. For the time being, the software reliability models are employed far from ubiquitous. As a national research project, we propose some strategies of improving the software reliability measurement. The central idea of the strategies proposed in this paper is to incorporate the influence factors of complexity of the software under test and the test effectiveness into the software reliability models so as to make the software reliability models more adequate and accurate to the real situation. Results from substantial experiments have shown the rationality and usefulness of the new model.
An Evidence Combination Rule Based on the Support Degree of Focal Element
Authors: He Luo, Shanlin Yang, Chao Fu, Xiaojian Hu
Venue: Proceedings of the Fourth International Conference on Fuzzy Systems and Knowledge Discovery - Volume 02 (2007)

According to the management and assignment of conflicted evidences in the evidence combination, the paper introduces the supporting degree of focal element of conflicted evidences to the combination rule according to these issues, and suggests a new way of combination assignment. Based on the support degree of focal element, we establish a combination rule of evidence theory. Besides, the paper also gives the strict demonstration and makes simulated experiments of the new rule. The new rule rationally assigns the probability of conflicted evidences to every focal element according to the support degree. The experiments show that the results of the new combination rule are very reliable and rational.
Radio-over-Fiber based architecture for seamless wireless indoor communication in the 60GHz band
Authors: Bao Linh Dang, M. Garcia Larrode, R. Venkatesha Prasad, Ignas Niemegeers, A. M. J. Koonen
Venue: Computer Communications (2007)

In order to satisfy the increasing demand of wireless broadband multimedia services, much attention has been paid to the 60GHz band where as much as 5GHz of spectrum has been reserved. However, in the indoor environment, the propagation of signals at this millimeter wave band is strongly hindered by walls, people and their movement, furniture, etc. As a result, a mobile user might experience frequent loss of connection as the user moves from one cell to another. In this paper, we propose a flexible and cost-effective Radio-over-Fiber (RoF) based network architecture to support indoor networking at millimeter wave bands. To create sufficient overlap areas between cells and thus to ensure a seamless communication environment for mobile users, the concept of Extended Cell is introduced. We demonstrate the effectiveness of the proposed architecture with a detailed simulation study of an indoor scenario. Furthermore, we analyze the impact of the architecture on the performance of two popular state-of-the-art protocols, namely IEEE 802.11 and IEEE 802.16, to find which Medium Access Control (MAC) protocol is suitable for RoF networks.
An ontology-based business process modeling methodolog
Authors: Li Liao, Hareton K. N. Leung
Venue: Proceedings of the third conference on IASTED International Conference: Advances in Computer Science and Technology (2007)

Business process modeling is important for SOA application development. Formal modeling methodology has significant benefits but related research seems inadequate. In this paper we present an upper ontology for business process modeling, called Business Process Ontology (BPO), and propose an SOA application modeling and developing framework. The BPO provides accurate definitions of the main components of SOA modeling. The extension of BPO can be used to define business process models, describe existing services, and define the mapping between processes and services. Applying ontology to SOA Modeling can help to identify the binding information of business process and service, increase the reusability of existing business processes and services, and accelerate the development of application.
Reliability of CMOS Integrated Circuits
Authors: G. L. Schnable
Venue: Computer (1978)

CMOS ICsare being produced using a variety of processes, and considerable data is now available on their reliability and failure mechanisms.
Twelve Years of Visualization Research at Microsoft
Authors: George Robertson
Venue: Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing (2007)

Microsoft Research has been involved in a variety of visualization research efforts over the last twelve years. In this talk, I will summarize the various threads of research, which include task management, personal information management, software visualization, business visualization, community visualization, graph and tree visualization, and visual analytics for homeland security. I will give demonstrations of key prototypes that have been built. One of the key challenges throughout this work has been developing effective means of evaluation of visualization techniques. I will summarize what we have learned about evaluation methods. Finally, I will summarize some basic lessons learned about what visualization techniques are most effective across all of these research efforts.