ppxscal/embedding_network huggingface dataset:
High-Level Expectations for Low-Level Image Processing
Authors: Lothar Hotz, Bernd Neumann, Kasim Terzic
Venue: Proceedings of the 31st annual German conference on Advances in Artificial Intelligence (2008)

Scene interpretation systems are often conceived as extensions of low-level image analysis with bottom-up processing for high-level interpretations. In this contribution we show how a generic high-level interpretation system can generate hypotheses and initiate feedback in terms of top-down controlled low-level image analysis. Experimental results are reported about the recognition of structures in building facades.
New Edge Detection Approach by Using Linear Filtering
Authors: Zhang Yingjie, Ge Liling
Venue: Proceedings of the 2007 Third International IEEE Conference on Signal-Image Technologies and Internet-Based System (2007)

This paper proposed a new method for edge detection based on the diffused images that are obtained by diffusing the source image with different parameters of filter, respectively. The edge map is determined by checking the varying of the pixel value on the diffused images, and multiscale edge detection can be achieved by using different filter parameters. Unlike previous approaches, the new method is robust to the varying of some parameters of images such as contrast, brightness, etc. Also it is computationally very efficient; in particular when the linear diffusion methods like four-points averaging algorithm is applied. Furthermore because the edges or contours of the image is located in the edge map based on the principle of level set-based segmentation algorithms, therefore the detected result is the same with that in the segmentation algorithms. The key to this algorithm is the determination of the filter parameters, and it can be tried and determined in advanced for a specified application. The proposed algorithm has been validated with some numerical results.
Near net shape technology: An innovative opportunity for the automotive industry
Authors: R. Cominotti, E. Gentili
Venue: Robotics and Computer-Integrated Manufacturing (2008)

Near net shape is an innovative concept in industrial manufacturing. The main focus of this technology is to produce parts, as near as possible close to their final shape and contour, implementing non-chipping techniques. In this way the manufacturing gives the possibility of a finished product with minimal cutting. Near net shape technology also generates the opportunity to reduce the productive steps for a given process chain. Both the above-mentioned characteristics have the same main goal: achieving cost reduction. This fundamental target incorporates several other advantages, such as: reduction of process variability, quality improvement in the finished product and the possibility to focus the design of mechanical devices on functional features, eliminating technical constraints imposed by the process. Based on these factors and in cooperation with the IWU Fraunhofer Institut of Chemnitz, the authors conducted a research regarding the manufacturing of an innovative automotive gear shaft, produced by applying near net shape processes. The goal of this study is to evaluate whether it is more convenient to produce the part implementing a traditional production chain or an innovative one, based on near net shape techniques. The first step was to locate the available technologies in order to produce the selected part. There are two alternatives: a traditional cutting manufacture, performed with a numerical control turning machine and a near-net-shape technique, characterized only by deformation processes. The next step was to detect the main differential costs between the two opportunities. Comparing technical data and information available in literature, the authors detected the main differential voices of cost: raw material, amortization, manpower and direct setup. In order to make the study more reliable, the authors assumed an actual industrial environment, featured by an annual demand of 400,000 pieces and a product lifetime cycle of 10yr. The evaluation led to the conclusion that the innovative manufacturing chain is more convenient.
A Branch and Bound Algorithm for Matching Protein Structures
Authors: Janez Konc, Dušanka Janežič
Venue: Proceedings of the 8th international conference on Adaptive and Natural Computing Algorithms, Part II (2007)

An efficient branch and bound algorithm for matching protein structures has been developed. The compared protein structures are represented as graphs and a product graph of these graphs is calculated. The resulting product graph is then the input to our algorithm. A maximum clique in the product graph corresponds to the maximum common substructure in the original graphs. Our algorithm, which gives an approximate solution to the maximum clique problem, is compared with exact algorithms commonly used in bioinformatics for protein structural comparisons. The computational results indicate that the new algorithm permits an efficient protein similarity calculation used for protein structure analysis and protein classification.
Content-Based Image Retrieval Using Shifted Histogram
Authors: Gi-Hyoung Yoo, Beob Kyun Kim, Kang Soo You
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

This paper proposes the shifted histogram method (SHM), for histogram-based image retrieval based on the dominant colors in images. The histogram-based method is very suitable for color image retrieval because retrievals are unaffected by geometrical changes in images, such as translation and rotation. Images with the same visual information, but with shifted color intensity, may significantly degrade if the conventional histogram intersection method (HIM) is used. In order to solve this problem, we propose the shifted histogram method (SHM). Our experimental results show that the shifted histogram method
MSRA Columbus at GeoCLEF 2006
Authors: Zhisheng Li, Chong Wang, Xing Xie, Xufa Wang, Wei-Ying Ma
Venue: Evaluation of Multilingual and Multi-modal Information Retrieval: 7th Workshop of the Cross-Language Evaluation Forum, CLEF 2006, Alicante, Spain, September 20-22, 2006, Revised Selected Papers (2007)

This paper describes the participation of Columbus Project of Microsoft Research Asia (MSRA) in GeoCLEF 2006. We participated in the Monolingual GeoCLEF evaluation (EN-EN) and submitted five runs based on different methods. In this paper, we describe our geographic information retrieval system, discuss the results and draw following conclusions: 1) if we just extract locations from the topics automatically without any expansions as geo-terms, the retrieval performance is barely satisfactory; 2) automatic query expansion weakens the performance; 3) if the queries are expanded manually, the performance is significantly improved.
A wired router can eliminate 802.11 unfairness, but it's hard
Authors: Kan Cai, Junfang Wang, Reza Lotun, Michael J. Feeley, Michael Blackstock, Charles Krasic
Venue: Proceedings of the 9th workshop on Mobile computing systems and applications (2008)

As mobile computing becomes ubiquitous and airspace more congested, it is increasingly important to fairly distribute bandwidth between competing wireless devices in order to ensure predictable and satisfactory performance for end users. In prior work, we have proposed a cross-layer approach called Shaper [3, 4] that uses TCP and a central router rather than the 802.11 protocol to decide the outcome of bandwidth allocation. The key idea is to avoid airspace congestion from happening in the first place. Shaper is effective and also easy to deploy. However, its implementation faces many fundamentally difficult challenges. This paper details these challenges and possible solutions.
Model Based Synthesis of Embedded Software
Authors: Daniel D. Gajski, Samar Abdi, Ines Viskic
Venue: Proceedings of the 6th IFIP WG 10.2 international workshop on Software Technologies for Embedded and Ubiquitous Systems (2008)

This paper presents SW synthesis using Embedded System Environment (ESE), a tool set for design of multi-core embedded systems. We follow a design process that starts with an application model consisting of C processes communicating via abstract message passing channels. The application model is mapped to a platform net-list of SW and HW cores, buses and buffers. A high speed transaction level model (TLM) is generated to validate abstract communication between processes mapped to different cores. The TLM is further refined into a Pin-Cycle Accurate Model (PCAM) for board implementation. The PCAM includes C code for all the communication layers including routing, packeting, synchronization and bus transfer. The generated embedded SW provides a library of application level services to the C processes on individual SW cores. Therefore, the application developer does not need to write low level SW for board implementation. Synthesis results for an multi-core MP3 decoder design, using ESE, show that the embedded SW is generated in order of seconds, compared to hours of manual coding. The quality of synthesized code is comparable to manually written code in terms of performance and code size.
Multivariate stress-strength reliability model and its evaluation for coherent structures
Authors: Serkan Eryilmaz
Venue: Journal of Multivariate Analysis (2008)

Consider a system which has n independent components (or subsystems) each consisting of m dependent elements. Let X"i=(X"i^1,X"i^2,...,X"i^m), i=1,2,...,n denote the random strength vector of the ith component, where X"i^j denotes the random strength of the jth element of the ith component. The elements of the components are subjected to a common random stress Y=(Y"1,Y"2,...,Y"m) over time. In this paper, we setup a multivariate stress-strength model based on the conditional ordering between X"is and Y and evaluate the reliability of coherent structures in this setup.
Next Generation Business Process Management: A Paradigm Shift
Authors: Tanuj Arora, Amol Nirpase
Venue: Proceedings of the 2008 IEEE Congress on Services - Part I (2008)

Business Process Management is a management model that allows the organizations to manage their processes as any other asset and improve them over a period of time. To date, many BPM packages have not been playing the role of strategic decision making. This paper will enable BPM users to understand next generation BPM packages. It covers the factors which leads the existing BPM to next generation BPM practices. Next generation BPM is explained with detailed components and structure.
Solving the Delay Constrained Multicast Routing Problem Using the Transiently Chaotic Neural Network
Authors: Wen Liu, Lipo Wang
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

Delay constrained multicast routing (DCMR) aims to construct a minimum-cost tree with end-to-end delay constraints. This routing problem is becoming more and more important to multimedia applications which are delay-sensitive and require real time communications. We solve the DCMR problem by the transiently chaotic neural network (TCNN) of Chen and Aihara. Simulation results show that the TCNN is more capable of reaching global optima compared with the Hopfield neural network (HNN).
A Parallel RBFNN Classifier Based on S-Transform for Recognition of Power Quality Disturbances
Authors: Weiming Tong, Xuelei Song
Venue: Proceedings of the 4th international symposium on Neural Networks: Part II--Advances in Neural Networks (2007)

This paper proposes a novel parallel RBFNN (Radial Basis Function Neural Network) classifier based on S-transform for recognition and classification of PQ (Power Quality) disturbances. S-transform is used to extract feature vectors, while the constructed parallel RBFNN classifier is used to recognize and classify PQ disturbances according to the extracted feature vectors. The parallel RBFNN classifier consists of eight sub-networks, each of which is only able to recognize one type of disturbance. In order to improve the convergence performance of RBFNN and optimize the number of hidden layer nodes, a dynamic clustering algorithm which clusters all training samples to determine the number of hidden layer nodes is proposed. Simulation and test results demonstrate that the method proposed to recognize and classify PQ disturbances is correct and feasible, and that the RBFNN classifier based on the dynamic clustering algorithm has a faster convergence speed and a higher correct identification rate.
Fast Most Similar Neighbor Classifier for Mixed Data
Authors: Selene Hernández-Rodríguez, J. Francisco Martínez-Trinidad, J. Ariel Carrasco-Ochoa
Venue: Proceedings of the 20th conference of the Canadian Society for Computational Studies of Intelligence on Advances in Artificial Intelligence (2007)

The nearest neighbor (NN) classifier has been a widely used technique in pattern recognition because of its simplicity and good behavior. To decide the class of a new object, the NN classifier performs an exhaustive comparison between the object to classify and the training set T. However, when T is large, the exhaustive comparison is very expensive and sometimes becomes inapplicable. To avoid this problem, many fast NN algorithms have been developed for numerical object descriptions, most of them based on metric properties to avoid comparisons. However, in some sciences as Medicine, Geology, Sociology, etc., objects are usually described by numerical and non numerical attributes (mixed data). In this case, we can not assume the comparison function satisfies metric properties. Therefore, in this paper a fast most similar object classifier based on search methods suitable for mixed data is presented. Some experiments using standard databases and a comparison with other two fast NN methods are presented.
IDFQ: An Interface for Database Flexible Querying
Authors: Mohamed Ali Hassine, Habib Ounelli
Venue: Proceedings of the 12th East European conference on Advances in Databases and Information Systems (2008)

In traditional database management systems, imprecision has not been taken into account so one can say that there is some sort of lack of flexibility. The main cause is that queries retrieve only elements which precisely match to the given Boolean query. Many works were proposed in this context. The majority of these works are based on Fuzzy logic. In this paper, we discuss the flexibility in databases by referring to the Formal Concept Analysis theory. We propose an environment based on this theory which permits the flexible modelling and querying of a database with powerful retrieval capability. The architecture of this environment reuses the existing structure of a traditional database and adds new components (Metaknowledge Base, Context Base, Concept Base, etc.) while guaranteeing interoperability between them.
Designing Syntax Embeddings and Assimilations for Language Libraries
Authors: Martin Bravenboer, Eelco Visser
Venue: Models in Software Engineering: Workshops and Symposia at MoDELS 2007, Nashville, TN, USA, September 30 - October 5, 2007, Reports and Revised Selected Papers (2008)

Language libraries extend regular libraries with domain-specific notation. More precisely, a language library is a combination of a domain-specific language embedded in the general-purpose host language, a regular library implementing the underlying functionality, and an assimilation transformation that maps embedded DSL fragments to host language code. While the basic architecture for realizing language libraries is the same for all applications, there are many design choices to be made in the design of a particular combination of library, guest language syntax, host language, and assimilation. In this paper, we give an overview of the design space for syntax embeddings and assimilations for the realization of language libraries.
The impact of customer interface quality, satisfaction and switching costs on e-loyalty: Internet experience as a moderator
Authors: Hsin Hsin Chang, Su Wen Chen
Venue: Computers in Human Behavior (2008)

Customer interface quality has been confirmed to critically influence the success of electronic commerce, and there has been extensive discussion about the effects of customer interface quality on consumer behavior. However, few studies have examined how customer interface quality affects e-loyalty. Furthermore, although satisfaction and switching costs are expected to be antecedents to customer loyalty, few studies have systematically examined how these elements are related to customer interface quality. This study proposes an integrating theoretical framework for testing the relationships among customer interface quality, satisfaction, switching costs, and e-loyalty. Moreover, this study argues that the relationships among these constructs are moderated by Internet experience. Empirical analyses are performed using structural equations modeling analysis. The findings confirm that customer interface quality, including customization, interaction, convenience and character, contributes to generating e-loyalty. Particularly, the results show that convenience directly enhances e-loyalty. Additionally, this study finds that customer interface quality positively influences switching costs for customers with higher Internet experience, a phenomenon that has not previously been explored.
A Decision-Making Approach to R&D Project with Uncertainty of Combining Randomness and Fuzziness
Authors: Changsheng Yi, Yufu Ning, Qiumei Jin
Venue: Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing (2008)

The main purpose of this study is to construct a suitable research and development (R&D) decision model which would facilitate the analysis of optimal stopping and investment strategy with mixed uncertainty of randomness and fuzziness in R&D project. In classical R&D decision models,the inter-arrival times between jumps are usually assumed as random variables which are exponentially distributed. In this paper, the inter-arrival times are treated as random fuzzy variables with arbitrary distributions. Furthermore, the random fuzzy expected value model is established to maximize the expected discounted net return from R&D project. To solve the model, the random fuzzy simulation for expected discounted net return is given and embedded into particle swarm optimization (PSO) algorithm to design a hybrid intelligent algorithm. Finally, an numerical example is given for the sake of illustration of the effectiveness of this algorithm.
On-Line Detection of Rule Violations in Table Soccer
Authors: Armin Hornung, Dapeng Zhang
Venue: Proceedings of the 31st annual German conference on Advances in Artificial Intelligence (2008)

In table soccer, humans can not always thoroughly observe fast actions like rod spins and kicks. However, this is necessary in order to detect rule violations for example for tournament play. We describe an automatic system using sensors on a regular soccer table to detect rule violations in realtime. Naive Bayes is used for kick classification, the parameters are trained using supervised learning. In the on-line experiments, rule violations were detected at a higher rate than by the human players. The implementation proved its usefulness by being used by humans in real games and sets a basis for future research using probability models in table soccer.
Regional Languages and Tiling: A Unifying Approach to Picture Grammars
Authors: Alessandra Cherubini, Stefano Crespi Reghizzi, Matteo Pradella
Venue: Proceedings of the 33rd international symposium on Mathematical Foundations of Computer Science (2008)

Several classical models of picture grammars based on array rewriting rules can be unified and extended by a tiling based approach. The right part of a rewriting rule is formalized by a finite set of permitted tiles. We focus on a simple type of tiling, named regional, and define the corresponding regional tile grammars. They include both Siromoney's (or Matz's) Kolam grammars, and their generalization by Průša. Regionally defined pictures can be recognized with polynomial time complexity by an algorithm extending the CKY one for strings. Regional tile grammars and languages are strictly included into the tile grammars and languages, and are incomparable with Giammarresi-Restivo tiling systems (or Wang's tilings).
Optimal access to information while writing: writing in the internet age
Authors: Olga Muñoz Ramos, Mari Carmen Puerta Melguizo, Lou Boves, Maria Gracia Castillo Vergara
Venue: Proceedings of the second international symposium on Information interaction in context (2008)

Writing professional documents requires finding relevant related information. Although the availability of information constantly increases, seeking for information relevant for the task is not easy. A Proactive Recommendation System (PRS) retrieves information relevant to the written text and presents it without user intervention. The information presented can improve the quality of the text, but can also interrupt the process of writing. We investigated the impact of a PRS on writing in comparison to active seeking situations. We explored the effects of both ways to access information (active versus proactive) during the different stages of writing. The results suggest that people need to access information especially in the first stage of writing: planning. Participants found that proactive presentation of relevant information is more useful and less disturbing during planning.
Towards Reusable Automation System Components
Authors: Thomas Aschauer, Gerd Dauenhauer, Wolfgang Pree
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

In this paper we present a domain specific language for describing an automation system, that is, its hardware and software components. These domain components form the basis of large-scale reuse so that specific automation systems can be configured efficiently.
Data Model Comprehension: An Empirical Comparison of ER and UML Class Diagrams
Authors: Andrea De Lucia, Carmine Gravino, Rocco Oliveto, Genoveffa Tortora
Venue: Proceedings of the 2008 The 16th IEEE International Conference on Program Comprehension (2008)

We present the results of two controlled experiments to compare ER and UML class diagrams, in order to find out which of the models provides better support during the comprehension of data models. The experiment involved Master and Bachelor students performing comprehension tasks on data models represented by ER or UML class diagrams. The achieved results show that UML class diagrams significantly improve the comprehension level achieved by subjects. Moreover, having different subjects with different levels of ability and experience allowed us to also make some considerations on the influence of such factors on the comprehension performances.
How Can the Term Compositionality Be Useful for Acquiring Elementary Semantic Relations?
Authors: Thierry Hamon, Natalia Grabar
Venue: Proceedings of the 6th international conference on Advances in Natural Language Processing (2008)

Acquiring and enriching lexical resources is crucial for various areas of the computational linguistics applications, especially in specialized domains. In this paper, we propose a high-quality method exploiting the compositionality of complex terms issued from a structured terminology in order to infer three kinds of semantic relations (synonymy, hierarchical and meronymy) between words or terms. The approach has been applied and evaluated on the Gene Ontology biomedical terminology: 1,273 is-a, 178 part-of and 921 synonymy relations have been inferred and show a precision over 90%. We analyze these results and the possibility of their cross-validation through a graph representation.