ppxscal/embedding_network huggingface dataset:
Precise Extraction of Partially Occluded Objects by Using HLAC Features and SVM
Authors: Kazutoki Otake, Kazuhito Murakami, Tadashi Naruse
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

In the RoboCup competition, robot soccer game, ball and robots are extracted by using color information. If color markers attached on the robot or a ball itself are occluded, especially the occlusion ratio is high, it will be difficult to extract them. This paper proposes a new and high precision method which extracts partially occluded objects based on the statistical features of the pixel and its neighborhoods. Concretely, at first, input image is labeled by using color information and small candidate regions which have similar color to the color markers or the ball are extracted, then each candidate region is classified into partially occluded object or noise by using HLAC features and SVM. We applied our method to the global vision system of RoboCup small size league (SSL) and confirmed that it could extract partially occluded objects, 94.23% for 5 to 8 pixels area and 80.06% for 3 to 4 pixels area, and worked more than 60fps.
Construction of Virtual Learning Environments of Lushan Mountain
Authors: Weijun Yang, Jianhua Gong, Lihui Zhang, Hongli Fan
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

Organizing a fieldwork in LuShan Mountain consumes much money and time, but the result is not effective. This demands a virtual learning environment of LuShan Moutain. Some methods of data collection based on mobile equipments are adopted. The data collection system constructs a collaborative 3D modeling environment, in which students can do goecollaboration. In this paper, some technologies to support data collection are discussed.
A Phrase Recommendation Algorithm Based on Query Stream Mining in Web Search Engines
Authors: M. Barouni-Ebrahimi, Ali A. Ghorbani
Venue: Algorithms and Models for the Web-Graph: Fourth International Workshop, WAW 2006, Banff, Canada, November 30 - December 1, 2006. Revised Papers (2007)

In this paper, a phrase recommender algorithm is proposed that suggests the related frequent phrases to an incomplete user query. The suggested phrases are extracted from past user queries based on the frequency rate of the phrases. A query recommender algorithm called OQD (Online Query Discovery) has also been designed for comparison purposes. Simulation results show the efficiency of the proposed phrase recommender algorithm compared to the OQD. The phrase recommender algorithm significantly reduces the size of the candidate set, which results in smaller memory usage and better performance, while recommending more appropriate phrases to the user.
On the Almighty Wand
Authors: Rémi Brochenin, Stéphane Demri, Etienne Lozes
Venue: Proceedings of the 22nd international workshop on Computer Science Logic (2008)

We investigate decidability, complexity and expressive power issues for (first-order) separation logic with one record field (herein called SL) and its fragments. SL can specify properties about the memory heap of programs with singly-linked lists. Separation logic with two record fields is known to be undecidable by reduction of finite satisfiability for classical predicate logic with one binary relation. Surprisingly, we show that second-order logic is as expressive as SL and as a by-product we get undecidability of SL. This is refined by showing that SL without the separating conjunction is as expressive as SL, whence undecidable too. As a consequence of this deep result, in SL the magic wand can simulate the separating conjunction. By contrast, we establish that SL without the magic wand is decidable with non-elementary complexity by reduction from satisfiability for the first-order theory over finite words. Equivalence between second-order logic and separation logic extends to the case with more than one selector.
Discrete data clustering using finite mixture models
Authors: Nizar Bouguila, Walid ElGuebaly
Venue: Pattern Recognition (2009)

Finite mixture models have been applied for different computer vision, image processing and pattern recognition tasks. The majority of the work done concerning finite mixture models has focused on mixtures for continuous data. However, many applications involve and generate discrete data for which discrete mixtures are better suited. In this paper, we investigate the problem of discrete data modeling using finite mixture models. We propose a novel, well motivated mixture that we call the multinomial generalized Dirichlet mixture. The novel model is compared with other discrete mixtures. We designed experiments involving spatial color image databases modeling and summarization, and text classification to show the robustness, flexibility and merits of our approach.
Comparing Classroom Problem-Solving with No Feedback to Web-Based Homework Assistance
Authors: Leena Razzaq, Michael Mendicino, Neil T. Heffernan
Venue: Proceedings of the 9th international conference on Intelligent Tutoring Systems (2008)

It is common for math teachers to give students time in class to practice problem solving skills. Some studies have shown that intelligent tutoring systems (ITS) can be superior to traditional classroom instruction. In this study, we compare problem solving with little or no feedback in the classroom to problem solving using a web-based ITS for homework. The system provides students with coached practice that is meant to scaffold "learning by doing" while students practice their problem solving skills. We found evidence that using the web-based ITS to practice problem solving at home was better than the classroom problem solving with an effect size of 0.5.
Conversational Case-Based Recommendations Exploiting a Structured Case Model
Authors: Quang Nhat Nguyen, Francesco Ricci
Venue: Proceedings of the 9th European conference on Advances in Case-Based Reasoning (2008)

There are case-based recommender systems that generate personalized recommendations for users exploiting the knowledge contained in past recommendation cases. These systems assume that the quality of a new recommendation depends on the quality of the recorded recommendation cases. In this paper, we present a case model exploited in a mobile critique-based recommender system that generates recommendations using the knowledge contained in previous recommendation cases. The proposed case model is capable of modeling evolving (conversational) recommendation sessions, capturing the recommendation context, supporting critique-based user-system conversations, and integrating both ephemeral and stable user preferences. In this paper, we evaluate the proposed case model through replaying real recommendation cases recorded in a previous live-user evaluation. We measure the impact of the various components of the case model on the system's recommendation performance. The experimental results show that the case components that model the user's contextual information, default preferences, and initial preferences, are the most important for mobile context-dependent recommendation.
A Framework for Designing Novel Magnetic Tiles Capable of Complex Self-assemblies
Authors: Urmi Majumder, John H. Reif
Venue: Proceedings of the 7th international conference on Unconventional Computing (2008)

Self-assembly has been immensely successful in creating complex patterns at the molecular scale. However, the use of self-assembly techniques at the macroscopic level has so far been limited to the formation of simple patterns. For example, in a number of prior works, self-assembling units or tiles formed aggregates based on the polarity of magnetic pads on their sides. The complexity of the resulting assemblies was limited, however, due to the small variety of magnetic pads that were used: namely just positive or negative polarity. This paper addresses the key challenge of increasing the variety of magnetic pads for tiles, which would allow the tiles to self-assemble into more complex patterns. We introduce a barcode scheme which potentially allows for the generation of arbitrarily complex structures using magnetic self-assembly at the macro-scale. Development of a framework for designing such barcode schemes is the main contribution of the paper. We also present a physical model based on Newtonian mechanics and Maxwellian magnetics. Additionally, we present a preliminary software simulation system that models the binding of these tiles using magnetic interactions as well as external forces (e.g. wind) which provide energy to the system. Although we have not performed any physical experiments, nevertheless, we show that it is possible to use the simulation results to extract a higher level kinetic model that can be used to predict assembly yield on a larger scale and provide better insight into the dynamics of the real system.
The model of roles within an ontology development tool: Hozo
Authors: Riichiro Mizoguchi, Eiichi Sunagawa, Kouji Kozaki, Yoshinobu Kitamura
Venue: Applied Ontology (2007)

One of the major goals of ontology is to represent properly the underlying conceptual structure of the messy world reflecting the reality as much as possible. Ontology building tools should be designed to help developers create good ontologies. However, few of them can deal with roles adequately. Needless to say, the world is full of roles (e.g., wife, teacher, president, fuel, food, product, output, height) although there has been extensive theoretical research on roles, we do not yet have a comprehensive and usable theory yet. Our group has already constructed an ontology-development tool known as Hozo which has the ability to deal with roles. However, although Hozo allows users to represent roles better than other existing tools, the underlying theoretical foundations are still unclear and there is some room for improvement concerning the generality of how to deal with roles. In this paper, as an extension of the Hozo framework for roles, we present a framework for organizing role concepts according to their context dependencies. We also focus on the clarification of role properties and requirements on the model of roles and on the feedback obtained from Hozo-based ontology building experiences. Establishment of a computational model of roles contributes to building good ontologies because such a theory would provide useful guidelines for dealing with view-related and context-dependent distinctions related to roles.
Effects of Diversity Measures on the Design of Ensemble Classifiers by Multiobjective Genetic Fuzzy Rule Selection with a Multi-classifier Coding Scheme
Authors: Yusuke Nojima, Hisao Ishibuchi
Venue: Proceedings of the 3rd international workshop on Hybrid Artificial Intelligence Systems (2008)

We have already proposed multiobjective genetic fuzzy rule selection with a multi-classifier coding scheme for the design of ensemble classifiers. An entropy-based diversity measure was used as an objective to be maximized for increasing the diversity of base classifiers in an ensemble. In this paper, we examine the use of other diversity measures in the design of ensemble classifiers. Experimental results show that the choice of a diversity measure has a large effect on the performance of designed ensemble classifiers.
Hierarchies in Fragments of Monadic Strict NP
Authors: Barnaby Martin, Florent Madelaine
Venue: Proceedings of the 3rd conference on Computability in Europe: Computation and Logic in the Real World (2007)

We expose a strict hierarchy within monotone monadic strict NP without inequalities (MMSNP), based on the number of second-order monadic quantifiers. We do this by studying a finer strict hierarchy within a class of forbidden patterns problems (FPP), based on the number of permitted colours. Through an adaptation of a preservation theorem of Feder and Vardi, we are able to prove that this strict hierarchy also exists in monadic strict NP (MSNP). Our hierarchy results apply over a uniform signature involving a single binary relation, that is over digraphs.
Investor Sentiment and Return Predictability in Chinese Fuel Oil Futures Markets
Authors: Qian Zhao, Jianping Li, Shuping Wang
Venue: Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007 (2007)

We investigate the relation between investor sentiment and market returns in Chinese Fuel Oil Futures Markets by Vector Autoregressions (VAR) model. The sample period is from 5 September 2005 until 31 December 2006. Studies using daily datum on sentiments of professional advisors and individual investors suggest that past market returns are an important determinant of sentiment. Our evidence supports that not individual but professional sentiment has predictive power for returns. Extreme levels of sentiment do not possess any superiority in returns predictability with the exception of the individual bottom sentiment. For 1-week, 2- week and 4-week intervals, returns can weakly predict sentiment or changes. Individual sentiment severs as a contrary indicator of returns in the followed week, whereas we find no evidence for the other circumstance.
Multi-robot Cooperative Localization through Collaborative Visual Object Tracking
Authors: Zhibin Liu, Mingguo Zhao, Zongying Shi, Wenli Xu
Venue: RoboCup 2007: Robot Soccer World Cup XI (2008)

In this paper we present an approach for a team of robots to cooperatively improve their self localization through collaboratively tracking a moving object. At first, we use a Bayes net model to describe the multi-robot self localization and object tracking problem. Then, by exploring the independencies between different parts of the joint state space of the complex system, we show how the posterior estimation of the joint state can be factorized and the moving object can serve as a bridge for information exchange between the robots for realizing cooperative localization. Based on this, a particle filtering method for the joint state estimation problem is proposed. And, finally, in order to improve computational efficiency and achieve real-time implementation, we present a method for decoupling and distributing the joint state estimation onto different robots. The approach has been implemented on our four-legged AIBO robots and tested through different scenarios in RoboCup domain showing that the performance of localization can indeed be improved significantly.
Ontology-Based Framework for Personalized Diagnosis and Prognosis of Cancer Based on Gene Expression Data
Authors: Yingjie Hu, Nikola Kasabov
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part II (2008)

This paper presents an ontology-based framework for personalized cancer decision support system based on gene expression data. This framework integrates the ontology and personalized cancer predictions using a variety of machine learning models. A case study is proposed for demonstrating the personalized cancer diagnosis and prognosis on two benchmark cancer gene data. Different methods based on global, local and personalized modeling, including Multi Linear Regression (MLR), Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Evolving Classifier Function (ECF), weighted distance weighted variables K-nearest neighbor method (WWKNN) and a transductive neuro-fuzzy inference system with weighted data normalization (TWNFI) are investigated. The development platform is general that can use multimodal information for personalized prediction and new knowledge creation within an evolving ontology framework.
Fuzzy c-Means for Data with Tolerance Defined as Hyper-Rectangle
Authors: Yasushi Hasegawa, Yasunori Endo, Yukihiro Hamasuna, Sadaaki Miyamoto
Venue: Proceedings of the 4th international conference on Modeling Decisions for Artificial Intelligence (2007)

The paper presents some new clustering algorithms which are based on fuzzy c-means. The algorithms can treat data with tolerance defined as hyper-rectangle. First, the tolerance is introduced into optimization problems of clustering. This is generalization of calculation errors or missing values. Next, the problems are solved and some algorithms are constructed based on the results. Finally, usefulness of the proposed algorithms are verified through numerical examples.
SAGE-A Data Processing System for Air Defense
Authors: Robert R. Everett, Charles A. Zraket, Herbert D. Benington
Venue: IEEE Annals of the History of Computing (1983)

The paper is adapted from a presentation at the 1957 Eastern Joint Computer Conference. The authors give details of the Semi-Automatic Ground Environment (SAGE) system and how it developed.
Reducing the Number of Bits in the BTB to Attack the Branch Predictor Hot-Spot
Authors: N. Tomás, J. Sahuquillo, S. Petit, P. López
Venue: Proceedings of the 14th international Euro-Par conference on Parallel Processing (2008)

Current superscalar processors access the BTB early to anticipate the branch/jump target address. This access is frequent and aggressively performed since the BTB is accessed every cycle for all instructions in the ICache line being fetched. This fact increases the power density, which could create hot spots, thus increasing packaging and cooling costs. Power consumption in the BTB comes mostly from its two main fields: the tag and the target address fields. Reducing the length of either of these fields reduces power consumption, silicon area and access time. This paper analyzes at what extent tag and target address lengths could be reduced to benefit both dynamic and static power consumption, silicon area, and access time, while sustaining performance. Experimental results show that the tag length and the target address could be reduced by about a half and one byte, respectively with no performance losses. BTB peak power savings can reach about 35% when both reductions are combined together, thus effectively attacking the hot-spot.
On the Relative Importance of Toponyms in GeoCLEF
Authors: Davide Buscaldi, Paolo Rosso
Venue: Advances in Multilingual and Multimodal Information Retrieval: 8th Workshop of the Cross-Language Evaluation Forum, CLEF 2007, Budapest, Hungary, September 19-21, 2007, Revised Selected Papers (2008)

In this work we attempted to determine the relative importance of the geographical and WordNet-extracted terms with respect to the remainder of the query. In our system, geographical terms are expanded with WordNet holonyms and synonyms and indexed separately. We checked the relative importance of the terms by multiplying their weight by 0.75, 0.5 and 0.25. The comparison to the baseline system, which uses only Lucene, shows that in some cases it is possible to improve the mean average precision by balancing the relative importance of geographical terms with respect to the content words in the query. We also observed that WordNet holonyms may help in improving the recall but WordNet has a small coverage and term expansion is sensible to ambiguous place names.
Comparison and Evaluation of Identity Management in Three Architectures for Virtual Organizations
Authors: Ali N. Haidar, Ali E. Abdallah
Venue: Proceedings of the 2008 The Fourth International Conference on Information Assurance and Security (2008)

This paper compares and contrasts authentication mechanisms used in three VO architectures: the first reflects ad-hoc connections among several organizations, the second uses a centrally managed database and the third is based on public key infrastructure (PKI). The reason for studying these particular three architectures is that they cover a large class of currently operating VOs (i.e. supply chains, Grids). These architectures used several types of authentication mechanisms starting from traditional username/password, through online trusted servers (Kerberos), to offline trusted third parties: Certificate Authorities and digital certificates. The current defacto-standard middleware used to build VOs, Globus Toolkit, is based on the PKI architecture.
Reasoning about Object Structures Using Ownership
Authors: Peter Müller
Venue: Verified Software: Theories, Tools, Experiments: First IFIP TC 2/WG 2.3 Conference, VSTTE 2005, Zurich, Switzerland, October 10-13, 2005, Revised Selected Papers and Discussions (2005)

Many well-established concepts of object-oriented programming work for individual objects, but do not support object structures. The development of a verifying compiler requires enhancements of programming theory to cope with this deficiency.In this paper, we support this position by showing that classical specification and verification techniques support invariants for individual objects whose fields are primitive values, but are unsound for invariants involving more complex object structures.We have developed an ownership model, which allows one to structure the object store and to restrict reference passing and the operations that can be performed on references. We use this model to generalize classical object invariants to cover such object structures. We summarize the state of our work and identify open research challenges.
Principal components-minimum variance based technique for high resolution detection of concealed object
Authors: Mujahid Al-Azzo
Venue: Proceedings of the 8th WSEAS International Conference on Multimedia systems and signal processing (2008)

The problem of spatially detection and imaging of closely separated objects is investigated. This paper presents principal components-minimum variance method, a high resolution technique, to model the long wavelength ultrasonic holographic imaging problem. Ultrasonic waves are used for detecting the concealed object. The in-line holography is employed. The performance of the method is compared with the traditional method, Fourier transform method. The technique is investigated for different values of signal to noise ratio(SNR) and synthetic aperture length.
A Proxy-Based System for Translation of Internet Content into Specific Form
Authors: Pavel Ocenasek
Venue: Proceedings of the 8th Asia-Pacific conference on Computer-Human Interaction (2008)

The paper deals with the system based on proxy techniques for translation of Internet content into specific form. The first part of the paper presents the motivation for translation of internet content. The second part deals with the system concept. The system can be built-up either as a standard internet proxy-server or URL web-proxy. The right choice depends on the application (content security, web accessibility). The final part of the paper concludes with the features that will be developed in the system in future.
Policy Based Messaging Framework
Authors: Martin Eggenberger, Nupur Prakash, Koji Matsumoto, Darrell Thurmond
Venue: Proceedings of the 5th international conference on Service-Oriented Computing (2007)

Due to integration complexities to legacy as well as new systems, a Common Messaging Framework has been developed that is based on policies to control the behavior of the various enterprise services. These policies include both internal and external Quality of Service Policies as well as constraint based business process policies. This paper proposes and identifies a policy based messaging framework for both intranet and extranet services, upon which individual policies can be injected during runtime for individual messages, domains and or processes. Further more these policies can be customized on a per actor basis and dynamically changed during runtime by a console user without having to stop the process.