ppxscal/embedding_network huggingface dataset:
Superstition in the Machine
Authors: Alexander Riegler
Venue: Anticipatory Behavior in Adaptive Learning Systems: From Brains to Individual and Social Behavior (2007)

It seems characteristic for humans to detect structural patterns in the world to anticipate future states. Therefore, scientific and common sense cognition could be described as information processing which infers rule-like laws from patterns in data-sets. Since information processing is the domain of computers, artificial cognitive systems are generally designed as pattern discoverers.This paper questions the validity of the information processing paradigm as an explanation for human cognition and a design principle for artificial cognitive systems. Firstly, it is known from the literature that people suffer from conditions such as information overload, superstition, and mental disorders. Secondly, cognitive limitations such as a small short-term memory, the set-effect, the illusion of explanatory depth, etc. raise doubts as to whether human information processing is able to cope with the enormous complexity of an infinitely rich (amorphous) world.It is suggested that, under normal conditions, humans construct information rather than process it. The constructed information contains anticipations which need to be met. This can be hardly called information processing, since patterns from the "outside" are not used to produce action but rather to either justify anticipations or restructure the cognitive apparatus.When it fails, cognition switches to pattern processing, which, given the amorphous nature of the experiential world, is a lost cause if these patterns and inferred rules do not lead to a (partial) reorganisation of internal structures such that constructed anticipations can be met again.In this scenario, superstition and mental disorders are the result of a profound and/or random restructuring of already existing cognitive components (e.g., action sequences). This means that whenever a genuinely cognitive system is exposed to pattern processing it may start to behave superstitiously. The closer we get to autonomous self-motivated artificial cognitive systems, the bigger the danger becomes of superstitious information processing machines that "blow up" rather than behave usefully and effectively. Therefore, to avoid superstition in cognitive systems they should be designed as information constructing entities.
Impact of Term-Indexing for Arabic Document Retrieval
Authors: Siham Boulaknadel
Venue: Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems (2008)

In this paper, we adapt the standard method for multi-word term extraction for Arabic language. We define the linguistic specifications and develop a term extraction tool. We experiment the term extraction program for document retrieval in a specific domain, evaluate two kinds of multi-word term weighting functions considering either the corpus or the document, and demonstrate the efficiency of multi-word term indexing for both weighting up to 5.8% of average precision. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Sparse Coding Neural Gas for the Separation of Noisy Overcomplete Sources
Authors: Kai Labusch, Erhardt Barth, Thomas Martinetz
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part I (2008)

We consider the problem of separating noisy overcomplete sources from linear mixtures, i.e., we observe N mixtures of M > N sparse sources. We show that the "Sparse Coding Neural Gas" (SCNG) algorithm [1] can be employed in order to estimate the mixing matrix. Based on the learned mixing matrix the sources are obtained by orthogonal matching pursuit. Using artificially generated data, we evaluate the influence of (i) the coherence of the mixing matrix, (ii) the noise level, and (iii) the sparseness of the sources with respect to the performance that can be achieved on the representation level. Our results show that if the coherence of the mixing matrix and the noise level are sufficiently small and the underlying sources are sufficiently sparse, the sources can be estimated from the observed mixtures.
A genetic procedure for RBF neural networks centers selection
Authors: Constantin-Iulian Vizitiu, Doru Munteanu
Venue: Proceedings of the 9th WSEAS International Conference on Neural Networks (2008)

It is well known that the performances of the RBF neural networks depend a lot by the positioning method of the radial functions centers. Using the affiliation of the genetic algorithms to the class of the global searching techniques with very good results in the solving of the complex optimization problems, it is absolutely justified the attempt to select the RBF neural networks centers using a proper genetic procedure.
Software Implementation of Arithmetic in
Authors: Omran Ahmadi, Darrel Hankerson, Alfred Menezes
Venue: Proceedings of the 1st international workshop on Arithmetic of Finite Fields (2007)

Fast arithmetic for characteristic three finite fields is desirable in pairing-based cryptography because there is a suitable family of elliptic curves over having embedding degree 6. In this paper we present some structure results for Gaussian normal bases of , and use the results to devise faster multiplication algorithms. We carefully compare multiplication in using polynomial bases and Gaussian normal bases. Finally, we compare the speed of encryption and decryption for the Boneh-Franklin and Sakai-Kasahara identity-based encryption schemes at the 128-bit security level, in the case where supersingular elliptic curves with embedding degrees 2, 4 and 6 are employed.
A Signal Processing Technique for Improving the Accuracy of MEMS Inertial Sensors
Authors: Peter A. Stubberud, Allen R. Stubberud
Venue: Proceedings of the 2008 19th International Conference on Systems Engineering (2008)

Navigation, guidance and control for small space vehicles require inertial measurement sensors which are small, inexpensive, low power, reliable and accurate. Micro inertial sensors, such as MEMS gyroscopes, can provide small, inexpensive, low power devices; however, the accuracy of these devices is insufficient for many space applications. Signal processing methods can be used to provide the necessary accuracy. The individual outputs of many nominally identical micro sensors can be combined to generate a single accurate measurement. An extended Kalman filter (EKF) [1] which includes the dynamics of every sensor can be used for such a combination; however, the 'curse of dimensionality' limits the number of sensors which can be used. In this paper, a new EKF technique for combining many sensors is proposed which, using a common nominal model for the micro sensors and a single EKF with the state dimension of a single sensor, has accuracy comparable to the high dimensional EKF and is significantly more accurate than a single sensor.
Quality Assessment in Software Product Lines
Authors: Leire Etxeberria, Goiuria Sagardui
Venue: Proceedings of the 10th international conference on Software Reuse: High Confidence Software Reuse in Large Systems (2008)

In a software product line, quality assessment is especially important because an error or an inadequate design decision can be spread into a lot of products. Moreover, in a product line, different members of the line may require different quality attributes. In this paper, a method for quality aware software product line engineering that takes into account the variability of quality aspects and facilitates quality assessment is presented.
A Multiobjective Approach to Fuzzy Job Shop Problem Using Genetic Algorithms
Authors: Inés González-Rodríguez, Jorge Puente, Camino R. Vela
Venue: Current Topics in Artificial Intelligence: 12th Conference of the Spanish Association for Artificial Intelligence, CAEPIA 2007, Salamanca, Spain, November 12-16, 2007. Selected Papers (2007)

We consider a job shop problem with uncertain durations and flexible due dates and introduce a multiobjective model based on lexicographical minimisation. To solve the resulting problem, a genetic algorithm and a decoding algorithm to generate possibly active schedules are considered. The multiobjective approach is tested on several problem instances, illustrating the potential of the proposed method.
Site-Independent Template-Block Detection
Authors: Aleksander Kołcz, Wen-Tau Yih
Venue: Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases (2007)

Detection of template and noise blocks in web pages is an important step in improving the performance of information retrieval and content extraction. Of the many approaches proposed, most rely on the assumption of operating within the confines of a single website or require expensive hand-labeling of relevant and non-relevant blocks for model induction. This reduces their applicability, since in many practical scenarios template blocks need to be detected in arbitrary web pages, with no prior knowledge of the site structure. In this work we propose to bridge these two approaches by using within-site template discovery techniques to drive the induction of a site-independent template detector. Our approach eliminates the need for human annotation and produces highly effective models. Experimental results demonstrate the usefulness of the proposed methodology for the important applications of keyword extraction, with relative performance gain as high as 20%.
Comparing Window and Syntax Based Strategies for Semantic Extraction
Authors: Pablo Gamallo Otero
Venue: Proceedings of the 8th international conference on Computational Processing of the Portuguese Language (2008)

In this paper, we describe and compare two different approaches for extracting similar words from large corpora. In particular, we compared a method based on syntactic contexts with two strategies relying on windows of tagged words, one using word order and the other bags of words. On a Portuguese corpus of 12 million words, syntactic contexts produce significantly better results for both frequent and not very frequent words. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Generalized Laplacian as Focus Measure
Authors: Muhammad Riaz, Seungjin Park, Muhammad Bilal Ahmad, Waqas Rasheed, Jongan Park
Venue: Proceedings of the 8th international conference on Computational Science, Part I (2008)

Shape from focus (SFF) uses focus measure operator for depth measurement from a sequence of images. From the analysis of defocused image, it is observed that the focus measure operator should respond to high frequency variations of image intensity and produce maximum values when the image is perfectly focused. Therefore, an effective focus measure operator must be a high-pass filter. Laplacian is mostly used as focus measure operator in the previous SFF methods. In this paper, generalized Laplacian is used as focus measure operator for better 3D shape recovery of objects.
Efficiently Handling Dynamics in Distributed Link Based Authority Analysis
Authors: Josiane Xavier Parreira, Sebastian Michel, Gerhard Weikum
Venue: Proceedings of the 9th international conference on Web Information Systems Engineering (2008)

Link based authority analysis is an important tool for ranking resources in social networks and other graphs. Previous work have presented $\mathrm{J^{X}_P}$, a decentralized algorithm for computing PageRank scores. The algorithm is designed to work in distributed systems, such as peer-to-peer (P2P) networks. However, the dynamics of the P2P networks, one if its main characteristics, is currently not handled by the algorithm. This paper shows how to adapt $\mathrm{J^{X}_P}$ to work under network churn. First, we present a distributed algorithm that estimates the number of distinct documents in the network, which is needed in the local computation of the PageRank scores. We then present a method that enables each peer to detect other peers leave and to update its view of the network. We show that the number of stored items in the network can be efficiently estimated, with little overhead on the network traffic. Second, we present an extension of the original $\mathrm{J^{X}_P}$ algorithms that can cope with network and content dynamics. We show by a comprehensive performance analysis the practical usability of our approach. The proposed estimators together with the changes in the core $\mathrm{J^{X}_P}$ components allow for a fast and authority score computation even under heavy churn. We believe that this is the last missing step toward the application of distributed PageRank measures in real-life large-scale applications.
A Novel Retrieval Refinement and Interaction Pattern by Exploring Result Correlations for Image Retrieval
Authors: Rongrong Ji, Hongxun Yao, Shaohui Liu, Jicheng Wang, Pengfei Xu
Venue: Adaptive Multimedial Retrieval: Retrieval, User, and Semantics: 5th International Workshop, AMR 2007, Paris, France, July 5-6, 2007 Revised Selected Papers (2007)

Efficient retrieval of image database that contains multiple predefined categories (e.g. medical imaging databases, museum painting collections) poses significant challenges and commercial prospects. By exploring category correlations of retrieval results in such scenario, this paper presents a novel retrieval refinement and feedback framework. It provides users a novel perceptual-similar interaction pattern for topic-based image retrieval. Firstly, we adopts Pairwise-Coupling SVM (PWC-SVM) to classify retrieval results into predefined image categories, and reorganizes them into category based browsing topics. Secondly, in feedback interaction, category operation is supported to capture users' retrieval purpose fast and efficiently, which differs from traditional relevance feedback patterns that need elaborate image labeling. Especially, an Asymmetry Bagging SVM (ABSVM) network is adopted to precisely capture users' retrieval purpose. And user interactions are accumulated to reinforce our inspections of image database. As demonstrated in experiments, remarkable feedback simplifications are achieved comparing to traditional interaction patterns based on image labeling. And excellent feedback efficiency enhancements are gained comparing to traditional SVM-based feedback learning methods.
Solving some NP-complete problems using split decomposition
Authors: Michaël Rao
Venue: Discrete Applied Mathematics (2008)

We show how to use the split decomposition to solve some NP-hard optimization problems on graphs. We give algorithms for clique problem and domination-type problems. Our main result is an algorithm to compute a coloration of a graph using its split decomposition. Finally we show that the clique-width of a graph is bounded if and only if the clique-width of each representative graph in its split decomposition is bounded.
Analysis and research on friction-free cylinder of modal testing suspension system
Authors: Jianhui Sun, Xiaohang Shan, Xiujun Zhang, Li Zhang, Zhisong Gao, Mingfeng Xie, Qingwu Wang
Venue: Proceedings of the 8th WSEAS International Conference on Robotics, Control and Manufacturing Technology (2008)

Pneumatic technology is one of the key technologies of ultra-low frequency modal analysis suspension system in the freedom-freedom conditions. This paper has introduced the principle of the suspension system modal testing, theoretically analysed and experimentally verified mechanical design and realized function of the pneumatic suspension subsystem friction-free cylinder. This pneumatic subsystems are used in low-frequency, ultra-low-frequency modal analysis testing system to achieve the flexible hanging. The experimental results has shown that the improvement on the aerodynamic subsystem may improve the loading capacity at the same time improve the aerodynamic subsystem vibration and pressure fluctuations influenced by the pressure source.
Some Mathematical Problems in Cryptanalysis
Authors: Xiaoyun Wang
Venue: Computer Mathematics: 8th Asian Symposium, ASCM 2007, Singapore, December 15-17, 2007. Revised and Invited Papers (2008)

The talk will recall some basic mathematical problems on analyzing both symmetric and asymmetric ciphers. A special focus will be on the advances in asymmetric ciphers based on the research of some fundamentally hard mathematical problems. Some fundamental statistical problems and cryptanalysis techniques for symmetric cipher will be reviewed as well. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Architecture Aware Partitioning Algorithms
Authors: Irene Moulitsas, George Karypis
Venue: Proceedings of the 8th international conference on Algorithms and Architectures for Parallel Processing (2008)

Existing partitioning algorithms provide limited support for load balancing simulations that are performed on heterogeneous parallel computing platforms. On such architectures, effective load balancing can only be achieved if the graph is distributed so that it properly takes into account the available resources (CPU speed, network bandwidth). With heterogeneous technologies becoming more popular, the need for suitable graph partitioning algorithms is critical. We developed such algorithms that can address the partitioning requirements of scientific computations, and can correctly model the architectural characteristics of emerging hardware platforms.
Face Verification Based on AdaBoost Learning for Histogram of Gabor Phase Patterns (HGPP) Selection and Samples Synthesis with Quotient Image Method
Authors: Jianfu Chen, Xingming Zhang, Jinsheng Li
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

Face verification technology is widely used in public safety, e-commerce, access control, and so on. We propose a novel face verification approach, which combines a relatively new object descriptor--Histogram of Gabor Phase Patterns (HGPP), AdaBoost Algorithm selecting HGPP features and learning binary classifier, and Quotient Image method synthesizing face images under new illumination conditions. Although Gabor wavelets have been widely used in face recognition, previous studies mainly focus on the magnitude information of Gabor feature, while neglect the phase information of it. We use HGPP as an attempt to utilize the neglected Gabor phase information in face verification. Then AdaBoost algorithm trains binary classifiers, meanwhile significantly reduce the dimension of HGPP. Further, the novel strategy that synthesizes and extends training samples with Quotient Image method enhances our algorithm's robustness for illumination variation. Experiments demonstrate our novel approach is able to achieve promising face verification results under different illumination conditions.
Autonomous Decentralized VoD Architecture to Achieve Service Assurance
Authors: Xiaodong Lu, Kinji Mori
Venue: Proceedings of the 2008 The 28th International Conference on Distributed Computing Systems Workshops (2008)

In distributed and ubiquitous computing systems, they have been utilized under the evolving situation where the system structure itself, the composing subsystems, their unctions, the accessible information would be changed constantly. With the advances of compression, storage and network technologies, Video on Demand (VoD) service is becoming more and more popular. However, it is difficult for conventional systems to meet the continuous and heterogeneous requirements from service providers and userssimultaneously. This paper introduces an autonomous decentralized VoD system sustained by mobile agents for information service provision and utilization. Under the proposed architecture, autonomous coordination technology for node adjustment is proposed to achieve load balance and continuous service in the situation of changing users preference. The effectiveness of the proposed technology is proved by the simulation.
Decision Fusion on Boosting Ensembles
Authors: Joaquín Torres-Sospedra, Carlos Hernández-Espinosa, Mercedes Fernández-Redondo
Venue: Proceedings of the 3rd IAPR workshop on Artificial Neural Networks in Pattern Recognition (2008)

Training an ensemble of neural networks is an interesting way to build a Multi-net System. One of the key factors to design an ensemble is how to combine the networks to give a single output. Although there are some important methods to build ensembles, Boosting is one of the most important ones. Most of methods based on Boosting use an specific combiner (Boosting Combiner). Although the Boosting combiner provides good results on boosting ensembles, the results of previouses papers show that the simple combiner Output Average can work better than the Boosting combiner. In this paper, we study the performance of sixteen different combination methods for ensembles previously trained with Adaptive Boosting and Average Boosting. The results show that the accuracy of the ensembles trained with these original boosting methods can be improved by using the appropriate alternative combiner.
Forming processes control by means of artificial intelligence techniques
Authors: E. Sáenz de Argandoña, A. Aztiria, C. García, N. Arana, A. Izaguirre, P. Fillatreau
Venue: Robotics and Computer-Integrated Manufacturing (2008)

Forming processes are manufacturing processes that use force and pressure in order to modify the shape of a material part until obtaining the final product. The wide range of non-linear factors that drive this sort of processes make them very complex and extremely difficult to be controlled. Traditional control techniques, like PID controllers, have not offered a reliable solution when global control has been pursued and the figure of the operator still remains present in most of the forming facilities. On the other hand, although operators have demonstrated to be a very successful strategy when controlling this type of processes, the actual market evolution towards the fabrication of more complex parts, made of lower formability materials at higher production rates, is decreasing their capacity of reaction when solving the daily problems. Thus, the development of new global control systems based not on traditional control techniques and mathematical models but on the control strategy that has been used successfully for many years, the control through the experience and knowledge is now even more necessary. In the present work, an intelligent control system based on one of the main techniques within the artificial intelligence, expert systems, has been developed. The main purpose of this intelligent control system is to emulate the decisions that expert operators take but in a quicker and more reliable way. The developed intelligent control system has been installed in a blanking facility and very good results have been achieved.