ppxscal/embedding_network huggingface dataset:
Robust sequential view planning for object recognition using multiple cameras
Authors: F. Farshidi, S. Sirouspour, T. Kirubarajan
Venue: Image and Vision Computing (2009)

While prior relevant research in active object recognition/pose estimation has mostly focused on single-camera systems, we propose two multi-camera solutions to this problem that can enhance object recognition rate, particularly in the presence of occlusion. In the proposed methods, multiple cameras simultaneously acquire images from different view angles of an unknown, randomly occluded object belonging to a set of a priori known objects. By processing the available information within a recursive Bayesian framework at each step, the recognition algorithms attempt to classify the object, if its identity/pose can be determined with a high confidence level. Otherwise, the algorithms would compute the next most informative camera positions for capturing more images. The principle component analysis (PCA) is used to produce a measurement vector based on the acquired images. Occlusions in the images are handled by a novel probabilistic modelling approach that can increase the robustness of the recognition process with respect to structured noise. The camera positions at each recognition step are selected based on two statistical metrics quantifying the quality of the observations, namely the mutual information (MI) and the Cramer-Rao lower bound (CRLB). While the former has also been used in a prior relevant work, the latter is new in the context of object recognition. Extensive Monte Carlo experiments conducted with a two-camera system demonstrate the effectiveness of the proposed approaches.
Impacts of frequency and posture on body mass index in manual handling tasks
Authors: Edem G. Tetteh, Niaz Latif, James D. McGlothlin, Jerry Peters
Venue: Human Factors in Ergonomics Manufacturing (2009)

Workspace design plays an important role in ensuring workers' safety and welfare. The issue is more pressing in the manufacturing industry, where many workers must remain in a standing position, assume awkward postures, and perform repetitive tasks for extended periods of time. In this research, an electromyographic measurement technique was used to measure activity of four back muscles: the trapezius p. descendens, the deltoideus p. scapularis, the infraspinatus, and the latissimus dorsi. The results showed a statistically significant (p < 0.05) impact of left versus right side of the body, the degree of rotation to the right side of the body (0, 30, and 60 degrees rotation to the mid-sagittal plane), body mass index level (normal weight [<25 kg-m2] vs. overweight [&ges;25 kg-m2]), and tasks (high vs. low frequency). In this study, the role that workers and workspace variation play is clearly associated with an increase in the amplitude of electromyography at the targeted back muscles. &copy; 2009 Wiley Periodicals, Inc.
Learning prediction suffix trees with Winnow
Authors: Nikos Karampatziakis, Dexter Kozen
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

Prediction suffix trees (PSTs) are a popular tool for modeling sequences and have been successfully applied in many domains such as compression and language modeling. In this work we adapt the well studied Winnow algorithm to the task of learning PSTs. The proposed algorithm automatically grows the tree, so that it provably remains competitive with any fixed PST determined in hindsight. At the same time we prove that the depth of the tree grows only logarithmically with the number of mistakes made by the algorithm. Finally, we empirically demonstrate its effectiveness in two different tasks.
GSM data services within CALM-based ITS solutions
Authors: Michal Vosatka, Tomas Zelinka
Venue: Proceedings of the 2009 Euro American Conference on Telematics and Information Systems: New Opportunities to increase Digital Citizenship (2009)

Transport telematics applications require availability of the seamless secure communications solutions covering selected usually wide areas and frequently serving extensive number of moving objects. Provided service is required to be served with selectable levels of service quality. There is available quite extensive range of wireless technologies provided either by public providers or privately. Described expectations lead to multi-path solutions where different wireless services are combined and selection of the best possible alternative is based on L3/L2 switching supported by different system level of the decision processes. Such approach is supported by ISO/CEN activities usually called as CALM family of standards. Relevant decisions must be based on deep understanding of applied technologies and precisely quantified requirements on system as well as subsystems performance indicators tolerance range. These limits are identified with aim to keep service provisioning on appropriate quality level with minimal impact of continuously changed conditions in time and served area. To cover identified system requirements each applied technology must be studied in detail to identify specific available performance indicators as well as their internal interactions to be able to monitor and manage each technology on appropriate quality level. This paper presents results of GSM data services laboratory measurement. Obtained results are compared with results of already published WiMax service analysis. These two access technologies belong definitely to the core alternatives applied within ITS and presented analysis represents necessary basis for future ITS CALM based system implementations.
Reverse k-Nearest Neighbor Search Based on Aggregate Point Access Methods
Authors: Hans-Peter Kriegel, Peer Kröger, Matthias Renz, Andreas Züfle, Alexander Katzdobler
Venue: Proceedings of the 21st International Conference on Scientific and Statistical Database Management (2009)

We propose an original solution for the general reverse k-nearest neighbor (RkNN) search problem in Euclidean spaces. Compared to the limitations of existing methods for the RkNN search, our approach works on top of Multi-Resolution Aggregate (MRA) versions of any index structures for multidimensional feature spaces where each non-leaf node is additionally associated with aggregate information like the sum of all leaf-entries indexed by that node. Our solution outperforms the state-of-the-art RkNN algorithms in terms of query execution times because it exploits advanced strategies for pruning index entries.
Speeding Up HMM Decoding and Training by Exploiting Sequence Repetitions
Authors: Yury Lifshits, Shay Mozes, Oren Weimann, Michal Ziv-Ukelson
Venue: Algorithmica (2009)

We present a method to speed up the dynamic program algorithms used for solving the HMM decoding and training problems for discrete time-independent HMMs. We discuss the application of our method to Viterbi&#x2019;s decoding and training algorithms (IEEE Trans. Inform. Theory IT-13:260&#x2013;269, 1967), as well as to the forward-backward and Baum-Welch (Inequalities 3:1&#x2013;8, 1972) algorithms. Our approach is based on identifying repeated substrings in the observed input sequence. Initially, we show how to exploit repetitions of all sufficiently small substrings (this is similar to the Four Russians method). Then, we describe four algorithms based alternatively on run length encoding (RLE), Lempel-Ziv (LZ78) parsing, grammar-based compression (SLP), and byte pair encoding (BPE). Compared to Viterbi&#x2019;s algorithm, we achieve speedups of &#x0398;(log&#x2009;n) using the Four Russians method, $\Omega(\frac{r}{\log r})$using RLE, $\Omega(\frac{\log n}{k})$using LZ78, $\Omega(\frac{r}{k})$using SLP, and &#x03a9;(r) using BPE, where k is the number of hidden states, n is the length of the observed sequence and r is its compression ratio (under each compression scheme). Our experimental results demonstrate that our new algorithms are indeed faster in practice. We also discuss a parallel implementation of our algorithms.
Monitoring and control of large systems with MonALISA
Authors: Iosif Legrand, Ramiro Voicu, Catalin Cirstoiu Costin Grigoras, Latchezar Betev, Alexandru Costan
Venue: Communications of the ACM (2009)

MonALISA developers describe how it works, the key design principles behind it, and the biggest technical challenges in building it.
When do Students Interrupt Help? Effects of Time, Help Type, and Individual Differences
Authors: Cecily Heiner, Joseph Beck, Jack Mostow
Venue: Proceeding of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology (2005)

When do students interrupt help to request different help? To study this question, we embedded a within-subject experiment in the 2003-2004 version of Project LISTEN's Reading Tutor. We analyze 168,983 trials of this experiment, randomized by help type, and report patterns in when students choose to interrupt help. Using the amount of prior help, we fit an exponential curve to predict interruption rate with an r2 of 0.97 on aggregate data and an r2 of 0.22 on individual data. To improve the model fit for individual data, we adjust our model to account for different types of help and individual differences. Finally, we report small but significant correlations between a student parameter in our model and external measures of motivation and academic performance.
Bridging the gap: Discrete-Event Systems for software engineering (short position paper)
Authors: Juergen Dingel, Karen Rudie, Chris Dragert
Venue: Proceedings of the 2nd Canadian Conference on Computer Science and Software Engineering (2009)

Discrete-Event System Theory (DES) allows the automatic control of a system with respect to a specification describing desirable sequences of events. It offers a large body of work with strong theoretical results and tool support. In this paper, we advocate the application of DES to software engineering problems. We summarize preliminary results and provide a list of directions for future research.
Design and analysis of a multiscale active queue management scheme
Authors: Qi-Jin Ji, Yong-Qiang Dong
Venue: Journal of Computer Science and Technology (2006)

Since Internet is dominated by TCP-based applications, active queue management (AQM) is considered as an effective way for congestion control. However, most AQM schemes suffer obvious performance degradation with dynamic traffic. Extensive measurements found that Internet traffic is extremely bursty and possibly self-similar. We propose in this paper a new AQM scheme called multiscale controller (MSC) based on the understanding of traffic burstiness in multiple time, scale. Different from most of other AQM schemes, MSC combines rate-based and queue-based control in two time scales. While the rate-based dropping on burst level (large time scales) determines the packet drop aggressiveness and is responsible for low and stable queuing delay, good robustness and responsiveness, the queue-based modulation of the packet drop probability on packet level (small time scales) will bring low loss and high throughput. Stability analysis is performed based on a fluid-flow model of the TCP/MSC congestion control system and simulation results show that MSC outperforms many of the current AQM schemes.
Improving decision making in fault detection and isolation using model validity
Authors: S. Gentil, S. Lesecq, A. Barraud
Venue: Engineering Applications of Artificial Intelligence (2009)

Fault detection and isolation commonly relies on the computation of numerical residuals deduced from the analytical model of the process to be diagnosed. This model can be more or less valid, due to the difficulty of getting good data sets in industry and to the process ageing. If this validity is not taken into account during the evaluation of the residuals, false symptoms may be produced and consequently a false diagnosis. The aim of this paper is to explicitly take into account the validity of the model to make the diagnostic decision. The decision formulation is inspired by the logical approach to consistency-based diagnosis proposed by the artificial intelligence community. However, in this paper fuzzy aggregation is used because it allows gradual diagnostic decision making. A fuzzy indicator of the model validity is first evaluated a priori during the model identification and further modified on-line to take into account actual operating conditions. The numerical residuals are fuzzified, taking into consideration their dynamical evolution. Finally, the model validity is aggregated on-line with the fuzzy residuals in order to provide fuzzy symptoms and a diagnostic decision that reflects both the residual value and the model validity. Academic examples illustrate the benefits of the proposed method.
Conservative numerical simulation of multi-component transport in two-dimensional unsteady shallow water flow
Authors: J. Murillo, P. García-Navarro, J. Burguete
Venue: Journal of Computational Physics (2009)

An explicit finite volume model to simulate two-dimensional shallow water flow with multi-component transport is presented. The governing system of coupled conservation laws demands numerical techniques to avoid unrealistic values of the transported scalars that cannot be avoided by decreasing the size of the time step. The presence of non conservative products such as bed slope and friction terms, and other source terms like diffusion and reaction, can make necessary the reduction of the time step given by the Courant number. A suitable flux difference redistribution that prevents instability and ensures conservation at all times is used to deal with the non-conservative terms and becomes necessary in cases of transient boundaries over dry bed. The resulting method belongs to the category of well-balanced Roe schemes and is able to handle steady cases with flow in motion. Test cases with exact solution, including transient boundaries, bed slope, friction, and reaction terms are used to validate the numerical scheme. Laboratory experiments are used to validate the techniques when dealing with complex systems as the @k-@e model. The results of the proposed numerical schemes are compared with the ones obtained when using uncoupled formulations.
Technical Section: Smooth reverse subdivision
Authors: Javad Sadeghi, Faramarz F. Samavati
Venue: Computers and Graphics (2009)

In this paper we present a new multiresolution framework that takes into consideration reducing the coarse points' energy during decomposition. We start from initial biorthogonal filters to include energy minimization in multiresolution. Decomposition and reconstruction are main operations for any multiresolution representation. We formulate decomposition as smooth reverse subdivision, based on a least squares problem. Both approximation of overall shape and energy are taken into account in the least squares formulation through different weights. Using this method, significant smoothness in decomposition of curves and tensor product surfaces can be achieved; while their overall shape is preserved. Having smooth coarse points yields details with maximum characteristics. Our method works well with synthesizing applications in which re-using high-energy details is important. We use our method for finding the smooth reverse of three common subdivision schemes. We also provide examples of our method in curve synthesis and terrain synthesis applications.
Improving Privacy of Recommender Agents by Means of Full Dissociation
Authors: Sonia Delfin, Claudia Carrillo, Eduard Muntaner, Araceli Moreno, Salvador Ibarra, Josep Lluis de la Rosa
Venue: Proceeding of the 2006 conference on Artificial Intelligence Research and Development (2006)

Our approach is to give privacy to the profile and behaviour of the user; the state of the art for privacy consists of encryption algorithms, occultation and temporary association of a user's information. In all cases these aspects present pros and cons. A primary disadvantage is that within a certain amount of time an attacker is capable of reconstruct the original information (encryptation), finding the information (occultation) and relating it to the original user (temporary association). In our approach, full dissociation is used to impede any relation with the original user. It is the concept of full dissociation which considerably reduces the available time for an attacker to discover the relation with the original user.
An efficient sparse metric learning in high-dimensional space via l1-penalized log-determinant regularization
Authors: Guo-Jun Qi, Jinhui Tang, Zheng-Jun Zha, Tat-Seng Chua, Hong-Jiang Zhang
Venue: Proceedings of the 26th Annual International Conference on Machine Learning (2009)

This paper proposes an efficient sparse metric learning algorithm in high dimensional space via an l1-penalized log-determinant regularization. Compare to the most existing distance metric learning algorithms, the proposed algorithm exploits the sparsity nature underlying the intrinsic high dimensional feature space. This sparsity prior of learning distance metric serves to regularize the complexity of the distance model especially in the "less example number p and high dimension d" setting. Theoretically, by analogy to the covariance estimation problem, we find the proposed distance learning algorithm has a consistent result at rate O (&radic;m2 log d)/n) to the target distance matrix with at most m nonzeros per row. Moreover, from the implementation perspective, this l1-penalized log-determinant formulation can be efficiently optimized in a block coordinate descent fashion which is much faster than the standard semi-definite programming which has been widely adopted in many other advanced distance learning algorithms. We compare this algorithm with other state-of-the-art ones on various datasets and competitive results are obtained.
Workflow Management System in Software Production & Maintenance
Authors: Pawel Markowski
Venue: Proceeding of the 2005 conference on Software Engineering: Evolution and Emerging Technologies (2005)

The maintenance is the longest period of software product life cycle and the most expensive, therefore increasing efficiency and reducing costs in this domain is important issue for any software company. Treating maintenance and also product development as business processes, we can use workflow software to optimize and automate their execution. Tytan Workflow is advanced system for business process modeling which is used in software engineering related activities. In this article feauters of system and examples of process models was introduced.
“Higher-κ” dielectrics for advanced silicon microelectronic devices: A combinatorial research study
Authors: M. L. Green, P. K. Schenck, K. -S. Chang, J. Ruglovsky, M. Vaudin
Venue: Microelectronic Engineering (2009)

Combinatorial methodology is used to rapidly screen suitable ternary higher-@k dielectrics for future complementary metal oxide semiconductor (CMOS), and dynamic random access memory (DRAM) devices. Dielectric constant (@k) and leakage current (L"C) were mapped from capacitance-voltage (C-V) and current-voltage (I-V) measurements. HfO"2-TiO"2-Y"2O"3 library films, made by pulsed laser deposition (PLD), have been characterized. We found a band of compositions in the middle of the HfO"2-TiO"2-Y"2O"3 phase diagram that have dielectric constants in the range of 50-80, with reasonably low leakage currents, that are therefore promising for these applications.
Query segmentation using conditional random fields
Authors: Xiaohui Yu, Huxia Shi
Venue: Proceedings of the First International Workshop on Keyword Search on Structured Data (2009)

A growing mount of available text data are being stored in relational databases, giving rise to an increasing need for the RDBMSs to support effective text retrieval. In this paper, we address the problem of keyword query segmentation, i.e., how to group nearby keywords in a query into segments. This operation can greatly benefit both the quality and the efficiency of the subsequent search operations. Compared with previous work, the proposed approach is based on Conditional Random Fields (CRF), and provides a principled statistical model that can be learned from query logs and easily adapt to user preferences. Extensive experiments on two real datasets confirm the effectiveness the efficiency of the proposed approach.
On the expressiveness and complexity of randomization in finite state monitors
Authors: Rohit Chadha, A. Prasad Sistla, Mahesh Viswanathan
Venue: Journal of the ACM (JACM) (2009)

In this article, we introduce the model of finite state probabilistic monitors (FPM), which are finite state automata on infinite strings that have probabilistic transitions and an absorbing reject state. FPMs are a natural automata model that can be seen as either randomized run-time monitoring algorithms or as models of open, probabilistic reactive systems that can fail. We give a number of results that characterize, topologically as well as with respect to their computational power, the sets of languages recognized by FPMs. We also study the emptiness and universality problems for such automata and give exact complexity bounds for these problems.
Towards the Modularization of C++ Concept Maps
Authors: Zalán Szűgyi, Ádám Sipos, Zoltán Porkoláb
Venue: Electronic Notes in Theoretical Computer Science (ENTCS) (2009)

Concept is a new and powerful language element being introduced in the next C++ standard. With the help of concepts we can define the properties a template requires from its type arguments. If a type does not fulfill the requirements syntactically, but semantically, the connection must be declared with the use of a concept_map. Often the description of the semantic matching results in long codes that need to be modularized. In this paper we present an extension to the concept_map language constructs that enables this transformation. We introduce the well-known public, protected, private class arrangement scheme into concept_maps. We present our preprocessor, that transforms the modularized code into regular code to be compiled by ConceptGCC, the experimental Concept C++ compiler.
Mining the Arabidopsis and rice genomes for cyclophilin protein families
Authors: S. O. Opiyo, E. N. Moriyama
Venue: International Journal of Bioinformatics Research and Applications (2009)

Cyclophilins, which possess peptidyl-prolyl isomerase activity, are cellular targets of immunosuppressant drugs and involved in a wide variety of functions. While the Arabidopsis thaliana genome contains the largest number of cyclophilins, the number of plant cyclophilins available in databases is small compared to that of other organisms. It implies that many cyclophilins are yet to be identified in plants. In order to identify cyclophilin candidates from available plant sequence data, we examined alignment-free methods based on Partial Least Squares (PLS). PLS classifier performed better than profile hidden Markov models and PSI-BLAST in identifying cyclophilins from the Arabidopsis and rice genomes.
Secure Hamming Distance Based Computation and Its Applications
Authors: Ayman Jarrous, Benny Pinkas
Venue: Proceedings of the 7th International Conference on Applied Cryptography and Network Security (2009)

This paper examines secure two-party computation of functions which depend only on the Hamming distance of the inputs of the two parties. We present efficient protocols for computing these functions. In particular, we present protocols which are secure in the sense of full simulatability against malicious adversaries.We show different applications of this family of functions, including a protocol we call m-point-SPIR, which is an efficient variant of symmetric private information retrieval (SPIR). It can be used if the server's database contains N entries, at most N/logN of which have individual values, and the rest are set to some default value. This variant of PIR is unique since it can be based on the existence of OT alone.