ppxscal/embedding_network huggingface dataset:
Voice as a Key
Authors: Ryszard Tadeusiewicz, Grayna Demenko
Venue: Proceedings of the 2009 International Conference on Biometrics and Kansei Engineering (2009)

Biometric methods numerous advantages are known very well for every computer security specialist and are in general highly valued. One of the most interesting methods used for biometric protection of computer system (and other objects) is speech parameters extraction, analysis and recognition. Problem under consideration is concentrated on methods showing, how to distinguish between voices of particular people and how to do it independent on the text pronounced by recognized person. Methods used for this purpose are complementary ones in comparison with widely used speech recognition goals, where we must understand the merit content of the utterance disregarding individual features of the voices of different speakers taken into account. The paper shows general problems related to biometric speaker identification and gives general outline, how to use voice as a key for guarded systems.
Designing a Dynamic Replication Engine for Grid Shared Data Programming
Authors: Georgiana Macariu, Dacian Tudor, Vladimir Cretu
Venue: Proceedings of the 2008 10th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2008)

Besides the complexity of grid application program-ming, achieving high performance has become a real challenge inlarge scale grid systems mainly because of the high latencies andunpredictable communication paths. We follow the idea of shareddata programming in grid environments and we design a replica-tion component for a shared data programming framework withdynamic replication capabilities. We define several replicationpolicies that are dynamically used during the application life-cycle in order to minimize the communication cost and providebetter performance. We evaluate several application scenarios inorder to prove that dynamic policy based replication can improvethe overall application performance and reduce resource accesstime.
UNT: SubFinder: combining knowledge sources for automatic lexical substitution
Authors: Samer Hassan, Andras Csomai, Carmen Banea, Ravi Sinha, Rada Mihalcea
Venue: Proceedings of the 4th International Workshop on Semantic Evaluations (2007)

This paper describes the University of North Texas SubFinder system. The system is able to provide the most likely set of substitutes for a word in a given context, by combining several techniques and knowledge sources. SubFinder has successfully participated in the best and out of ten (oot) tracks in the SemEval lexical substitution task, consistently ranking in the first or second place.
Online Mass Flow Prediction in CFB Boilers
Authors: Andriy Ivannikov, Mykola Pechenizkiy, Jorn Bakker, Timo Leino, Mikko Jegoroff, Tommi Kärkkäinen, Sami Äyrämö
Venue: Proceedings of the 9th Industrial Conference on Advances in Data Mining. Applications and Theoretical Aspects (2009)

Fuel feeding and inhomogeneity of fuel typically cause process fluctuations in the circulating fluidized bed (CFB) process. If control systems fail to compensate for the fluctuations, the whole plant will suffer from fluctuations that are reinforced by the closed-loop controls. This phenomenon causes a reduction of efficiency and lifetime of process components. Therefore, domain experts are interested in developing tools and techniques for getting better understanding of underlying processes and their mutual dependencies in CFB boilers. In this paper we consider an application of data mining technology to the analysis of time series data from a pilot CFB reactor. Namely, we present a rather simple and intuitive approach for online mass flow prediction in CFB boilers. This approach is based on learning and switching regression models. Additionally, noise canceling, and windowing mechanisms are used for improving the robustness of online prediction. We validate our approach with a set of simulation experiments with real data collected from the pilot CFB boiler.
Evolution of an empathetic digital entity: phase one
Authors: Margaret Manella Kozak
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 4 (2005)

This demonstration highlights the first of seven segments designed to develop a digital entity that will possess the potential for human empathy. The experiences in the first phase of the digital entity Zoe (Zero-One Entity) parallel a subset of learning and development activities encountered by human beings during their first nine months of existence. A website has been created to provide a window to observe Zoe's experiences and action selection process in order to make her basic learning observable, cumulative, and evolutionary. The human observer is invited to influence her action selection by setting the intensity of Zoe's digital personality traits such as assertiveness, reasoning ability, and disposition. Actions generate body-based and emotive-based feelings which are stored in memory structures. Significantly, these structures serve as a foundation for later stages of learning, understanding and reasoning.
Finite Element Analysis of the Rubber Sealing Yx-ring in Hydraulic Cylinder
Authors: Jian Xie, Gui Tian, Jun Chen
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 02 (2009)

This paper presents an analysis of the rubber sealing Yx-ring in hydraulic cylinder with finite element method and ANSYS software. The distribution nephogram of contact stress between the sealing ring and cylinder, and the relationship between the contact stress and the working pressure under different working conditions were obtained. Results show that the contact stress distributes asymmetrically and exhibits in the form of the pressure peak. With the increase of the working pressure, the contact stress increases correspondingly, and the region of high contact stress called main seal region becomes larger and shifts along the contact length slightly. The maximal contact stress is not only linear with the working pressure, but also always greater than the working pressure in working condition, which ensures the performance of the sealing Yx-ring.
The Complete Guide to Light
Authors: Mark Cleghorn
Venue:  (2009)

Master the light and you master the photographthat's the key idea in this hands-on guide to understanding and using lighting. Internationally known photographer Mark Cleghorn uses jargon-free language to explain exactly how light worksand how it can be manipulatedin the photographer's medium. Cleghorn covers such subjects as using natural and ambient light, maximizing the benefits of an on-camera flash, and applying innovative Photoshop techniques. To make things even easier, he provides photos and graphics of various lighting setups that demonstrate how the placement of equipment alters the final result. 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
Design Theory for Speed Control by Using Increasing Edge Rate
Authors: Shun-ying Zhu, Qin-mei Sun, Hong Wang
Venue: Proceedings of the 2009 International Conference on Measuring Technology and Mechatronics Automation - Volume 01 (2009)

Edge rate is an important source for driver’s perceptual speed. In this paper, the concept of edge rate and the theory about driver’s speed perception and control which based on edge rate were briefly described, and an introduction to the application effects of edge rate was also made. According to the concept of edge rate and Newton motion equation, a model fitting the comfortable uniformly decelerated motion was designed for speed control, which satisfied two restrictions, including the restriction of keeping edge rate increasing toward the directions of traffic and the restriction of time Weber’s law. Using the 3DMAX, the videos simulating car moving process on the freeway were made in which edge rate was a key manipulative parameter. Six males and two females took part in the experiments. 260 Subjectively Equal Speed experiments were implemented by using the Forced-Choice Method, and the reasonable bound of the edge rate value was educed by analyzing the experimental results. The Weber fraction was also determined through literature review. A case study was carried out in this paper, and the edge line spacing was calculated for controlling the speed from 120km/h down to 90km/h by the designed model. Comparison experiments were carried out between the condition when edge rate kept increasing and the condition when edge rate kept constant through the simulating video. The demonstration experiment indicated that the design mode of keeping edge rate increasing was more effective than the design mode of keeping edge rate constant.
Integrating Answer Set Modules into Agent Programs
Authors: Stefania Costantini
Venue: Proceedings of the 10th International Conference on Logic Programming and Nonmonotonic Reasoning (2009)

The use of ASP in agents has been advocated since long, with ASP mainly taking the form of Action Description Languages. These kind of ASP-based languages were first introduced in [1] and [2] and have been since then extended and refined in many subsequent papers by several authors. Action Description Languages are formal models used to describe dynamic domains, by focusing on the representation of effects of actions. In particular, an action specification represents the direct effects of each action on the state of the world, while the semantics of the language takes care of all the other aspects concerning the evolution of the world (e.g., the ramification problem). 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
Gem #58: Ada / Java exception handling
Authors: Quentin Ochem
Venue: ACM SIGAda Ada Letters (2009)

Ada and Java are two languages that rely heavily on exceptions. A large part of the Ada data model is based on the fact that data is checked at run time, and will raise various kinds of exceptions such as Constraint_Error when constraints are violated. Similarly, there are many cases where Java performs checks that can raise exceptions, among the most common being checks on casts and null dereferences. It is therefore extremely important to support exceptions that are properly propagated from one language to the other and even potentially caught/handled, without having to worry about the language of origin.
Jointly identifying predicates, arguments and senses using Markov logic
Authors: Ivan Meza-Ruiz, Sebastian Riedel
Venue: Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (2009)

In this paper we present a Markov Logic Network for Semantic Role Labelling that jointly performs predicate identification, frame disambiguation, argument identification and argument classification for all predicates in a sentence. Empirically we find that our approach is competitive: our best model would appear on par with the best entry in the CoNLL 2008 shared task open track, and at the 4th place of the closed track---right behind the systems that use significantly better parsers to generate their input features. Moreover, we observe that by fully capturing the complete SRL pipeline in a single probabilistic model we can achieve significant improvements over more isolated systems, in particular for out-of-domain data. Finally, we show that despite the joint approach, our system is still efficient.
A Performance Isolation Algorithm for Shared Virtualization Storage System
Authors: Ke Jian, Zhu Xu Dong, Na Wen-wu, Zhang Jun-wei, Han Xiao-ming, Zhang Jian-gang, Xu Lu
Venue: Proceedings of the 2009 IEEE International Conference on Networking, Architecture, and Storage (2009)

It is a challenging task that enables performance isolation while providing performance guarantees among applications that share storage infrastructure. This paper presents Admission-control-based Proportional Allocation (APA), a novel I/O request scheduler that combines the admission control of worst-case resources reserved with the proportional resources allocation to manage the bandwidth resources for performance isolation. APA has three characteristics: 1) admission control for I/O requests of applications; 2) fairness allocation for idle bandwidth resources; 3) performance monitoring and feedback-based weight adjustment. We implemented APA in a prototype Performance Virtual Storage System (PVSS). Through experiments on a real system, we show that APA has ability to provide the performance isolation and predictable performance guarantees, and to avoid the performance interference among virtual disks.
Agents Based Data Mining and Decision Support System
Authors: Serge Parshutin, Arkady Borisov
Venue: Agents and Data Mining Interaction: 4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15,2009, Revised Selected Papers (2009)

Production planning is the main aspect for a manufacturer affecting an income of a company. Correct production planning policy, chosen for the right product at the right moment in the product life cycle (PLC), lessens production, storing and other related costs. This arises such problems to be solved as defining the present a PLC phase of a product as also determining a transition point - a moment of time (period), when the PLC phase is changed.The paper presents the Agents Based Data Mining and Decision Support system, meant for supporting a production manager in his/her production planning decisions. The developed system is based on the analysis of historical demand for products and on the information about transitions between phases in life cycles of those products. The architecture of the developed system is presented as also an analysis of testing on the real-world data results is given.
Distribution-preserving statistical disclosure limitation
Authors: Simon D. Woodcock, Gary Benedetto
Venue: Computational Statistics Data Analysis (2009)

One approach to limiting disclosure risk in public-use microdata is to release multiply-imputed, partially synthetic data sets. These are data on actual respondents, but with confidential data replaced by multiply-imputed synthetic values. A mis-specified imputation model can invalidate inferences based on the partially synthetic data, because the imputation model determines the distribution of synthetic values. We present a practical method to generate synthetic values when the imputer has only limited information about the true data generating process. We combine a simple imputation model (such as regression) with density-based transformations that preserve the distribution of the confidential data, up to sampling error, on specified subdomains. We demonstrate through simulations and a large scale application that our approach preserves important statistical properties of the confidential data, including higher moments, with low disclosure risk.
Agent Assignment for Process Management: Pattern Based Agent Performance Evaluation
Authors: Stefan Jablonski, Ramzan Talib
Venue: Agents and Data Mining Interaction: 4th International Workshop, ADMI 2009, Budapest, Hungary, May 10-15,2009, Revised Selected Papers (2009)

In almost all workflow management system the role concept is determined once at the introduction of workflow application and is not reevaluated to observe how successfully certain processes are performed by the authorized agents. This paper describes an approach which evaluates how agents are working successfully and feed this information back for future agent assignment to achieve maximum business benefit for the enterprise. The approach is called Pattern based Agent Performance Evaluation (PAPE) and is based on machine learning technique combined with post processing technique. We report on the result of our experiments and discuss issues and improvement of our approach.
Identifying the Intent of a User Query Using Support Vector Machines
Authors: Marcelo Mendoza, Juan Zamora
Venue: Proceedings of the 16th International Symposium on String Processing and Information Retrieval (2009)

In this paper we introduce a high-precision query classification method to identify the intent of a user query given that it has been seen in the past based on informational, navigational, and transactional categorization. We propose using three vector representations of queries which, using support vector machines, allow past queries to be classified by user's intents. The queries have been represented as vectors using two factors drawn from click-through data: the time users take to review the documents they select and the popularity (quantity of preferences) of the selected documents. Experimental results show that time is the factor that yields higher precision in classification. The experiments shown in this work illustrate that the proposed classifiers can effectively identify the intent of past queries with high-precision.
Algorithm for Finding k-Vertex Out-trees and Its Application to k-Internal Out-branching Problem
Authors: Nathann Cohen, Fedor V. Fomin, Gregory Gutin, Eun Jung Kim, Saket Saurabh, Anders Yeo
Venue: Proceedings of the 15th Annual International Conference on Computing and Combinatorics (2009)

An out-tree T is an oriented tree with exactly one vertex of in-degree zero and a vertex x of T is called internal if its out-degree is positive. We design randomized and deterministic algorithms for deciding whether an input digraph contains a subgraph isomorphic to a given out-tree with k vertices. Both algorithms run in O *(5.704 k ) time. We apply the deterministic algorithm to obtain an algorithm of runtime O *(c k ), where c is a constant, for deciding whether an input digraph contains a spanning out-tree with at least k internal vertices. This answers in affirmative a question of Gutin, Razgon and Kim (Proc. AAIM'08).
Solving DisCSPs with penalty driven search
Authors: Muhammed Basharu, Ines Arana, Hatem Ahriz
Venue: Proceedings of the 20th national conference on Artificial intelligence - Volume 1 (2005)

We introduce the Distributed, Penalty-driven Local search algorithm (DisPeL) for solving Distributed Constraint Satisfaction Problems. DisPeL is a novel distributed iterative improvement algorithm which escapes local optima by the use of both temporary and incremental penalties and a tabu-like no-good store. We justify the use of these features and provide empirical results which demonstrate the competitiveness of the algorithm.
Target localization by resolving the time synchronization problem in istatic radar systems using space fast-time adaptive processor
Authors: D. Madurasinghe, A. P. Shaw
Venue: EURASIP Journal on Advances in Signal Processing (2009)

The proposed technique allows the radar receiver to accurately estimate the range of a large number of targets using a transmitter of opportunity as long as the location of the transmitter is known. The technique does not depend on the use of communication satellites or GPS systems, instead it relies on the availability of the direct transmit copy of the signal from the transmitter and the reflected paths off the various targets. An array-based space-fast time adaptive processor is implemented in order to estimate the path difference between the direct signal and the delayed signal, which bounces off the target. This procedure allows us to estimate the target distance as well as bearing.
Pivoting Algorithm for Optimization Model of Portfolio Rebalancing with Transaction Costs
Authors: Yanwu Liu, Zhongzhen Zhang
Venue: Proceedings of the 2009 International Conference on Computational Intelligence and Natural Computing - Volume 01 (2009)

Portfolio optimization is an important branch to which optimization methods are applied. Transaction costs have significant influence on portfolio rebalancing in practice. The introduction of transaction costs into optimal rebalancing model significantly enlarges the size of optimization problem and need more efficient algorithms. We deduce the relationships between the Karush-Kuhn-Tucker (KKT) conditions of the original model and those of its sub-problem. Pivoting algorithm can make full use of these relationships to obtain the optimal solution for the original model efficiently from that for its subproblem.
Bodily Explorations in Space: Social Experience of a Multimodal Art Installation
Authors: Giulio Jacucci, Anna Spagnolli, Alessandro Chalambalakis, Ann Morrison, Lassi Liikkanen, Stefano Roveda, Massimo Bertoncini
Venue: Proceedings of the 12th IFIP TC 13 International Conference on Human-Computer Interaction: Part II (2009)

We contribute with an extensive field study of a public interactive art installation that applies multimodal interface technologies. The installation is part of a Theater production on Galileo Galilei and includes: projected galaxies that are generated and move according to motion of visitors changing colour depending on their voices; projected stars that configure themselves around shadows of visitors. In the study we employ emotion scales (PANAS), qualitative analysis of questionnaire answers and video-recordings. PANAS rates indicate dominantly positive feelings, further described in the subjective verbalizations as gravitating around interest, ludic pleasure and transport. Through the video analysis, we identified three phases in the interaction with the artwork (circumspection, testing, play) and two pervasive features of these phases (experience sharing and imitation), which were also found in the verbalizations. Both video and verbalisations suggest that visitor's experience and ludic pleasure are rooted in the embodied, performative interaction with the installation, and is negotiated with the other visitors.
Improving the Accuracy of Space Mission Software Anomaly Frequency Estimates
Authors: Allen P. Nikora, Galen Balcom
Venue: Proceedings of the Third IEEE International Conference on Space Mission Challenges for Information Technology (2009)

Anomaly data can be used to estimate baseline values for operational mission software anomaly frequencies; these estimates can be used for future missions to determine whether software reliability is improving. The accuracy of anomaly frequency estimates can be affected by characteristics of the anomaly data and the problem reporting system maintaining that data. We have been using text mining and machine learning techniques to address one of these issues, in which the number of software-related anomalies is incorrectly reported because the problem reporting system does not tag them correctly. Results to date indicate that these techniques may substantially increase the accuracy of anomaly frequency estimates.