ppxscal/embedding_network huggingface dataset:
An Architectural Paradigm for Collaborative Semantic Indexing of Multimedia Data Objects
Authors: Clement H. Leung, Jiming Liu, Alice W. Chan, Alfredo Milani
Venue: Proceedings of the 10th international conference on Visual Information Systems: Web-Based Visual Information Search and Management (2008)

A challenging problem facing the semantic search of multimedia data objects is the ability to index them. Here, we present an architectural paradigm for collaborative semantic indexing, which makes use of a dynamic evolutionary approach. By capturing, analyzing and interpreting user response and query behavior, the patterns of searching and finding multimedia data objects may be established. Within the present architectural paradigm, the semantic index may be dynamically constructed, validated, and built-up, where the performance of the system will increase as time progresses. Our system also incorporates a high degree of robustness and fault-tolerance whereby inappropriate index terms will be gradually eliminated from the index, while appropriate ones will be reinforced. We also incorporate genetic variations into the design to allow objects which may otherwise be hidden to be discovered. Experimental results indicate that the present approach is able to confer significant performance benefits in the semantic searching and discovery of a wide variety of multimedia data objects.
Solution Method Using Correlated Noise for TSP
Authors: Atsuko Goto, Masaki Kawamura
Venue: Neural Information Processing: 14th International Conference, ICONIP 2007, Kitakyushu, Japan, November 13-16, 2007, Revised Selected Papers, Part I (2007)

We suggest solution method for optimization problems using correlated noises. The correlated noises are introduced to neural networks to discuss mechanism of synfire chain. Kawamura and Okada have introduced correlated noises to associative memory models and have analyzed those dynamics. In the associative memory models, memory patterns are memorized as attractors in the minimum of the system. They found the correlated noise can make the state transit between the attractors. However, the mechanism of the state transition has not been known enough yet. One the other hand, for combinational optimization problems, the energy function of a problem can be defined. Therefore, finding a optimum solution is finding a minima of the energy function. The steepest descent method searches one of the solutions by going down along the gradient direction. By this method, however, the state is usually trapped in a local minimum of the system. In order to escape from the local minimum, the simulated annealing, i.e. Metropolis method, or chaotic disturbance is introduced. These methods can be represented by adding thermal noises or chaotic inputs to the dynamic equation.In this paper, we show that correlated noises introduced to neural networks can be applied to solve the optimization problems. We solve the TSP that is a typical combinational optimization problem of NP-hard, and evaluated solutions obtained by using the steepest descent method, the simulated annealing and the proposed method with the correlated noises. As results, in the case of ten cities, the proposed method with correlated noises can obtain more optimum solutions than the steepest descent method and the simulated annealing. In the cases of large numbers of cites, where it is hard to find one of the optimum solutions, our method can obtain solutions at least as same level as the simulated annealing.
Trackside DEIRA: a dynamic engaging intelligent reporter agent
Authors: François L. A. Knoppel, Almer S. Tigelaar, Danny Oude Bos, Thijs Alofs, Zsófia Ruttkay
Venue: Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 1 (2008)

DEIRA is a virtual agent commenting on virtual horse races in real time. DEIRA analyses the state of the race, acts emotionally and comments about the situation in a believable and engaging way, using synthesized speech and facial expressions. In this paper we discuss the challenges, explain the computational models for the cognitive, emotional and communicative behavior, and account on implementation and feedback from users.
The MOD Keyboard
Authors: Peter Nelson, Larry Korba, Gordon Park, David Crabtree
Venue: IEEE Micro (1983)

A special plug-in cartridge for the VIC-20 converts it into a dynamic keyboard emulator that enables a handicapped user to control a second, unmodified computer.
Multiple Shift Scheduling of Hierarchical Workforce with Multiple Work Centers
Authors: Salem M. Al-Yakoob, Hanif D. Sherali
Venue: Informatica (2007)

This paper is concerned with an employee scheduling problem involving multiple shifts and work centers, where employees belong to a hierarchy of categories having downward substitutability. An employee at a higher category may perform the duties of an employee at a lower category, but not vice versa. However, a higher category employee receives a higher compensation than a lower category employee. For a given work center, the demand for each category during a given shift is fixed for the weekdays, and may differ from that on weekends. Two objectives need to be achieved: The first is to find a minimum-cost workforce mix of categories of employees that is needed to satisfy specified demand requirements, and the second is to assign the selected employees to shifts and work centers taking into consideration their preferences for shifts, work centers, and off-days. A mixed-integer programming model is initially developed for the problem, based on which a specialized scheduling heuristic is subsequently developed for the problem. Computational results reported reveal that the proposed heuristic determines solutions proven to lie within 92-99% of optimality for a number of realistic test problems. This work was supported by Kuwait University under Research Grant No. [SM06/02] and by the National Science Foundation under Research Grant No. [DMI-0094462]. Special thanks to Mrs. Fatima Al-awadi for her contributions to the computational implementation of the scheduling algorithm.
Separating Global Motion Components in Transparent Visual Stimuli --- A Phenomenological Analysis
Authors: Andrew Meso, Johannes M. Zanker
Venue: Proceedings of the 18th international conference on Artificial Neural Networks, Part II (2008)

When two distinct movements overlap in the same region of the visual field, human observers may perceive motion transparency. This perception requires the visual system to separate informative and non informative motion signals into transparent components. In this study, we explored the computational constraints in solving this signal separation task - particularly for the stimulus configuration where two grating components move in the same direction at different speeds. We developed a phenomenological model which demonstrates that separation can be achieved only for stimuli with a broadband Fourier spectrum. The model identifies the informative component signals from the non informative signals by considering edges. This approach is shown to be limited by an edge sensitive spatial filtering of the image sequence, the threshold tolerance for local signals considered and the number of iterative computational steps.
Improving memory hierarchy performance with addressless preload, order-free lsq, and runahead scheduling
Authors: Jih-Kwon Peir
Venue:  (2007)

The average memory access latency is determined by three primary factors, cache hit latency, miss rate, and miss penalty. It is well known that cache miss penalty in processor cycles continues to grow. For those memory-bound workloads, a promising alternative is to exploit memory-level parallelism by overlapping multiple memory accesses. We study P-load scheme (P-load stands for Preload), an efficient solution to reduce the cache miss penalty by overlapping cache misses. To reduce cache misses, we also introduce a cache organization with an efficient replacement policy to specifically reduce conflict misses. A recent trend is to fetch and issue multiple instructions from multiple threads at the same time on one processor. This design benefits much from resource sharing among multiple threads. However, contentions of shared resources including caches, instruction issue window and instruction window may hamper the performance improvement from multi-threading schemes. In the third proposed research, we evaluate a technique to solve the resource contention problem in multi-threading environment. Store-load forwarding is a critical aspect of dynamically scheduled execution in modern processors. Conventional processors implement store-load forwarding by buffering the addresses and data values of all in-flight stores in an age-ordered store queue. A load accesses the data cache and in parallel associatively searches the store queue for older stores with matching addresses. Associative structures can be made fast, but often at the cost of substantial additional energy, area, and/or design effort. We introduce a new order-free store queue that decouples the matching of the store/load address and its corresponding age-based priority encoding logic from the original store queue and largely decreases the hardware complexity.
A Person Tracking System for CHIL Meetings
Authors: Alessio Brutti
Venue: Multimodal Technologies for Perception of Humans: International Evaluation Workshops CLEAR 2007 and RT 2007, Baltimore, MD, USA, May 8-11, 2007, Revised Selected Papers (2008)

This paper presents the audio based tracking system designed at FBK-irst laboratories for the CLEAR 2007 evaluation campaign. The tracker relies on the Global Coherence Field theory that has proved to efficiently deal with the foreseen scenarios. Particular emphasis is given to the post-processing of localization hypotheses which guarantees smooth speaker trajectories and is crucial for the overall performance of the system. The system is also equipped with a speech activity detector based on Hidden Markov Models. The performance delivered by the proposed tracker presents a considerable gain with respect to the previous evaluation. An attempt to devise a multimodal tracker based on merging outputs of a video and an audio trackers is also described. 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
Separating Sublinear Time Computations by Approximate Diameter
Authors: Bin Fu, Zhiyu Zhao
Venue: Proceedings of the 2nd international conference on Combinatorial Optimization and Applications (2008)

We study sublinear time complexity and algorithm to approximate the diameter for a sequence S = p 1 p 2 ¿ p n of points in a metric space, in which every pair of two consecutive points p i and p i + 1 in the sequence S has the same distance. The diameter of S is the largest distance between two points p i and p j in S. The approximate diameter problem is investigated under deterministic, zero error randomized, and bounded error randomized models. We obtain a class of separations about the sublinear time computations using various versions of the approximate diameter problem based on the restriction about the format of input data.
Locality Preserving Projection in Orthogonal Domain
Authors: Zhonglong Zheng, Jianmin Zhao
Venue: Proceedings of the 2008 Congress on Image and Signal Processing, Vol. 4 - Volume 04 (2008)

Locality Preserving Projection (LPP), as a linear version of manifold learning algorithm, has attracted considerable interests in recent years. When LPP is applied to image representation and recognition, PCA is used for dimensionality reduction first. In this paper, the theoretical foundation of why LPP can perform in such orthonormal transformed subspace is presented. Based on this theoretical framework, we prove that LPP can be directly implemented in discrete cosine transform (DCT) domain. The motivation is derived from the widely applications of DCT in JPEG and MPEG standard on the one hand, and from the initially reduction of computational cost on the other hand. Experiments demonstrate competitive performance of the proposed method.
Design of M-Ary Low Correlation Zone Sequence Sets by Interleaving
Authors: Jin-Ho Chung, Kyeongcheol Yang
Venue: Proceedings of the 5th international conference on Sequences and Their Applications (2008)

In this paper we present a new method to construct an M-ary low correlation zone (LCZ) sequence set from an M-ary sequence with good autocorrelation by using the interleaved technique, where M is an even integer. We also show that the constructed LCZ sequence sets are optimal or nearly optimal with respect to the Tang-Fan-Matsufuji bound. Due to the flexibility in the choice of alphabet size, LCZ size, and period, our construction may be applied to various situations in quasi-synchronous code-division multiple access environment.
Introduction to Software Product Line Adoption
Authors: Linda M. Northrop, Lawrence G. Jones
Venue: Proceedings of the 2008 12th International Software Product Line Conference (2008)

This tutorial describes a phased, pattern-based approach to software product line adoption. It reviews the challenges of product line adoption; introduces a roadmap for phased, product line adoption; describes adoption planning artifacts; and establishes linkages with other improvement efforts.
Application of Optimization Technique for GPS Navigation Kalman Filter Adaptation
Authors: Dah-Jing Jwo, Shun-Chieh Chang
Venue: Proceedings of the 4th international conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications - with Aspects of Theoretical and Methodological Issues (2008)

The position-velocity (PV) process model can be applied to the GPS Kalman filter adequately when navigating a vehicle with constant speed. However, when an abrupt acceleration motion occurs, the filtering solution becomes very poor or even diverges. To avoid the limitation of the Kalman filter, the particle swarm optimization can be incorporated into the filtering mechanism as dynamic model corrector. The PSO can be utilized as the noise-adaptive mechanism to tune the covariance matrix of process noise and overcome the deficiency of Kalman filter. In this paper, PSO-aided Kalman filter approach is employed for tuning the covariance of the GPS Kalman filter so as to reduce the estimation error during substantial maneuvering. Performance evaluation for the PSO-aided Kalman filter as compared to the conventional Kalman filter is provided.
Perceptions and importance of user friendliness of IR systems according to users' individual characteristics and academic discipline
Authors: Polona Vilar, Maja Žumer
Venue: Journal of the American Society for Information Science and Technology (2008)

This article presents one part of a wider study, performed at the Department of library and information science and book studies (LIS & BS) at the University of Ljubljana (UL). The study investigated the perceptions of user friendliness of information-retrieval systems (IRS) and the role of individual characteristics of users in these perceptions. Based on an expert study, a user study with 61 postgraduate students of the UL was performed. Three interfaces of e-journals were studied: Science Direct, Proquest Direct, and Ebsco Host. Questionnaires and observations were used for data collection. The users'perceptions of user friendliness and of importance of auxiliary functions were investigated. Also, the connections between these perceptions and the users'individual characteristics were identified. Three sets of individual characteristics were included: approaches to studying, thinking styles, and hemisphere leanings. In connection with the dimensions of individual characteristics, very different perceptions of user friendliness were expressed. Some dimensions of individual characteristics were also found to be connected to the users'academic areas. It is shown that participants from different academic areas have different requirements and perceptions of user friendliness. The results of the study are relevant for the design of the user interfaces of disciplinary IR systems. They also have implications for other areas, for example, user education and training. &copy; 2008 Wiley Periodicals, Inc.
The Uncertainty of the Truth
Authors: Michel Deriaz
Venue: Proceedings of the 2008 Sixth Annual Conference on Privacy, Security and Trust (2008)

How to trust without knowing the truth? This is probably the key question that arises while designing applications using virtual tags. A virtual tag is a geo-referenced note that is visible for all the people that are in a specific place. But what if you see a tag about an event or an object that is not here? How to know if you are facing a spam attack, or if the tag is simply outdated? And, how to update the trust values of the author and the other people that confirmed the tag, since you do not know if they are honest? To answer these questions, we designed and implemented FoxyTag, a free and collaborative system which consist in posting virtual tags over speed cameras in order to warn the other drivers. We used it to test our new generic trust engine and got very promising results.
From Unstructured Data to Actionable Intelligence
Authors: Ramana Rao
Venue: IT Professional (2003)

There's content everywhere, but not the information you need. Content analysis can organize a pile of text into a richly accessible repository.
A Risk-Minimizing Model Under Uncertainty in Portfolio
Authors: Yuji Yoshida
Venue: Proceedings of the 12th international Fuzzy Systems Association world congress on Foundations of Fuzzy Logic and Soft Computing (2007)

A risk-minimizing portfolio model under uncertainty is discussed. In the uncertainty model, the randomness and fuzziness are evaluated respectively by the probabilistic expectation and mean values with evaluation weights and ¿-mean functions. The means, variances and the measurements of fuzziness for fuzzy numbers/fuzzy random variables are applied in the possibility case and the necessity case, and a risk estimation is derived from both random factors and fuzzy factors in the model. By quadratic programming approach, we derive a solution of the risk-minimizing portfolio problem. It is shown that the solution is a tangency portfolio. A numerical example is given to illustrate our idea.
Task Model Refinement with Meta Operators
Authors: Maik Wurdel, Daniel Sinnig, Peter Forbrig
Venue: Interactive Systems. Design, Specification, and Verification: 15th International Workshop, DSV-IS 2008 Kingston, Canada, July 16-18, 2008 Revised Papers (2008)

In model-based user interface (UI) development task models are successively refined into more detailed task specifications. To ensure that analysis information is correctly translated into requirements and design artifacts it is important to verify that for each transformation step the derived task model is a valid refinement of its base specification. In this paper we present a versatile refinement relation between task models based on the principle of mandatory scenario equivalence. Which scenarios are mandatory is determined by metaoperators. These operators are assigned to tasks by the requirements engineer depending on the role of the task model in the development lifecycle.
On Sparsity Maximization in Tomographic Particle Image Reconstruction
Authors: Stefania Petra, Andreas Schröder, Bernhard Wieneke, Christoph Schnörr
Venue: Proceedings of the 30th DAGM symposium on Pattern Recognition (2008)

This work focuses on tomographic image reconstruction in experimental fluid mechanics (TomoPIV), a recently established 3D particle image velocimetry technique. Corresponding 2D image sequences (projections) and the 3D reconstruction via tomographical methods provides the basis for estimating turbulent flows and related flow patterns through image processing. TomoPIV employs undersampling to make the high-speed imaging process feasible, resulting in an ill-posed image reconstruction problem. We address the corresponding basic problems involved and point out promising optimization criteria for reconstruction based on sparsity maximization, that perform favorably in comparison to classical algebraic methods currently in use for TomoPIV.
The Development of Reliabililty in Industrial Control Systems
Authors: Theodore Williams
Venue: IEEE Micro (1984)

Hierarchical organization and distributed computing capability are the keys to the highly fault-tolerant, plant-wide control and management systems users demand today.
Effective Pruning Techniques for Mining Quasi-Cliques
Authors: Guimei Liu, Limsoon Wong
Venue: Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II (2008)

Many real-world datasets, such as biological networks and social networks, can be modeled as graphs. It is interesting to discover densely connected subgraphs from these graphs, as such subgraphs represent groups of objects sharing some common properties. Several algorithms have been proposed to mine quasi-cliques from undirected graphs, but they have not fully utilized the minimum degree constraint for pruning. In this paper, we propose an efficient algorithm called Quick to find maximal quasi-cliques from undirected graphs. The Quick algorithm uses several effective pruning techniques based on the degree of the vertices to prune unqualified vertices as early as possible, and these pruning techniques can be integrated into existing algorithms to improve their performance as well. Our experiment results show that Quick is orders of magnitude faster than previous work on mining quasi-cliques.
Codebook Design for Speech Guided Car Infotainment Systems
Authors: Martin Raab, Rainer Gruhn, Elmar Noeth
Venue: Proceedings of the 4th IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems (2008)

In car infotainment systems commands and other words in the user's main language must be recognized with maximum accuracy, but it should be possible to use foreign names as they frequently occur in music titles or city names. Previous approaches did not address the constraint of conserving the main language performance when they extended their systems to cover multilingual input.In this paper we present an approach for speech recognition of multiple languages with constrained resources on embedded devices. Speech recognizers on such systems are typically to-date semi-continuous speech recognizers, which are based on vector quantization.We provide evidence that common vector quantization algorithms are not optimal for such systems when they have to cope with input from multiple languages. Our new method combines information from multiple languages and creates a new codebook that can be used for efficient vector quantization in multilingual scenarios. Experiments show significant improved speech recognition results.
Computing credit spreads under imprecise information
Authors: Elettra Agliardi, Rossella Agliardi
Venue: Proceedings of the WSEAS International Conference on Applied Computing Conference (2008)

This paper experiments the effect of imperfect information on the value of defaultable bonds. The numerical results show that the fuzziness of the stochastic underlying asset and/or the barrier triggering the default have material impact on the qualitative shape of the term structures of credit spreads.