ppxscal/embedding_network huggingface dataset:
Continuous monitoring of skyline query over highly dynamic moving objects
Authors: Li Tian, Le Wang, Peng Zou, Yan Jia, Aiping Li
Venue: Proceedings of the 6th ACM international workshop on Data engineering for wireless and mobile access (2007)

We address the problem of continuous skyline computation on highly dynamic moving objects (i.e. objects with dynamic dimensions move in an unrestricted and unpredictable fashion), which is quite a different scenario from existing literatures on skyline algorithms. We propose a continuous skyline query processing strategy for static query point, and the main idea is as follows: (1) The work space is divided into lots of regular grids, and the valid objects are indexed by this data structure. (2) Some grids are organized as the influence region, while the rest compose of the free region. The algorithm achieves low running time by handling movements only from objects that fall in the influence region, while data changes in the free region are omitted with correctness guarantee. (3) The initialization module adopts an efficient method to obtain the initial result without having to process all the data points; after that the maintenance module updates the change of skyline and influence region dynamically when data changes. We analyze the space and time costs of the proposed method and conduct an extensive experiment, which indicates that our grid-based algorithm is efficient and significantly outperforms existing methods adopted for the application.
Increasing the Participation of People with Disabilities in Computing Fields
Authors: Sheryl E. Burgstahler, Richard E. Ladner
Venue: Computer (2007)

Efforts to increase the participation of people with disabilities in high-tech careers will ultimately benefit both society and the computing profession.
Portfolio performance sensitivity for various asset-pricing kernels
Authors: Mohamed A. Ayadi, Lawrence Kryzanowski
Venue: Computers and Operations Research (2008)

This paper examines the sensitivity of various measures of portfolio performance to the choice of the benchmark model using the asset-pricing kernel methodology. It derives the appropriate estimation frameworks that are suitable to perform evaluations of fixed-weight and dynamic portfolio strategies. Various asset-pricing kernel-based benchmark models are tested using a comprehensive sample of Canadian equity mutual funds over the period, 1989-1999. The performance statistics and inferences are sensitive to the choice of the kernel-based benchmark model and to the choice of liquidity as an alternative sorting variable for forming the passive benchmark portfolios. However, they are robust to the removal of ex post index mimickers and somewhat less robust to the presence of nonlinearities in the structure of the pricing kernel. Since conditioning has a more pronounced impact on absolute than on relative performance inferences, this supports the common industry practice of comparing the performance of funds against each other.
Robust speaker verification via fusion of speech and lip modalities
Authors: T. Wark
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06 (1999)

This paper investigates the use of lip information, in conjunction with speech information, for robust speaker verification in the presence of background noise. It has been previously shown in our own work, and in the work of others, that features extracted from a speaker's moving lips hold speaker dependencies which are complementary with speech features. We demonstrate that the fusion of lip and speech information allows for a highly robust speaker verification system which outperforms the performance of either sub-system. We present a new technique for determining the weighting to be applied to each modality so as to optimize the performance of the fused system. Given a correct weighting, lip information is shown to be highly effective for reducing the false acceptance and false rejection error rates in the presence of background noise.
2007 Special Issue: Improving weather radar estimates of rainfall using feed-forward neural networks
Authors: Reinhard Teschl, Walter L. Randeu, Franz Teschl
Venue: Neural Networks (2007)

In this paper an approach is described to improve weather radar estimates of rainfall based on a neural network technique. Other than rain gauges which measure the rain rate R directly on the ground, the weather radar measures the reflectivity Z aloft and the rain rate has to be determined over a Z-R relationship. Besides the fact that the rain rate has to be estimated from the reflectivity many other sources of possible errors are inherent to the radar system. In other words the radar measurements contain an amount of observation noise which makes it a demanding task to train the network properly. A feed-forward neural network with Z values as input vector was trained to predict the rain rate R on the ground. The results indicate that the model is able to generalize and the determined input-output relationship is also representative for other sites nearby with similar conditions.
Harissa: a flexible and efficient java environment mixing bytecode and compiled code
Authors: Gilles Muller, Bárbara Moura, Fabrice Bellard, Charles Consel
Venue: Proceedings of the 3rd conference on USENIX Conference on Object-Oriented Technologies (COOTS) - Volume 3 (1997)

The Java language provides a promising solution to the design of safe programs, with an application spectrum ranging from Web services to operating system components. The well-known tradeoff of Java's portability is the inefficiency of its basic execution model, which relies on the interpretation of an object-based virtual machine. Many solutions have been proposed to overcome this problem, such as just-in-time (JIT) and off-line bytecode compilers. However, most compilers trade efficiency for either portability or the ability to dynamically load bytecode. In this paper, we present an approach which reconciles portability and efficiency, and preserves the ability to dynamically load bytecode. We have designed and implemented an efficient environment for the execution of Java programs, named Harissa. Harissa permits the mixing of compiled and interpreted methods. Harissa's compiler translates Java bytecode to C, incorporating aggressive optimizations such as virtual-method call optimization based on the Class Hierarchy Analysis. To evaluate the performance of Harissa, we have conducted an extensive experimental study aimed at comparing the various existing alternatives to execute Java programs. The C code produced by Harissa's compiler is more efficient than all other alternative ways of executing Java programs (that were available to us): it is up to 140 times faster than the JDK interpreter, up to 13 times faster than the Softway Guava JIT, and 30% faster than the Toba bytecode to C compiler.
Solving traveling salesman problems by combining global and local search mechanisms
Authors: Huai-Kuang Tsai, Jinn-Moon Yang, Cheng-Yan Kao
Venue: Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02 (2002)

In this paper an evolutionary algorithm for the traveling salesman problem is proposed. The key idea is to enhance the ability of exploration and exploitation by incorporating global search with local search. A new local search, called the neighbor-join (NJ) operator, is proposed to improve the solution quality of the edge assembly crossover (EAX) considered as a global search mechanism in this paper. Our method is applied to 15 well-known traveling salesman problems with numbers of cities ranging from 101 to 3038 cities. The experimental results indicate that the neighbor-join operator is very competitive with related operators surveyed in this paper. Incorporating the NJ into the EAX significantly outperforms the method incorporating 2-opt into the EAX for some hard problems. For each test instance the average value of solution quality stays within 0.03% from the optimum. For the notorious hard problem att532, it is able to find the optimum solution 23 times in 30 independent runs.
A Visual Tracking Algorithm for Real Time People Detection
Authors: T. D'Orazio, M. Leo, P. Spagnolo, P. L. Mazzeo, N. Mosca, M. Nitti
Venue: Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services (2007)

In this paper we present a multi-people-tracking algorithm which is able to detect and track humans in complex situations with varying light conditions, high frame rate, and real time processing.We propose a stochastic approach for foreground people tracking based on the evaluation of the maximum a posteriori probability (MAP). The algorithm evaluates geometrical information on the blob overlapping and does not require the feature extraction to track the single object. Experimental tests have been carried out on soccer image sequence in which some players enter into the camera view and remain for some time.
Mapping multi-dimensional signals into hierarchical memory organizations
Authors: Hongwei Zhu, Ilie I. Luican, Florin Balasa
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

The storage requirements of the array-dominated and loop-organized algorithmic specifications running on embedded systems can be significant. Employing a data memory space much larger than needed has negative consequences on the energy consumption, latency, and chip area. Finding an optimized storage of the usually large arrays from these algorithmic specifications is an important step during memory allocation. This paper proposes an efficient algorithm for mapping multi-dimensional arrays to the data memory. Similarly to [13], it computes bounding windows for live elements in the index space of arrays, but this algorithm is several times faster. Moreover, since this algorithm works not only for entire arrays, but also parts of arrays -- like, for instance, array references or, more general, sets of array elements represented by lattices [11], this signal-to-memory mapping technique can be also applied in multi-layer memory hierarchies.
Using smoothed K-TSS language models in continuous speech recognition
Authors: A. Varona
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02 (1999)

A syntactic approach of the well-known N-grams models, the K-testable language in the strict sense (K-TSS), is used in this work to be integrated in a continuous speech recognition (CSR) system. The use of smoothed K-TSS regular grammars allowed to obtain a deterministic stochastic finite state automaton (SFSA) integrating K k-TSS models into a self-contained model. An efficient representation of the whole model in a simple array of adequate size is proposed. This structure can be easily handled at decoding time by a simple search function through the array. This formulation strongly reduced the number of parameters to be managed and thus the computing complexity of the model. An experimental evaluation of the proposed SFSA representation was carried out over an Spanish recognition task. These experiments showed important memory saving to allocate K-TSS language models, more important for higher values of K. They also showed that the decoding time did not meaningfully increased when K did. The lower word error rates for the Spanish task tested were achieved for K=4 and 5. As a consequence the ability of this syntactic approach of the N-grams to be well integrated in a CSR system, even for high values of K, has been established.
Combining Single-Version and Evolutionary Dependencies for Software-Change Prediction
Authors: Huzefa Kagdi, Jonathan I. Maletic
Venue: Proceedings of the 29th International Conference on Software Engineering Workshops (2007)

The paper advocates the need for the investigation and development of a software-change prediction methodology that combines the change sets estimated from software dependency analysis (via single-version analysis) and the actual change sets found in software version histories (via multiple-version analysis). Traditionally prescribed methodologies such as Impact Analysis (IA) are based on the former, whereas a more recent methodology, Mining Software Repository (MSR), is based on the latter. The research hypothesis is that combining these two methodologies will result in an overall improved support for software-change prediction.
Control Structure in Project-Based Asynchronous Collaborative Learning
Authors: Timothy J. Ellis, William Hafner
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

Although project-based, collaborative learning (PBCL) activities have been established as effective learning experiences, they have been shown to be difficult to implement, especially in an asynchronous, distributed environment. Students and faculty alike have shown resistance to team-based exercises, citing numerous management concerns such as equitably distributing the work, assessing the performance of the individuals comprising the team, and resolving conflicts within the team. One major issue has been how to establish control within the team. Control structure refers to the manner in which responsibility for executing the tasks associated with the role is assigned. Control structure within a (PBCL) assignment can vary on a continuum from an entirely democratic model to an autocratic model. The goal of this study was to examine the impact of the type of control structure on team functioning by comparing both performance in and attitude toward PBCL in democratically and autocratically controlled teams.
Practical Scheduling of Bag-of-Tasks Applications on Grids with Dynamic Resilience
Authors: Young Choon Lee, Albert Y. Zomaya
Venue: IEEE Transactions on Computers (2007)

Over the past decade, the grid has emerged as an attractive platform to tackle various large-scale problems, especially in science and engineering. One primary issue associated with the efficient and effective utilization of heterogeneous resources in a grid is scheduling. Grid scheduling involves a number of challenging issues, mainly due to the dynamic nature of the grid. There are only a handful of scheduling schemes for grid environments that realistically deal with this dynamic nature that have been proposed in the literature. In this paper, two novel scheduling algorithms, called the Shared-Input-data-based Listing (SIL) algorithm and the Multiple Queues with Duplication (MQD) algorithm for bag-of-tasks (BoT) applications in grid environments are proposed. The SIL algorithm targets scheduling data-intensive BoT (DBoT) applications, whereas the MQD algorithm deals with scheduling computationally intensive BoT (CBoT) applications. Their common and primary forte is that they make scheduling decisions without fully accurate performance prediction information. Another point to note is that both scheduling algorithms adopt task duplication as an attempt to reduce serious schedule increases. Our evaluation study employs a number of experiments with various simulation settings. The results show the practicability and competitiveness of our algorithms when compared to existing methods.
Area optimization of multi-cycle operators in high-level synthesis
Authors: M. C. Molina, R. Ruiz-Sautua, J. M. Mendías, R. Hermida
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

Conventional high-level synthesis algorithms usually employ multi-cycle operators to reduce the cycle length in order to improve the circuit performance. These operators need several cycles to execute one operation, but the entire functional unit is not used in any cycle. Additionally, the execution of operations over wider multi-cycle operators is unfeasible if their results must be available in a smaller number of cycles than the functional unit delay. This obliges to add new functional resources to the datapath even if multi-cycle operators are idle when the execution of the operation begins. In this paper a new design technique to overcome the restricted reusability of multi-cycle operators is presented. It reduces the area of these functional units allowing their internal reuse when executing one operation. It also expands the possibilities of common hardware sharing as it allows the partial use of multi-cycle operators to calculate narrower operations faster than the functional unit delay. This technique is applied as an optimization phase at the end of the high-level synthesis process, and can optimize the circuits synthesized by any high-level synthesis tool.
Scalable web caching of frequently updated objects using reliable multicast
Authors: Dan Li, David R. Cheriton
Venue: Proceedings of the 2nd conference on USENIX Symposium on Internet Technologies and Systems - Volume 2 (1999)

Frequently updated web objects reduce the benefit of caching, increase the problem of cache inconsistency, and aggravate the inefficiency of the conventional "repeated unicast" delivery model. In this paper, we investigate multicast invalidation and delivery of popular, frequently updated objects to web cache proxies. Our protocol, MMO, groups objects into volumes, each of which maps to one IP multicast group. We show that, by forming volumes of the appropriate size and/or object correlation, the benefit from reliable multicast outweighs the cost of delivering extraneous data as well as the overhead of multicast reliability. Moreover, trace-driven simulations show that the bandwidth saving over conventional approaches increases significantly as the audience size grows. We conclude that MMO provides efficient bandwidth utilization and service scalability, and makes strong web cache consistency for dynamic objects practical.
A Component-based Framework for Face Detection and Identification
Authors: Bernd Heisele, Thomas Serre, T. Poggio
Venue: International Journal of Computer Vision (2007)

We present a component-based framework for face detection and identification. The face detection and identification modules share the same hierarchical architecture. They both consist of two layers of classifiers, a layer with a set of component classifiers and a layer with a single combination classifier. The component classifiers independently detect/identify facial parts in the image. Their outputs are passed the combination classifier which performs the final detection/identification of the face.We describe an algorithm which automatically learns two separate sets of facial components for the detection and identification tasks. In experiments we compare the detection and identification systems to standard global approaches. The experimental results clearly show that our component-based approach is superior to global approaches.
A match moving technique for merging CG and human video sequences
Authors: H. Saito
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 03 (2001)

Merging virtual objects with human video sequences is an important technique for many applications such as special effects in movies and augmented reality. In the traditional method, the operator manually fits a 3D body model onto the human video sequence, and generates virtual objects at the current 3D body pose. However, the manual fitting is a time consuming task, and automatic registration is required. We propose a new method for merging virtual objects onto the human video sequence. First, we track the current 3D pose of the human figure by using spatio-temporal analysis and structural knowledge of the human body. Then we generate a CG object and merge it with the human figure in video. We demonstrate examples of merging virtual cloth with the video captured images.
Function-based ATPG for Path Delay Faults using the Launch-Off-Capture Scan Architecture
Authors: Edward Flanigan, Rajsekhar Adapa, Hailong Cui, Michael Laisne, Spyros Tragoudas, Tsvetomir Petrov
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

In this paper we present a novel function-based test generation technique for path delay faults (PDFs) under the launch-off-capture (LOC) scan architecture. The LOC architecture imposes the condition that the second test pattern must be a functional response of the initial scan test pattern. The proposed function-based LOC methodology incorporates traditional function-based ATPG techniques alongside an implicit framework to efficiently identify testable PDFs under the LOC scan architecture, and avoids the complex backtracking performed by structural techniques which may abort PDF classifications for path intensive designs. The effectiveness and scalability of the proposed method is demonstrated on the path intensive ISCAS 89 benchmarks.
A Page-based Hybrid (Software-Hardware) Dynamic Memory Allocator
Authors: Wentong Li, Saraju Mohanty, Krishna Kavi
Venue: IEEE Computer Architecture Letters (2006)

Modern programming languages often include complex mechanisms for dynamic memoryallocation and garbage collection. These features drive the need for more efficient implementation of memory management functions, both in terms of memory usage and execution performance. In this paper, we introduce a software and hardware co-design to improve the speed of the software allocator used in Free-BSD systems. The hardware complexity of our design is independent of the dynamic memory size, thus making the allocator suitable for any memory size. Our design improves the performance ofmemory management intensive benchmarks by as much as 43%. To our knowledge, this is the first-ever work of this kind, introducing "hybrid memory allocator".
A Bayesian Network Model for the Diagnosis of the Caring Procedure for Wheelchair Users with Spinal Injury
Authors: Maria Athanasiou, Jonathan Y. Clark
Venue: Proceedings of the Twentieth IEEE International Symposium on Computer-Based Medical Systems (2007)

This paper describes a probabilistic causal model for the caring procedure to be followed on wheelchair users with spinal injury. Uncertainty in the caring procedure arises mostly from incomplete information about patient findings (i.e. the signs and symptoms) due to loss of sensation and movement caused by the spinal cord injury. As a result, it may not be easy to assess the extent of a condition -- and, thus, make an accurate diagnosis. Bayesian Networks are used for diagnostic reasoning because they offer a way of conducting probabilistic inference about the conditions associated with the caring procedure in the face of uncertainty. The network structure and numerical parameters are based on data elicited from the qualified staff nurses and literature of the National Spinal Injury Centre, Stoke Mandeville Hospital, Aylesbury, UK. We also present the model and report the results of the diagnostic performance tests using the AgenaRisk Bayesian network package.
A status report on engineering education in Japan
Authors: H. Akiyama
Venue: Proceedings of the 26th Annual Frontiers in Education - Volume 01 (1996)

During the past five decades, Japan has spent considerable effort and resources to stimulate and accommodate explosive growth in undergraduate enrolment in Japanese universities, driven in large part by the increasing fraction of students who complete high school and enter universities. Recent sharp increases in the number of students who continue to graduate school reflect increasing concentration on graduate programs. This paper outlines features of academic studies at both the undergraduate and graduate levels at leading Japanese national universities. It highlights some emerging trends.