ppxscal/embedding_network huggingface dataset:
Multicomponent Compatibility and its Verification
Authors: Donald C. Craig, Wlodek M. Zuberek
Venue: Proceedings of the Seventh International Conference on Application of Concurrency to System Design (2007)

Software architecture has been introduced with promise of better re-use of software, greater flexibility, scalability and higher quality of software services [1] [10]. Software architecture uses components as the basic building blocks of software systems.
Recognition of Hand Raising Gestures for a Remote Learning Application
Authors: Bill Kapralos, Andrew Hogue, Hamed Sabri
Venue: Proceedings of the Eight International Workshop on Image Analysis for Multimedia Interactive Services (2007)

A central technical issue in developing synchronous distance learning technology is enabling the remote class and the instructor to interact with each other. Issues such as "how does a student capture the instructor's attention?", "how can the instructor select one student to converse with?", and "how can the instructor attend to the student once (s)he has been selected?" are complex problems that must be addressed if the class and instructor are to interact in an effective manner. This paper describes the use of Hidden Markov Models for the recognition of students signaling their intent to interact with the instructor using "traditional" classroom hand gestures such as raising and waving hand motions. Hand raising gestures are detected using motion cues over a sequence of omni-directional images using a set of pre-defined Hidden Markov Models.
A taxonomy of distributed query management techniques for wireless sensor networks: Research Articles
Authors: S. Chatterjea, P. Havinga
Venue: International Journal of Communication Systems (2007)

In the not too distant future, wireless sensor networks are envisioned to proliferate through the entire spectrum of the &lsquo;environmental monitoring&rsquo; market allowing users to monitor a multitude of environments. Thousands or even millions of sensor nodes may span vast geographical areas enabling various environmental parameters to be monitored with significantly higher spatial and temporal resolutions than what is achievable using existing monitoring technologies. In order to manage the large amount of data that will be generated by these numerous sensor nodes, novel querying methods are needed to extract the required information in an energy-efficient manner. This paper studies the techniques used to manage the queries in a distributed manner and classifies the current state-of-the-art in this field into four main categories: in-network processing, acquisitional query processing, cross-layer optimization and data-centric data&#x002F;query dissemination. This taxonomy not only illustrates how query management techniques have advanced over the recent past, but also allows researchers to identify the relevant features when designing sensor networks for different applications. Copyright &copy; 2006 John Wiley & Sons, Ltd.
Automatic Extraction of Lip Based on Wavelet Edge Detection
Authors: Ye-Peng Guan
Venue: Proceedings of the Eighth International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (2006)

The effective automatic lip extraction from images is fundamental in a variety of applications. Since the outer labial contour of the mouth is very poor color distinction when compared against its skin background, it makes extraction of lip a difficult problem. In order to improve the contrast between lip and the other face regions, discrete Hartley transform (DHT) is proposed. We perform wavelet multi-scale edge detection across the C3 component of the HDT, which takes both the color information and the geometric characteristic into account. Comparative study with some existing lip segmentation algorithms has indicated the superior performance of the developed algorithm. The proposed algorithm produces better segmentation without need to determine an optimum threshold for each face image. In contrast with the other methods investigated, the lip segmentation is determined completely automatically.
A Vision System for Monitoring Intermodal Freight Trains
Authors: Avinash Kumar, Narendra Ahuja, John M. Hart, U K. Visesh, P J. Narayanan, C V. Jawahar
Venue: Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision (2007)

We describe the design and implementation of a vision based Intermodal Train Monitoring System(ITMS) for extracting various features like length of gaps in an intermodal( IM) train which can later be used for higher level inferences. An intermodal train is a freight train consisting of two basic types of loads - containers and trailers. Our system first captures the video of an IM train, and applies image processing and machine learning techniques developed in this work to identify the various types of loads as containers and trailers. The whole process relies on a sequence of following tasks - robust background subtraction in each frame of the video, estimation of train velocity, creation of mosaic of the whole train from the video and classification of train loads into containers and trailers. Finally, the length of gaps between the loads of the IM train is estimated and is used to analyze the aerodynamic efficiency of the loading pattern of the train, which is a critical aspect of freight trains. This paper focusses on the machine vision aspect of the whole system.
Static specification mining using automata-based abstractions
Authors: Sharon Shoham, Eran Yahav, Stephen Fink, Marco Pistoia
Venue: Proceedings of the 2007 international symposium on Software testing and analysis (2007)

We present a novel approach to client-side mining of temporal API specifications based on static analysis. Specifically, we present an interprocedural analysis over a combined domain that abstracts both aliasing and event sequences for individual objects. The analysis uses a new family of automata-based abstractions to represent unbounded event sequences, designed to disambiguate distinct usage patterns and merge similar usage patterns. Additionally, our approach includes an algorithm that summarizes abstract traces based on automata clusters, and effectively rules out spurious behaviors. We show experimental results mining specifications from a number of Java clients and APIs. The results indicate that effective static analysis for client-side mining requires fairly precise treatment of aliasing and abstract event sequences. Based on the results, we conclude that static client-side specification mining shows promise as a complement or alternative to dynamic approaches.
PrivateBits: managing visual privacy in web browsers
Authors: Kirstie Hawkey, Kori M. Inkpen
Venue: Proceedings of Graphics Interface 2007 (2007)

Privacy can be an issue during collaboration around a personal display when previous browsing activities become visible within web browser features (e.g., AutoComplete). Users currently lack methods to present only appropriate traces of prior activity in these features. In this paper we explore a semi-automatic approach to privacy management that allows users to classify traces of browsing activity and filter them appropriately when their screen is visible by others. We developed PrivateBits, a prototype web browser that instantiates previously proposed general design guidelines for privacy management systems as well as those specific to web browser visual privacy. A preliminary evaluation found this approach to be flexible enough to meet participants' varying privacy concerns, privacy management strategies, and viewing contexts. However, the results also emphasized the need for additional security features to increase trust in the system and raised questions about how to best manage the tradeoff between ease of use and system concealment.
Rapid design of discrete orthonormal wavelet transforms using silicon IP components
Authors: S. Masud
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

A rapid design methodology for orthonormal wavelet transform cores has been developed. This methodology is based on a generic, scaleable architecture utilising time-interleaved coefficients for the wavelet transform filters. The architecture has been captured in VHDL and parameterised in terms of wavelet family, wavelet type, data word length and coefficient word length. The control circuit is embedded within the cores and allows them to be cascaded without any interface glue logic for any desired level of decomposition. Case studies for stand alone and cascaded silicon cores for single and multi-stage wavelet analysis respectively are reported. The design time to produce silicon layout of a wavelet based system has been reduced to typically less than a day. The cores are comparable in area and performance to hand-crafted designs. The designs are portable across a range of foundries and are also applicable to FPGA and PLD implementations.
Visualizing the Decision-Making Process in a Face-to-Face Meeting
Authors: Fouad Shoie Alallah, Mahtab Nezhadasl, Pourang Irani, Dean Jin
Venue: Proceedings of the 11th International Conference Information Visualization (2007)

The decision making process is usually one of the most critical elements of any face-to-face meeting. Participants in a group meeting follow certain procedures and guidelines for facilitating the decision making process. These include such rules as turn taking, not interrupting the consultation, and keeping suggestions or ideas clear and concise. The ultimate objective of such meetings is to arrive at decisions in a timely manner by having a diversity of opinions from as many participants as possible. We postulate that by visualizing the group dynamics during a face-to-face meeting, administrators might be able to get a better handle on the strengths and weaknesses of the group's consultation process. The end result would be to improve the overall quality of meetings. We present a visualization tool that captures and reveals the ongoing social dynamics during the decision-making process within a face-to-face and real-time meeting. Our system captures the required data trough a simple and easy-to-use interface and then visualizes the outcome of the meeting.
Study of Performance Evaluation for Data-Intensive Large-Scale Systems
Authors: Ying Liu, Huaiming Song, Limei Jiao
Venue: Proceedings of the First Asia International Conference on Modelling & Simulation (2007)

The different applications make performance evaluation for data-intensive large-scale systems become a very important work. General test methods pursue the peak value as the final result without paying enough attention on resource utilization. However, the recent studies have proved that the behavior of resources can reflect the latent problems. In this paper we present a new method called POPE (Process- Oriented Performance Evaluation), which analyses the systems combined workload characterization with resource utilization based on different node roles. It simplifies the complex system environment and its result contains much more information than before. This method has been applied to the real system with tens of nodes and it has found several key problems in design and equipments in time.
Multi-rate speech coding for wireless and Internet applications
Authors: J. E. Kleider
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 04 (1999)

Fixed-rate speech codecs are unable to provide synthesized speech with fixed delay when the channel capacity changes, and can not dedicate additional forward error correction bits for protection against noisy channels. We propose a multi-rate method for variable bandwidth applications, such as the Internet, and severely degraded wireless channels, such as mobile cellular. The technique uses a multi-rate version of the sinusoidal transform coder (MRSTC), operates at 9.6/4.8/2.4/1.2 kilobits/sec (kb/s), and is switchable "on-the-fly". The algorithm produces high quality speech, even when transitioning between rates. We compare two switching techniques, one method uses a "frame-deletion" (FD) technique, and a second method which utilizes "parameter-history" (PH) information. PH produces the best speech quality. FD is attractive because it requires no additional speech memory. Experimental results show greater than a 9 dB gain in receiver C/N/sub o/ operating range using the MRSTC over a fixed-rate system with STC operating at 9.6 kb/s.
Studying the influence of synchronous and asynchronous parallel GP on programs length evolution
Authors: G. Galeano, F. Femdndez, M. Tomassini, L. Vanneschi
Venue: Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02 (2002)

In this paper we present a study of parallel and distributed genetic programming models and their relationships with the bloat phenomenon. The experiments that we have performed have also allowed us to find an interesting link between the number of processes, subpopulations and the model we should use when applying parallelism to GP. We study the synchronous and asynchronous version of the island-model in GP domain.
A Job Schedule Model Based on Grid Environment
Authors: Homer Wu, Chong-Yen Lee, Wuu-Yee Chen, Tsang-Yean Lee
Venue: Proceedings of the First International Conference on Complex, Intelligent and Software Intensive Systems (2007)

Factors such as CPU utilization, throughput, turnaround time, waiting time, and response time can influence system performance. Different operating systems use different scheduling algorithms to achieve their goals. System performance of grid computing is calculated from resources usages. Job scheduling is more important when jobs are not uniformly distributed in all grid nodes. In order to achieve performance optimization, we propose a Maximum Processor Utilization and Throughput (MPUT) scheduling algorithm which maximizes CPU utilization and throughput at the same time and minimizes turnaround time as well. The algorithm is used in all execute grid nodes to schedule their jobs and get good performance.
Towards a perceptually optimal spectral amplitude estimator for audio signal enhancement
Authors: P. J. Wolfe
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

We present a statistical model-based approach to signal enhancement in the case of additive broadband noise. Because broadband noise is localised in neither time nor frequency, its removal is one of the most pervasive and difficult signal enhancement tasks. In order to improve perceived signal quality, we take advantage of human perception and define a best estimate of the original signal in terms of a cost function incorporating perceptual optimality criteria. We derive the resultant signal estimator and implement it in a short-time spectral attenuation framework.
Exploiting conjugate symmetry in power minimization based pre-processing for GPS: reduced complexity and smoothness
Authors: W. L. Myrick
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 05 (2000)

Space-time power minimization pre-processing can exhibit a significant improvement in GPS receiver performance by exploiting spatial and temporal processing techniques. This type of preprocessing however, will require significant computations due to the large dimensionality of the complex valued space-time correlation matrix and will cause some distortion of the PN codes due to temporal processing. To reduce the computational complexity and distortion effects simultaneously, a conjugate symmetry space-time pre-processor has been proposed. It is demonstrated that this pre-processor enhances smoothness across angle and frequency and facilitates the use of real valued space-time correlation matrices in a reduced dimension utilizing the multi-stage nested Wiener filter (MSNWF).
Mechanisms of Action Generation and Recognition in the Human Brain
Authors: Toshio Inui
Venue: Proceedings of the Second International Conference on Informatics Research for Development of Knowledge Society Infrastructure (2007)

This article reported three fMRI experiments concerning 1) the difference between natural movement with tactual manipulations and pantomime, 2) the process of state prediction in motor control, and 3) prediction learning of phonological sequence, in order to consider the brain mechanisms for construction of the egocentric model, prediction of an object's movements and actions, and mental simulation, those of which were proposed as three prerequisites of human mind by Inui [17]. Furthermore, it overviewed the global structure of brain network involved in realizing the basic functions of human mind.
Energy minimization with soft real-time and DVS for uniprocessor and multiprocessor embedded systems
Authors: Meikang Qiu, Chun Xue, Zili Shao, Edwin H.-M. Sha
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

Energy-saving is extremely important in real-time embedded systems. Dynamic Voltage Scaling (DVS) is one of the prime techniques used to achieve energy-saving. Due to the uncertainties in execution times of some tasks of systems, this paper models each varied execution time as a random variable. By using probabilistic approach, we propose two optimal algorithms, one for uniprocessor and one for multiprocessor to explore soft real-time embedded systems and avoid over-designing them. Our goal is to minimize the expected total energy consumption while satisfying the timing constraint with a guaranteed confidence probability. The solutions can be applied to both hard and soft real-time systems. The experimental results show that our approach achieves significant energy-saving than previous work.
Constructing and evaluating sensor-based statistical models of human interruptibility
Authors: Scott E. Hudson
Venue:  (2006)

While people can typically make a rapid assessment of another person's interruptibility, current systems generally have no way to consider whether an interruption is appropriate. Systems therefore tend to interrupt at inappropriate times or unduly demand attention. Sensor-based statistical models of human interruptibility are one approach to addressing this problem. In a series of studies, we examine the feasibility and robustness of sensor-based statistical models of human interruptibility, creating models that perform better than human observers. We then present a tool to enable non-expert development of applications that use sensor-based statistical models of human situations. Our first study collects audio and video recordings in the normal work environments of several office workers. We measure their interruptibility by collecting interruptibility self-reports via experience sampling. We then use a Wizard of Oz method to examine the recordings and simulate many potential sensors. Building statistical models from these simulated sensors, we are able to evaluate potential sensors without actually building them. In our second study, human observers view the recordings and estimate the interruptibility of the office workers. Statistical models based on our simulated sensors perform better than these human observers. Our third study examines the robustness of this result by implementing and deploying real sensors with a more diverse set of office workers. While different sensors are more predictive for different types of office workers, even a general model performs better than the human observers. Because these first three studies are dominated by social engagement, our fourth study explicitly examines task engagement. We show that low-level programming environment events can be used to model when a programmer will choose to defer an interruption. We then develop Subtle, a tool to enable further research into how human computer interaction can best benefit from sensor-based statistical models of human situations. With an extensible sensing library, fully-automated iterative feature generation, and support for model deployment, Subtle enables non-expert development of applications that use sensor-based statistical models of human situations. Subtle allows human computer interaction researchers to focus on compelling applications and datasets, rather than the difficulties of collecting appropriate sensor data and learning statistical models. Finally, we present a summary of contributions and plans for future work.
Middleboxes no longer considered harmful
Authors: Michael Walfish, Jeremy Stribling, Maxwell Krohn, Hari Balakrishnan, Robert Morris, Scott Shenker
Venue: Proceedings of the 6th conference on Symposium on Opearting Systems Design & Implementation - Volume 6 (2004)

Intermediate network elements, such as network address translators (NATs), firewalls, and transparent caches are now commonplace. The usual reaction in the network architecture community to these so-called middleboxes is a combination of scorn (because they violate important architectural principles) and dismay (because these violations make the Internet less flexible). While we acknowledge these concerns, we also recognize that middleboxes have become an Internet fact of life for important reasons. To retain their functions while eliminating their dangerous side-effects, we propose an extension to the Internet architecture, called the Delegation-Oriented Architecture (DOA), that not only allows, but also facilitates, the deployment of middleboxes. DOA involves two relatively modest changes to the current architecture: (a) a set of references that are carried in packets and serve as persistent host identifiers and (b) a way to resolve these references to delegates chosen by the referenced host.
Massively Multiplayer Online Game Supported Foreign Language Listening Ability Training
Authors: Michu M. Hu, Ben Chang
Venue: Proceedings of the The First IEEE International Workshop on Digital Game and Intelligent Toy Enhanced Learning (2007)

Digital games are engaging and capturing the attention of many people around the world. Massively Multiplayer Online Games (MMOGs) are quickly gaining popularity. Although most of the MMOGs on the market are designed for entertainment, more and more researchers are exploring the possibilities to apply MMOG technology in learning. These researchers based on learning theories, such as experiential learning, constructivist learning, collaborative learning, flow theory, and so on for the digital game design. A well-designed MMOG learning environment can stimulate students' learning attitudes and increase students' interest and engagement. In this paper, the authors discuss that how to use MMOG technology to facilitate learners to enhance their foreign language listening ability. The system architecture is presented to demonstrate the idea of using the MMOG technology to enhance the learners' listening capability of foreign language learning.
A Brief Review of Digital Games and Learning
Authors: Hui-Chun Hsiao
Venue: Proceedings of the The First IEEE International Workshop on Digital Game and Intelligent Toy Enhanced Learning (2007)

Digital games have caught the attention of scholars across a variety of disciplines. Today, scholars from fields as diverse as media design, literature, computer science, education, and theatre studies have together contributed to the understanding of this emergent medium and its phenomenon as a learning tool. The unsatisfying experience of directly adopting game formats into educational contexts has motivated researchers to study successful (commercial) digital games, in particular to examine the play activities of digital games and the principles underlying the design of digital games in order to develop concepts and strategies for rich virtual learning contexts. In this review, I provide a brief account of academic arguments regarding digital games and learning.