ppxscal/embedding_network huggingface dataset:
High damping electrostatic system for vibration energy scavenging
Authors: G. Despesse, J. J. Chaillout, T. Jager, J. M. Léger, A. Vassilev, S. Basrour, B. Charlot
Venue: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies (2005)

Advances in low power electronics and microsystems design open up the possibility to power small wireless sensor nodes thanks to energy scavenging techniques. Among the potential energy sources, we have focused on mechanical surrounding vibrations. To convert vibrations into electrical power we have chosen mechanical structures based on electrostatic transduction. Thanks to measurements and in agreement with recent studies [1], we have observed that most of surrounding mechanical vibrations occurs at frequencies below 100 Hz. We report here global simulations and designs of mechanical structures able to recover power over a large spectrum below 100 Hz. Contrary to existing structures tuned on a particular frequency [2], we have investigated conversion structures with a high electrical damping. Mathematica analytical models have been performed to determine the mechanical and electrical parameters that maximize the scavenged power for a wide number of applications. Two prototypes of mechanical structures have been designed.
A Thermodynamics Approach to Graph Similarity
Authors: Antonio Robles-Kelly
Venue: Proceedings of the Digital Image Computing on Techniques and Applications (2005)

In this paper, we describe the use of concepts from the areas of spectral-graph theory, kernel methods and differential geometry for the purposes of recovering a measure of similarity between pairs of graphical structures. To do this, we commence by relating each of the graphs under study to a Riemannian manifold through the use of the graph Laplacian and the heat operator. We do this by making use of the heat kernel and the set of initial conditions for the space of functions associated to the Laplace-Beltrami operator. With these ingredients, we make use of the first law of thermodynamics to recover the thermal energy associated to the conduction of heat through the graph. Thus, the problem of recovering a measure of similarity between pairs of graphs becomes that of computing the difference in their thermal energies. We illustrate the utility of the similarity metric recovered in this way for purposes of content-based image database indexing and retrieval.
ADAPT: Multi-Channel Adaptation Framework for Single-Authored Services
Authors: Bernd Mrohs, Stephan Steglich, Ilja Radusch
Venue: Proceedings of the Seventh IEEE International Symposium on Multimedia (2005)

Thanks to the proliferation of multimedia devices, people can use multiple channels to access services nowadays. Service developers have to face the challenge of developing services for a huge amount of devices with diverse capabilities. Adapting multimedia services manually for several devices can not be a preferred solution, since this would make the service development process more expensive and time consuming. This paper presents a way to avoid reauthoring of service content through automatic service adaptation. It presents ADAPT, an architecture for multi-channel service delivery. ADAPT implements a service adaptation function that automatically transforms the markup language for generic user interaction (GUIML) to device specific user interface formats, taking heterogeneous device and network capabilities as well as user preferences into account. Thus, service users can employ multiple devices to access multimedia services, while developers don't have to take care about specific target devices for their services.
Experimental Evaluation of Iris Recognition
Authors: Xiaomei Liu, Kevin W. Bowyer, Patrick J. Flynn
Venue: Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Workshops - Volume 03 (2005)

Iris is an important biometric method with high reported accuracy. However, current iris recognition systems require substantial user cooperation in the image acquisition. Relatively little is known about how iris recognition might perform with less stringent control of image quality. We have re-implemented a Daugman-like iris matchingmethod, and evaluated its performance on an image dataset of over 12,000 images from over 300 persons, with iris images of different qualities. We find an overall rank-one recognition rate using of 89.64%. Poor quality images account for most of the instances of incorrect recognition. Inaccurate segmentation is also a key problem. These results show that greater flexibility in use of iris recognition will require further work on handling images of non-ideal quality. We also explore the use of multiple images for representing a person.
Some experiments in directory organization: a simulation study
Authors: Allen Reiter
Venue: ACM SIGSIM Simulation Digest (1976)

Using a simulation model, experiments were conducted on various directory organization schemes and their performance implications. In particular we tested the effects of a multiprogrammed environment on system throughput for retrieval operations. Analysis of the results shows that different factors are relevant to performance for the various systems, and that under some circumstances ISAM and nasn-coding may lose the advantages they possess over B-trees in a stand-alone environment when multiprogramming is used. Some results of sharing data among simultaneous users are also presented.
Adaptive Optical Flow for Person Tracking
Authors: Simon Denman, Vinod Chandran, Sridha Sridharan
Venue: Proceedings of the Digital Image Computing on Techniques and Applications (2005)

Person tracking systems are dependent on being able to locate a person accurately across a series of frames. Optical flow can be used to segment a moving object from a scene, provided the expected velocity of the moving object is known; but successful detection also relies on being able segment the background. A problem with existing optical flow techniques is that they don't discriminate the foreground from the background, and so often detect motion (and thus the object) in the background. To overcome this problem, we propose a new optical flow technique, that is based upon an adaptive background segmentation technique, which only determines optical flow in regions of motion. This technique has been developed with a view to being used in surveillance systems, and our testing shows that for this application it is more effective than other standard optical flow techniques.
Improving Soft Real-Time Performance through Better Slack Reclaiming
Authors: Caixue Lin, Scott A. Brandt
Venue: Proceedings of the 26th IEEE International Real-Time Systems Symposium (2005)

Modern operating systems frequently support applications with a variety of timing constraints including hard real-time, soft real-time, and best-effort. To guarantee performance, critical applications typically over-reserve resources based on worst-case resource usage estimates, while others may reserve based on average-case or other estimates. When resources are fully subscribed, the performance of soft- and non-real-time applications depends upon the effective distribution of dynamic slack — reserved, but unused resources— from other tasks. Motivated by several representative examples, we derive four general principles for the effective management of slack. We have implemented these principles in four progressively better slack schedulers that demonstrate their effectiveness. BACKSLASH, which employs all four principles, misses fewer soft realtime deadlines than all of the other slack schedulers we examined.
E-Mail Authentication Is Here, but Has It Arrived Yet?
Authors: George Lawton
Venue: Computer (2005)

To counter the explosion of spam and phishing attacks that cost victims time and money, companies are pursuing e-mail authentication, which is designed to determine whether mail has come from a reliable source and is thus legitimate.
A face authentication system using the trace transform
Authors: S. Srisuk, M. Petrou, W. Kurutach, A. Kadyrov
Venue: Pattern Analysis Applications (2005)

In this paper we introduce novel face representations, the masked Trace transform (MTT), the shape Trace transform (STT) and the weighted Trace transform (WTT), for recognising faces in a face authentication system. We first transform the image space to the Trace transform space to produce the MTT. We then identify the points of the MTT which take similar values irrespective of intraclass variations and this way we create the WTT. Next we threshold the MTT and extract the edges of the thresholded regions to produce some shapes that characterise the person. This is the STT. Therefore, each person in the database is represented by their WTT and STT. We estimate the dissimilarity between two shapes by a new measure we propose, the Hausdorff context. Reinforcement learning is used to search for the optimal parameter values of the algorithm. Shape and features from the MTT are then integrated at the decision level, by a classifier combination algorithm. Our system is evaluated with experiments on the XM2VTS database using 2360 face images. We achieve a Total Error Rate (TER) of 0.18%, which is the lowest error among all other reported methods which used the same data and the same evaluation protocol in a recently published study.
An Intelligent Tropical Cyclone Eye Fix System Using Motion Field Analysis
Authors: Ka Yan Wong, Chi Lap Yip
Venue: Proceedings of the 17th IEEE International Conference on Tools with Artificial Intelligence (2005)

Tropical cyclones (TCs) are weather systems with vast destructive power. Accurate location of their circulation centers, or "eyes", is thus important to forecasters. However, the eye fix process is often done manually in practice. While multiple factors are considered in the process, with subjective elements in these methods, forecasters could disagree. This paper describes a TC eye fix system that uses a novel motion field structure analysis method. It can handle TCs without well-defined structure that are partially out of the image. The systems also adapts user inputs and past results to improve its accuracy. Implemented on a commodity desktop computer, the system can process about 5 images per minute, giving an average error of about 0.16 degrees in latitude/longitude on Mercator projected map for TCs that are completely inside the radar image. This is well within the relative error of about 0.3-0.4 degrees given by different TC warning centers. This TC eye fix system is useful in giving an objective TC center location in contrast to traditional manual analysis.
Run-Time Power Consumption Modeling for Embedded Multimedia Systems
Authors: Yu Hu, Qing Li, C.-C. Jay Kuo
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

The run-time power consumption model for multimedia application routines in an embedded system is developed in this work. A wide range of benchmarks for these routines such as image, video and speech coding algorithms are examined extensively to characterize their power consumption behavior. Then, based on this study, a run-time power consumption model is proposed to achieve fast and accurate power usage estimation, where the model depends on the specific application routine involved as well as the applied voltage and the operating frequency. It is demonstrated that the developed model is able to predict the cumulative energy consumption of validating sequences with little error. Finally, this model is validated with a commercial VLIW processor by checking its actual power consumption behavior.
Distance-Based Detection and Prediction of Outliers
Authors: Fabrizio Angiulli, Stefano Basta, Clara Pizzuti
Venue: IEEE Transactions on Knowledge and Data Engineering (2006)

A distance-based outlier detection method that finds the top outliers in an unlabeled data set and provides a subset of it, called outlier detection solving set, that can be used to predict the outlierness of new unseen objects, is proposed. The solving set includes a sufficient number of points that permits the detection of the top outliers by considering only a subset of all the pairwise distances from the data set. The properties of the solving set are investigated, and algorithms for computing it, with subquadratic time requirements, are proposed. Experiments on synthetic and real data sets to evaluate the effectiveness of the approach are presented. A scaling analysis of the solving set size is performed, and the false positive rate, that is, the fraction of new objects misclassified as outliers using the solving set instead of the overall data set, is shown to be negligible. Finally, to investigate the accuracy in separating outliers from inliers, ROC analysis of the method is accomplished. Results obtained show that using the solving set instead of the data set guarantees a comparable quality of the prediction, but at a lower computational cost.
Fast leave-one-out evaluation for dynamic gene selection
Authors: Z. Ying, K. C. Keong
Venue: Soft Computing - A Fusion of Foundations, Methodologies and Applications (2006)

Gene selection procedure is a necessary step to increase the accuracy of machine learning algorithms that help in disease diagnosis based on gene expression data. This is commonly known as a feature subset selection problem in machine learning domain. A fast leave-one-out (LOO) evaluation formula for least-squares support vector machines (LS-SVMs) is introduced here that can guide our backward feature selection process. Based on that, we propose a fast LOO guided feature selection (LGFS) algorithm. The gene selection step size is dynamically adjusted according to the LOO accuracy estimation. For our experiments, the application of LGFS to the gene selection process improves the classifier accuracy and reduces the number of features required as well. The least number of genes that can maximize the disease classification accuracy is automatically determined by our algorithm.
Understanding Stakeholder Values as a Means of Dealing with Stakeholder Conflicts
Authors: Bernard Wong
Venue: Software Quality Control (2005)

This paper reports on a quantitative study, which examines the link between software characteristics, sought after consequences and personal values in software evaluation, whilst investigating the stakeholders' understanding of software quality. The study involved a survey of 403 subjects, which were then analyzed quantitatively with bi-variate analysis, and multivariate analysis of variance. The research argues that trade-offs in software development projects are often experienced in software development because of conflicts. These conflicts involve schedules, priorities and are very much caused by the different stakeholder views of quality, different desired consequences sought by the different stakeholders and more importantly influenced by the desired values of the different stakeholders. The research finds that different classes of stakeholders have different views of software quality. The research also finds that certain values sought by the stakeholder influences their sought after consequences required in the developed software product. However, it is not just any values that affect the stakeholder, but rather, it is the values affected by the evaluated software, which influences the selection of characteristics and sought after consequences. Values, which are important, but are not affected by software use, do not influence the stakeholder. As such, these results help us gain a better understanding of what types of values influence the choice of characteristics in software evaluation, and the desired consequences in a software product, and why conflicts exist during software development life-cycle. The results provide a number of important insights and suggest several conclusions. The study showed (1) that stakeholders differ in their priorities in the sought after consequences of the software being developed; (2) that the desired values, which are perceived to be affected by the software differ between stakeholders and influence the choice of characteristic and consequence; (3) that the consequence, value relationship as described in the Software Evaluation Framework can be valuable to understand the conflicts and trade-offs fond in software development.
Guest Editors' Introduction: Energy-Efficient Design
Authors: Kunio Uchiyama, Pradip Bose
Venue: IEEE Micro (2005)

Energy efficiency has been a key design constraint for microprocessor development teams since the late 1990s. The fundamental technological issues that have led to this point are quite well understood at this time by industry and academia. Although active (or dynamic) and passive (or standby) components of the net power equation are of concern, in recent years the latter (leakage) aspect of chip power has been escalating at a much faster rate than active power. IEEE Micro, in putting together a special issue on this important theme, decided to focus on two recently held (and relatively new) conferences: Cool Chips VIII, held April 2005 in Yokohama, Japan, and the fourth Annual Austin Conference on Energy Efficient Design (ACEED), held in March 2005 in Austin, Texas. The papers in the issue, from those conferences, focus on energy efficient design, and the Cell processor.
Exploring Issues of User Model Transparency and Proactive Behaviour in an Office Environment Control System
Authors: Keith Cheverst, Hee Eon Byun, Dan Fitton, Corina Sas, Chris Kray, Nicolas Villar
Venue: User Modeling and User-Adapted Interaction (2005)

It is important that systems that exhibit proactive behaviour do so in a way that does not surprise or frustrate the user. Consequently, it is desirable for such systems to be both personalised and designed in such a way as to enable the user to scrutinise her user model (part of which should hold the rules describing the behaviour of the system). This article describes on-going work to investigate the design of a prototype system that can learn a given user's behaviour in an office environment in order to use the inferred rules to populate a user model and support appropriate proactive behaviour (e.g. turning on the user's fan under appropriate conditions). We explore the tension between user control and proactive services and consider issues related to the design of appropriate transparency with a view to supporting user comprehensibility of system behaviour. To this end, our system enables the user to scrutinise and possibly over-ride the `IF-THEN' rules held in her user model. The system infers these rules from the context history (effectively a data set generated using a variety of sensors) associated with the user by using a fuzzy-decision-tree-based algorithm that can provide a confidence level for each rule in the user model. The evolution of the system has been guided by feedback from a number of real-life users in a university department. A questionnaire study has yielded supplementary results concerning the extent to which the approach taken meets users' expectations and requirements.
Network Anomaly Detection Using Time Series Analysis
Authors: Qingtao Wu, Zhiqing Shao
Venue: Proceedings of the Joint International Conference on Autonomic and Autonomous Systems and International Conference on Networking and Services (2005)

This paper presents a method of detecting network anomalies by analyzing the abrupt change of time series data obtained from Management Information Base (MIB) variables. The method applies the Auto- Regressive (AR) process to model the abrupt change of time series data, and performs sequential hypothesis test to detect the anomalies. With time correlation and location correlation, the method determines not only the presence of anomalous activity, but also its occurring time and location. The experimental results show that the proposed method performs well in detecting the traffic-related Anomalies
Open Loop Control and Business Planning- A Preliminary
Authors: Cyrus F. Nourani, R. M. Moudi
Venue: Proceedings of the Joint International Conference on Autonomic and Autonomous Systems and International Conference on Networking and Services (2005)

New optimality principles are put forth based on competitive model business planning. A Generalized MinMax local optimum dynamic programming algorithm is presented and applied to business model computing where predictive techniques can determine local optima. Based on a systems model an enterprise is not viewed as the sum of its component elements, but the product of their interactions. The paper starts with introducing a systems approach to business modeling. A competitive business modeling technique, based on the author's planning techniques is applied. Systemic decisions are based on common organizational goals, and as such business planning and resource assignments should strive to satisfy higher organizational goals. It is critical to understand how different decisions affect and influence one another. Here, a business planning example is presented where systems thinking technique, using Causal Loops, are applied to complex management decisions. A preliminary optimal game modeling technique is presented in brief. Conducting gap and risk analysis can assist with this process.
Multi-paradigm Java-Prolog integration in tuProlog
Authors: Enrico Denti, Andrea Omicini, Alessandro Ricci
Venue: Science of Computer Programming (2005)

tuProlog is a Java-based Prolog engine explicitly designed to be minimal, dynamically configurable, and support full and clean Prolog/Java integration. In this paper, we discuss the tuProlog approach to Prolog/Java multi-paradigm integration. After tuProlog motivations and requirements, we present some examples of bidirectional Prolog/Java integration and discuss the model and architecture of the tuProlog system. Then, we focus on the specific issue of the access to Java resources from tuProlog, discuss the essentials of its implementation, and compare it extensively with many other relevant related approaches and systems.