ppxscal/embedding_network huggingface dataset:
Self-Organizing Spatial Regions for Sensor Network Infrastructures
Authors: Nicola Bicocchi, Marco Mamei, Franco Zambonelli
Venue: Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02 (2007)

This paper focuses on sensor networks as shared environmental infrastructures, and presents an approach to enable a sensor network to self-partition itself, at pre-defined energy costs, into spatial regions of nodes characterized by similar patterns of sensed data. Such regions can then be used to aggregate data on a per-region basis and to enable multiple mobile users to extract information at limited and pre-defined costs.
Scalable techniques and tools for reliability analysis of large circuits
Authors: Debayan Bhaduri, Sandeep Shukla, Paul Graham, Maya Gokhale
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

With the rapid advancement of CMOS and non-CMOS nanotechnologies, circuit reliability is becoming an important design parameter. In recent years, a number of reliability evaluation methodologies based on probabilistic model checking, probabilistic transition matrices, etc., have been proposed. Scalability has been a concern in the wide applicability of these methodologies to the reliability analysis of large circuits. In this paper, we discuss the similarities between these reliability evaluation methodologies and focus mainly on the scalability issue. In particular, we develop a scalable technique for the model checking-based methodology, and show how this technique can be applied to the other methodologies. We also develop a tool called SETRA that can be used to integrate the scalable forms of these methodologies in the conventional circuit design flow.
Butterfly and benes-based on-chip communication networks for multiprocessor turbo decoding
Authors: Hazem Moussa, Olivier Muller, Amer Baghdadi, Michel Jézéquel
Venue: Proceedings of the conference on Design, automation and test in Europe (2007)

Several research activities have recently emerged aiming to propose multiprocessor implementations in order to achieve flexible and high throughput parallel iterative decoding. Besides application algorithm optimizations and application-specific instruction-set processor design, the on-chip communication network constitutes a major issue in this application domain. In this paper, we propose to use multistage interconnection networks as on-chip communication networks for parallel turbo decoding. Adapted Benes and Butterfly networks are proposed with detailed hardware implementation of network interfaces, routers, and topologies. In addition, appropriate packet format and routing for interleaved/deinterleaved extrinsic information exchanges are proposed. The flexibility of these on-chip communication networks enables their use for all turbo code standards and constitutes a promising feature for their reuse for any similar interleaved/deinterleaved iterative communication profile.
A constrained optimal data association for multiple target tracking
Authors: Hong Jeong
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

One of the major problems in multiple target tracking is to obtain an accurate association between targets and noisy measurements. We introduce a new scheme, called constrained optimal data association (CODA), that finds the optimal data association by a MAP estimation method and uses a new energy function. In this scheme, the natural constraints between targets and measurements are defined so that they may contain missed detection and false alarm errors. Most current algorithms involve many heuristic adjustments of the parameters. Instead, this paper suggests an adaptive mechanism for such parameter updating. In this manner, the system automatically adapts to the clutter environment as it continuously changes in time and space, resulting in better association. Experimental results, using PDA, NNF, and CODA, show that the new approach reduces position errors in crossing trajectories by 13.9% on average compared to NNF.
Application Development Framework for the Rapid Integration of High Performance Image Processing Algorithms
Authors: Scott Spetka, George Ramseyer, Richard W. Linderman
Venue: Proceedings of the 35th Applied Imagery and Pattern Recognition Workshop (2006)

The Application Development Framework (ADF) provided developers with a unique environment that supported the rapid integration and testing of image processing algorithms on high performance computers (HPCs). Using object-oriented middleware for the base of the system, along with Web technologies, allowed considerable flexibility in extending the system to a broad range of system development tools and components. The pub/sub system at the core of the ADF was the foundation that provided rapid system integration.
Modeling and prediction with a class of time delay dynamic neural networks
Authors: Yasar Becerikli, Yusuf Oysal
Venue: Applied Soft Computing (2007)

In this paper, we propose a time delay dynamic neural network (TDDNN) to track and predict a chaotic time series systems. The application of artificial neural networks to dynamical systems has been constrained by the non-dynamical nature of popular network architectures. Many of the drawbacks caused by the algebraic structures can be overcome with TDDNNs. TDDNNs have time delay elements in their states. This approach provides the natural properties of physical systems. The minimization of a quadratic performance index is considered for trajectory tracking applications. Gradient computations are presented based on adjoint sensitivity analysis. The computational complexity is significantly less than direct method, but it requires a backward integration capability. We used Levenberg-Marquardt parameter updating method.
Scenario building for E-Government in 2020: Consolidating the results from regional workshops
Authors: Marijn Janssen, Patrick van der Duin, Rene W. Wagenaar, Melanie Bicking, Maria A. Wimmer, Sharon Dawes, Rimantas Petrauskas
Venue: Proceedings of the 40th Annual Hawaii International Conference on System Sciences (2007)

E-government research is currently at a stage of consolidation and new orientation. Smaller steps of government modernization have in part been successfully implemented; larger ones still lie ahead of us. Within an EC funded project, a roadmap for egovernment is being defined. Thereby, scenario building about the future is being used to grasp pictures of the future. From these future scenarios, research actions shall be derived. In this paper we present the results of the scenario building workshops in four regions for e-government in the year 2020. In total 15 scenarios were developed shaping aspects of different dimensions of alternative futures. A wide range of topics were addressed, varying from interoperability, division of power, corruption, cyber war to changing democratic systems, religious activities, participations and the role of individualisms in society. Next steps are to assess the scenario results in respect to the current EC agenda and to derive from there actions of research in order to ensure that desired futures will come true and that unwanted futures are being avoided.
Integration of basic electromagnetism and engineering technology
Authors: S. Bentz
Venue: Proceedings of the Frontiers in Education Conference, on 1995. Proceedings., 1995 - Volume 02 (1995)

The theory of electromagnetism is taught as a part of most contemporary electrical engineering curricula. Usually a basic course is intended to cover all the fundamental electromagnetic theory which is needed in later engineering courses. However it is often found that students fail to understand and retain much of the course material, which in turn makes their subsequent studies more difficult. We describe a freshman course in electromagnetism which alleviates these problems. Our hypothesis is that the course material is difficult to grasp because of its abstract nature. Consequently the purely theoretical course contents have been reduced to a core of fundamental principles. These are combined with the study of magnetic properties of materials closely related to manufacturer's data sheets. To enhance the understanding of these fundamentals, practical topics from engineering technology are included. Components or systems that combine magnetic, electrical and mechanical aspects are preferred. Also, a series of hands-on lab projects give the students an opportunity to learn by doing. The topics that are covered by the course are outlined. By integrating the teaching of basic physical laws and their application in technology students get a more comprehensive understanding of electromagnetism, and they are able to apply the physical principles to problems they encounter later in their careers. 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
An efficient square-root algorithm for BLAST
Authors: B. Hassibi
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02 (2000)

Bell Labs Layered Space-Time (BLAST) is a scheme for transmitting information over a rich-scattering wireless environment using multiple receive and transmit antennas. The main computational bottleneck in the BLAST algorithm is a "nulling and cancellation" step, where the optimal ordering for the sequential estimation and detection of the received signals is determined. To reduce the computational cost of BLAST, we develop an efficient square-root algorithm for the nulling and cancellation step. The main features of the algorithm include efficiency: the computational cost is reduced by 0.7 M, where M is the number of transmit antennas, and numerical stability: the algorithm is division-free and uses only orthogonal transformations. In a 14 antenna system designed for transmission of 1 Mbit/s over a 30 kHz channel, the nulling and cancellation computation is reduced from 190 MFlops/s to 19 MFlops/s, with the overall computations being reduced from 220 MFlops/s to 49 MFlops/s. The numerical stability of the algorithm also make it attractive for implementation in fixed-point (rather than floating-point) architectures.
Optimal binarization of images by neural networks for morphological analysis of ductile cast iron
Authors: A. De Santis, O. Di Bartolomeo, D. Iacoviello, F. Iacoviello
Venue: Pattern Analysis Applications (2007)

This work aims to characterize different objects on a scene by means of some of their morphological properties. The leading application consists in the analysis of ductile cast iron specimen pictures, in order to provide a quantitative evaluation of the graphite nodules shape; to this aim the material specimen pictures are binarized. Such a binarization process can be formulated as an optimal segmentation problem. The search for the optimal solution is solved efficiently by training a neural network on a suitable set of binary templates. A robust procedure is obtained, amenable for parallel or hardware implementation, so that real-time applications can be effectively dealt with. The method was developed as the core of an expert system aimed at the unsupervised analysis of ductile cast iron mechanical properties that are influenced by the microstructure and the peculiar morphology of graphite elements.
A partial studio model for teaching undergraduate heat transfer
Authors: R. J. Ribando
Venue: Proceedings of the 26th Annual Frontiers in Education - Volume 01 (1996)

A new partial studio model for teaching undergraduate heat and mass transfer is described. Students are exposed to modern numerical algorithms and visualization techniques while learning the fundamental principles of heat transfer in an interactive PC-based classroom setting. As part of this project seven software modules were developed for numerical simulations of fundamental heat transfer and fluids processes. The modules combined the ease and attractiveness of Visual Basic user-interfaces with the power and speed of Fortran numerical routines. Color-contour and other visualization schemes were generated from Fortran using the common Windows 16-bit graphics functions.
A Scalable Frame-Level Pipelined Architecture for FSBM Motion Estimation
Authors: Wei-Feng He, Meng-Lian Zhao, Chi-Ying Tsui, Zhi-Gang Mao
Venue: Proceedings of the 20th International Conference on VLSI Design held jointly with 6th International Conference: Embedded Systems (2007)

Block-based motion estimation is widely used in video compression for removing video temporal redundancy. Frame-level pipelined Full-Search Block- Matching motion estimation architecture supports frame-level pipelined operation by exploiting the explicit parallelism among blocks. In this paper, a scalable improved frame-level pipelined architecture for FSBM motion estimation is proposed. The design efforts are focused on extending the array's MAD computation capability while still keeping nearly 100% processor utilization and low hardware overhead. Based on this architecture, a special frame-level pipelined architecture for the case of search range [-N,N -1] is presented, in which internal buffers FIFO1 and FIFO2 are removed and the array's computation capability is 4 times compared with previous W.F. He and Z.G. Mao's architecture. As a result, this architecture offers a feasible solution for HDTV and SHDTV video pictures.
Learning and generalizing control-based grasping and manipulation skills
Authors: Roderic Grupen, Andrew H. Fagg
Venue:  (2006)

One of the main challenges in the field of robotics is to build machines that can function intelligently in unstructured environments. Because of this, the field has witnessed a trend away from the sense-plan-act paradigm where the robot makes an attempt to model everything before planning and acting. Nevertheless, few approaches to robotic grasping and manipulation have been proposed that do not require detailed geometric models of the manipulation environment. One exception is the control-based approach where closed-loop controllers reactively generate grasping and manipulation behavior. This thesis develops and extends the control-based approach to grasping and manipulation and proposes a new framework for learning control-based skills based on generalized solutions. This thesis extends control-based approaches to grasping and manipulation in several ways. First, several new controllers relevant to reaching and grasping are proposed, including a grasp controller that slides contacts over the surface of an object toward good grasp configurations by using haptic feedback. The number of different grasps that can be generated using grasp controllers is expanded through the use of virtual contacts. In addition, a new approach to statically-stable dexterous manipulation is proposed whereby the robot navigates through a space of statically stable grasp configurations by executing closed-loop controllers. In a series of experiments, grasp controllers are shown to be a practical approach to synthesizing different grasps from a variety of different starting configurations. This thesis also proposes a new approach to learning control-based behaviors by applying a generalized solution in new situations. Instead of searching the entire space of all controller sequences and combinations, only variations of a generalized solution, encoded by an action schema, are considered. A new algorithm, known as schema structured learning, is proposed that learns how to apply the generalized solution in different problem contexts through a process of trial and error. This approach is applied to the grasp synthesis problem, enabling a robot to learn grasp skills with relatively little training experience. The algorithm learns to select an appropriate reach-grasp strategy based on coarse visual context. In an experiment where a dexterous humanoid robot grasps a range of grocery items it had no prior experience with, the learned grasp skills are shown to generalize well to new objects and object configurations.
A discrete-time wavelet transform based on a continuous dilation framework
Authors: Wei Zhao
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

We present a new form of wavelet transform. Unlike the continuous wavelet transform (CWT) or discrete wavelet transform (DWT), the mother wavelet is chosen to be a discrete-time signal and wavelet coefficients are computed by correlating a given discrete-time signal with continuous dilations of the mother wavelet. The results developed are based on the definition of a discrete-time scaling (dilation) operator through a mapping between the discrete and continuous frequencies. The forward and inverse wavelet transforms are formulated. The admissibility condition is derived, and examples of discrete-time wavelet construction are provided. The new form of wavelet transform is naturally suited for discrete-time signals and provides analysis and synthesis of such signals over a continuous range of scaling factors.
GeoGrid: A Scalable Location Service Network
Authors: Jianjun Zhang, Gong Zhang, Ling Liu
Venue: Proceedings of the 27th International Conference on Distributed Computing Systems (2007)

This paper presents GeoGrid, a geographical location service overlay network system, for providing scalable location-based services to a large and growing number of mobile users. GeoGrid is designed as a decentralized and geographical location aware overlay network and provides system-level facilities and optimizations for balancing load in the presence of node heterogeneity, dynamically moving hot-spots (location queries), and unpredictable rate of node join, departure and failure. GeoGrid uses geographical mapping of nodes to regions and geographical proximity based routing to take advantage of the similarity between physical and network proximity. Furthermore, GeoGrid exploits multiple opportunities for dynamic workload adaptation in the presence of static hotspot queries and moving hotspot queries. Its dynamic load balancing algorithms can efficiently utilize the heterogeneous capacities of end systems and balance both the location query workload and the routing workload.Our initial prototype development and experimental study demonstrate that GeoGrid can effectively reduce the workload imbalance by an order of magnitude.
Pulse train deinterleaving: algorithms and cost criteria
Authors: K. S. M. Lee
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 05 (1999)

Consider the problem where pulse trains transmitted from a known number of sources are received on a single communications channel. These pulses are corrupted with noise. The deinterleaving problem is to determine which source contributed which pulse and the periods and phases of each source. This paper explores the performance of a number of deinterleaving algorithms. We propose an alternative to the existing forward dynamic programming (FDP) technique: simulated annealing (SA). It can use either the same cost function as for FDP, or an L/sub 1/ or L/sub 2/ norm output error cost function. We also investigate modelling the noise by heavy-tailed distributions, in addition to white Gaussian noise (WGN).
Sinusoidal modeling of audio and speech using psychoacoustic-adaptive matching pursuits
Authors: R. Heusdens
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05 (2001)

We propose a segment-based matching pursuit algorithm where the psychoacoustical properties of the human auditory system are taken into account. Rather than scaling the dictionary elements according to auditory perception, we define a psychoacoustic-adaptive norm on the signal space which can be used for assigning the dictionary elements to the individual segments in a rate-distortion optimal manner. The new algorithm is asymptotically equal to signal-to-mask ratio based algorithms in the limit of infinite analysis window length. However, the new algorithm provides a significantly improved selection of the dictionary elements for finite window length.
Kernel PCA in Detecting Moving Vehicle from Its Viewpoint
Authors: Anand Santhanam, M. Masudur Rahman
Venue: Proceedings of the International Conference on Computing: Theory and Applications (2007)

Kernel Principal Component Analysis (KPCA) has gained much attention for capturing nonlinear image features which is particulary important for clustering high-dimensional multi-class features. We introduce KPCA in this paper for detecting and classifying moving vehicles from its viewpoint images. The KPCA extracts non-linear features of multi-class moving vehicles by mapping input space to a higher dimensional feature space through a non-linear map. The results provide us a clustered feature space of the car and non-car for classifying them by separating the dimensional space or eigenvector. The experimental results show the robustness of the KPCA's feature separation in our car database that lead to the cars' classification. Extended experiments on various vehicles detection have also shown the remarkable performance of the proposed method.
Economic Model for Replicated Database Placement in Grid
Authors: Cherif Haddad, Yahya Slimani
Venue: Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid (2007)

Grid infrastructures enable the creation of virtual organizations for sharing distributed resources across the world with different usage or access policies, different cost models, and varying workloads and availability. Database plays an important role in fulfilling the data management requirements of Grid applications thanks to its advanced data management capability. However, when we want to integrate databases in a grid, we have to address a number of issues. One of them is the problem of database placement. In this paper, we define an economic model for the problem of database placement in Grid architecture. We propose an economic model for regulating data supply and queries. Our proposal is evaluated with OptorSim simulator. The experiments show that our proposed model results in a notable improvement for distributed query processing.
Modeling Distributed Scheduling via Fuzzy Constraint-Based Agent Negotiation
Authors: K. Robert Lai, Menq-Wen Lin, Bo-Rue Kao
Venue: Proceedings of the Third International Conference on Autonomic and Autonomous Systems (2007)

This paper presents a general framework for modeling a distributed scheduling problem via fuzzy constraint-based agent negotiation. Fuzzy constraints, in this way, are used not only to represent the requirements that jobs being scheduled must satisfy, but also to specify the possibilities prescribing to what extent the solutions are suitable for scheduling to rank the solutions. Furthermore, fuzzy constraint-based agent negotiation provides a systematic method to gradually relax the requirements to generate a proposal, and then utilizes possibility functions to select an alternative that is subject to the others' acceptability. Each agent, on behalf of each entity involved in the scheduling, iteratively proposes its offers in order to gradually move toward a satisfactory schedule. The iterative nature of agent negotiation process forces the convergence between demand and offer. Thus, each agent, who is in charge of different aspects of the problem, not only distributively solves its problems to maximize its local objectives, but also works together with other agents to attain a globally beneficial schedule. Experimental results suggest that the proposed approach is focused not only on the minimization of parameters such as makespan and tardiness, but also on the economical effects to maximize the profits of the enterprise.