ppxscal/embedding_network huggingface dataset:
Parallel domain decomposition for simulation of large-scale power grids
Authors: Kai Sun, Quming Zhou, Kartik Mohanram, Danny C. Sorensen
Venue: Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design (2007)

This paper presents fully parallel domain decomposition (DD) techniques for efficient simulation of large-scale linear circuits such as power grids. DD techniques that use non-overlapping and overlapping partitioning of power grids are described in this paper. Simulation results show that with the proposed parallel DD framework, existing linear circuit simulators can be extended to handle large-scale power grids. Results for circuits with more than four million nodes indicate that parallel DD with LU factorization is most suitable for power grid simulation. However, for densely connected power grids, parallel DD with additive Schwarz preconditioning offers maximum scalability and best performance.
Marketing strategies in virtual worlds
Authors: Tsz-Wai Lui, Gabriele Piccoli, Blake Ives
Venue: ACM SIGMIS Database (2007)

More and more businesses are selling products and providing services through multiple channels. 3D virtual worlds are emerging to be one of the channels for companies to communicate with their customers. Being able to simulate similar experiences as customers have in real stores, virtual worlds are able to enhance product knowledge, attitude and purchase intention of customers. However, not all product attributes are able to be experienced virtually because not all kinds of senses (e.g. taste) can be digitzed and presented through a virtual reality interface. Applying theory of cognitive fit and media richness theory, we propose the products attributes that can be experienced virtually with the current technologies. These product attributes and their moderating effects on the relationships between virtual reality and product knowledge, attitude and purchase intention should be studied further so that companies can make decides on the investment in their presence in virtual worlds and the marketing strategies most appropriate for their products.
A memory efficient partially parallel decoder architecture for quasi-cyclic LDPC codes
Authors: Zhongfeng Wang, Zhiqiang Cui
Venue: IEEE Transactions on Very Large Scale Integration (VLSI) Systems (2007)

This paper presents a memory efficient partially parallel decoder architecture suited for high rate quasi-cyclic low-density parity-check (QC-LDPC) codes using (modified) min-sum algorithm for decoding. In general, over 30% of memory can be saved over conventional partially parallel decoder architectures. Efficient techniques have been developed to reduce the computation delay of the node processing units and to minimize hardware overhead for parallel processing. The proposed decoder architecture can linearly increase the decoding throughput with a small percentage of extra hardware. Consequently, it facilitates the applications of LDPC codes in area/power sensitive high-speed communication systems.
LiTPiC -- Light-trails and Photonic Integrated Circuits: Issues of Network Design and Performance
Authors: Ashwin Gumaste, Nasir Ghani
Venue: Proceedings of the 32nd IEEE Conference on Local Computer Networks (2007)

A recent advance in high-speed networks is the concept of Photonic Integrated Circuits (PICs) on an Indium Phosphide substrate, allowing miniaturization and integration of multiple OE and EO modules in a chip. PICs have the potential to do away with the opto-electronic bandwidth mismatch as well as result in severe cost reduction, hence questioning the need for all-optical networking. In this paper we analyze the impact of this digital optical networking concept by combining PIC technology with an all-optical solution -- light-trails, resulting in a new solution called LiTPiC (Light-Trail Photonic Integrated Circuit). LiTPiCs offer the best of both digital and all-optical worlds. By enabling selective (and on-demand) regeneration of the signal, we are able to enhance the reach of all-optical light-trails. In addition, we are able to partition light-trail buses into multiple geographically disjoint sub-buses called PIC-Trails, thus for the first time introducing wavelength reuse within a light-trail. The LiTPiC concept gives PICs a new direction -- that of being a technology enabler for next generation services using ROADM (Reconfigurable Optical Add-Drop Multiplexer) architecture and a complementary solution to the light-trail technology.
An Efficient Thresholding Algorithm for Brazilian Bank Checks
Authors: C. Mello, B. Bezerra, C. Zanchettin, V. Macario
Venue: Proceedings of the Ninth International Conference on Document Analysis and Recognition - Volume 01 (2007)

It is present herein an algorithm for thresholding images of bank checks. These images have complex background elements. Some of these patterns make very hard to distinguish between the text and the texture pattern defined by the bank. For the binarizing process, an adaptive global thresholding algorithm is proposed based on ROC curves and it is compared to several well-known algorithms. The images generated by the new algorithm achieved a hit rate of 97% for recognition of the CMC7 code.
Stack Computers: An Introduction
Authors: D. M. Bulman
Venue: Computer (1977)

Basic idea. The stack, or last-in first-out store, has become more familiar recently because many microprocessors have incorporated a stack in some form. In some microprocessors, the stack can only contain return addresses for subroutines; in others there are provisions for holding temporary data in the stack. The stack derives its name from the idea that items are placed on the "top," thus "pushing down" those items already on the stack. Items are removed from the top, "popping up" those items remaining on the stack.
XWAVE: optimal and approximate extended wavelets
Authors: Sudipto Guha, Chulyun Kim, Kyuseok Shim
Venue: Proceedings of the Thirtieth international conference on Very large data bases - Volume 30 (2004)

Wavelet synopses have been found to be of interest in query optimization and approximate query answering. Recently, extended wavelets were proposed by Deligiannakis and Roussopoulos for data sets containing multiple measures. Extended wavelets optimize the storage utilization by attempting to store the same wavelet coefficient across different measures. This reduces the bookkeeping overhead and more coefficients can be stored. An optimal algorithm for minimizing the error in representation and an approximation algorithm for the complementary problem was provided. However, both their algorithms take linear space. Synopsis structures are often used in environments where space is at a premium and the data arrives as a continuous stream which is too expensive to store. In this paper, we give algorithms for extended wavelets which are space sensitive, i.e., use space which is dependent on the size of the synopsis (and at most on the logarithm of the total data) and operates in a streaming fashion. We present better optimal algorithms based on dynamic programming and a near optimal approximate greedy algorithm. We also demonstrate the performance benefits of our algorithms compared to previous ones through experiments on real-life and synthetic data sets.
Ontology-BasedWeb Data Integration Architecture Modeling and Implementation
Authors: Guan-yu LI, Wei-li ZHANG, Huan-zhong GENG
Venue: Proceedings of the 2007 IFIP International Conference on Network and Parallel Computing Workshops (2007)

Web data integration has overcome structural heterogeneities by using XML, but failed to overcome the semantic heterogeneities. To solve this problem, a architecture for ontology-based web data integration system is proposed. Then the infrastructure of Ontology, the mapping algorithm between Ontology and data sources, and semantic query are mainly discussed. To large extent, the semantic heterogeneity problem is overcome by using the proposed architecture.
A PSO-Based Web Document Classification Algorithm
Authors: Ziqiang Wang, Qingzhou Zhang, Dexian Zhang
Venue: Proceedings of the Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing - Volume 03 (2007)

Due to the exponential growth of documents in the Internet and the emergent need to organize them, the automatic document classification has received an ever-increased attention in the recent years. The particle swarm optimization (PSO) algorithm, new to the document classification community, is a robust stochastic evolutionary algorithm based on the movement and intelligence of swarms. In this paper, a PSO-based algorithm for document classification is presented. Comparison between our method and other conventional document classification algorithms is conducted on Reuter and TREC corpora. The experimental results indicate that our proposed algorithm yields much better performance than other conventional algorithms.
To share or not to share?
Authors: Ryan Johnson, Stavros Harizopoulos, Nikos Hardavellas, Kivanc Sabirli, Ippokratis Pandis, Anastasia Ailamaki, Naju G. Mancheril, Babak Falsafi
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

Intuitively, aggressive work sharing among concurrent queries in a database system should always improve performance by eliminating redundant computation or data accesses. We show that, contrary to common intuition, this is not always the case in practice, especially in the highly parallel world of chip multiprocessors. As the number of cores in the system increases, a trade-off appears between exploiting work sharing opportunities and the available parallelism. To resolve the trade-off, we develop an analytical approach that predicts the effect of work sharing in multi-core systems. Database systems can use the model to determine, statically or at runtime, whether work sharing is beneficial and apply it only when appropriate. The contributions of this paper are as follows. First, we introduce and analyze the effects of the trade-off between work sharing and parallelism on database systems running complex decision-support queries. Second, we propose an intuitive and simple model that can evaluate the trade-off using real-world measurement approximations of the query execution processes. Furthermore, we integrate the model into a prototype database execution engine, and demonstrate that selective work sharing according to the model outperforms never-share static schemes by 20% on average and always-share ones by 2.5x.
Profile-guided optimization of critical medical imaging algorithms
Authors: David R. Kaeli, Byunghyun Jang, Perhaad Mistry, Dana Schaa
Venue: Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro (2009)

Given the rapid growth in computational requirements for medical image analysis, Graphics Processing Units (GPUs) have begun to be utilized to address these demands. But even though GPUs are well-suited to the underlying processing associated with medical image reconstruction, extracting the full benefits of moving to GPU platforms requires significant programming effort, and presents a fundamental barrier for more general adoption of GPU acceleration in a wider range of medical imaging applications. In this paper we describe our experience in accelerating a number of challenging medical imaging applications, and discuss how we utilize profile-guided analysis to reap the full benefits available on GPU platforms. Our work considers different GPU architectures, as well as how to fully exploit the benefits of using multiple GPUs.
Biomedical imaging ecosystem and the role of the GPU
Authors: Kimberly Powell
Venue: Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro (2009)

The biomedical imaging chain is continuously being challenged to reconstruct, analyze, and visualize increasing amounts of data in shorter amounts of time. Parallel computing on multi-core devices and clustered computers has allowed for continued innovation of compute and processing technologies but not without facing serious constraints of cost, space, and power consumption. Over the last three years the graphics processing unit (GPU) and its increased programmability has played an integral role in defining a new dimension to parallel computing with its single chip, many-core architecture as well as evolving the graphics pipeline to enhance visualization techniques. Image reconstruction, segmentation and registration algorithms architected to take advantage of the GPU parallel architecture not only realize massive processing speedups but also set the stage for scalability. High resolution rendering of 3D and 4D datasets are navigated in interactive, real-time approaches. Real time ray tracing and 3D stereoscopic solutions bring increased realism to images. Understanding the optimized mix of GPU and CPU, both in the sense of hardware and software, is necessary for imaging applications to innovate, realize cost/performance efficiency and continue to enhance visualization. Several approaches for GPU programmability are available and will be explored. Innovations in the compute, graphics and visualization space will be discussed to show the relevance of the GPU throughout the imaging chain.
VOLES: vascularity-oriented level set algorithm for pulmonary vessel segmentation in image guided intervention therapy
Authors: Xiangjun Zhu, Zhong Xue, Xin Gao, Yisheng Zhu, Stephen T. C. Wong
Venue: Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro (2009)

Delicate surgical planning and accurate guidance plays an important role in successful image guided intervention. In interventional lung cancer diagnosis and treatments, precise segmentation of pulmonary vessels from lung CT images provides vital visualization for pre-op planning and inra-op guidance to avoid major vessel damage. While simple thresholding and window/level setting can briefly segment different tissues, their results are not accurate. Recently, level set methods have been increasingly and successfully used in various organ segmentations, however, the penalty on large curvature makes the evolution along vascular structure slow, thus rendering difficulty in lung vessels. In this paper, we propose a Vascularity-Oriented LEvel Set algorithm (VOLES) to offset the curvature effect on the evolving front along vessel directions, also the evolution direction can be adaptively adjusted based on the joint intensity and vesselness statistics to prevent leakage and to adapt to intensity inhomogeneity. The VOLES algorithm is validated using lung CT images in the experiments, and results show it outperforms the traditional level set method on pulmonary vessel segmentation.
Energy-aware task assignment and data aggregation protocols in wireless sensor networks
Authors: Hady S. AbdelSalam, Syed R. Rizvi, Stephan Olariu
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

In a typical sensor network environment, sensor energy is considered a precious resource that must be used wisely and only if necessary. Energy-unaware task assignment protocols can deplete the energy of some sensors much more than they do for others. This results in reducing network density around those heavily loaded sensors and eventually creates energy holes that isolate the network into separated islands. These problems have negative impacts on network durability and reliability. To avoid these problems, we propose and evaluate a lightweight management protocol that assigns tasks to sensors based on their energy so that energy consumption is almost even among network sensors. In addition, we propose another mechanism to aggregate data collected by sensors before sending them back to the base station. Our aggregation mechanism supports different aggregation functions including exact evaluation of the minimum, the maximum, and the logical OR and an approximation of the average of the collected sensory data. Using simulation, we compare the lifetime achieved by assigning tasks to network sensors using the proposed protocol against another energy-neutral protocol. Simulation results verified that the proposed approach increases network durability by balancing task load among sensors. Also simulation shows that, under reasonable parameters, the error in the approximated value of the average is less than %3.
A fundamental characterization of stability in broadcast queueing systems
Authors: Chan Zhou, Gerhard Wunder
Venue: Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2 (2009)

Stability with respect to a given scheduling policy has become an important issue for wireless communication systems; but hard to prove in particular scenarios. In this paper two sufficient conditions for stability in a broadcast setting are derived, which are often very easy to check. Moreover, it is shown that if the given scheduling policy complies with both conditions the resulting throughput region of the policy equals the ergodic achievable rate region and the system is stable in a strong sense. This extends results presented in [1] where the statement was shown for scheduling policies fulfilling so-called integrability condition. Additionally, in this paper we also present a partial converse to the statement which is demonstrated by an application example.
Email shape analysis for spam botnet detection
Authors: Paul Sroufe, Santi Phithakkitnukoon, Ram Dantu, João Cangussu
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

Botnets have become the major sources of spamming, which generates massive unwanted traffic on networks. An effective detection mechanism can greatly mitigate the problem. In this paper, we present a novel botnet detection mechanism based on the email "shape" analysis that relies on neither content nor reputation analysis. Shape is our new way of characterizing an email by mimicking human visual inspection. A set of email shapes are derived and then used to generate a botnet signature. Our preliminary results show greater than 80% classification accuracy (without considering email content or reputation analysis). This work investigates the discriminatory power of email shape, for which we believe will be a significant complement to other existing techniques such as a network behavior analysis.
Capacity of MIMO DSL systems using 100 MHz measured channel data
Authors: Diogo Acatauassú, Francisco C. B. F. Müller, Aldebaro Klautau
Venue: Proceedings of the 16th international conference on Telecommunications (2009)

This paper evaluates the capacity of MIMO DSL systems up to 100 MHz using short loops (50 and 200 meters) based on measured channel data. The experimental results show that these systems have capacities as high as 0.77 Gbps for the 50 m loop, for example.
A cognitive beamforming scheme for coexistence of incumbent and cognitive radios
Authors: Jaewoon Kim, Sanhae Kim, Oh-Soon Shin, Yoan Shin
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

We propose a new cognitive beamforming scheme for coexistence of IR (Incumbent Radio) CR (Cognitive Radio). The proposed cognitive beamforming scheme does not cause any interference to the IRU (IR User), while the CRU (Cognitive Radio User) is served without additional radio resource consumption. Simulation results show that when using the proposed scheme the CRU does not interfere to the IRU and there is little bit error rate performance degradation of the CRU as compared to that of the ideal beamforming system which does not consider the IR priority.
Networking aspects for the security of game input
Authors: Christos Bouras, Vassilis Poulopoulos, Vassilis Tsogkas
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

Following the trends of our era, Games At Large IST Project introduces an innovative platform for running interactive, rich content multimedia applications over a Wireless Local Area Network. Games@Large project's vision is to provide a new system architecture for Interactive Multimedia which will enhance existing CE devices such as, Set Top Boxes (STB), Small Screen and other devices, which are lacking both the CPU power and the graphical performance to provide a rich user experience. This paper presents the input command transferring module that provides encryption capabilities for ensuring the security of the transmitted sensitive user data. In a nutshell, the client software when capturing input from a keyboard device encrypts the commands that are transmitted over a Wireless Local Area Network, using a public key encryption scheme and the server is responsible for decrypting and executing the commands to the corresponding game application.
Grid-based multi-path with congestion avoidance routing (GMCAR) protocol for wireless sensor networks
Authors: Omar Banimelhem, Samer Khasawneh
Venue: Proceedings of the 16th international conference on Telecommunications (2009)

A new routing protocol that handles real-time and non-real time applications in Wireless Sensor Networks (WSNs) is proposed. We employ the idea of dividing the sensor network field into grids. Inside each grid, one of the sensor nodes is selected as a master node which is responsible for delivering the data generated by any node in that grid and for routing the data received from other master nodes in the neighbor grids. For each master node, multiple paths that connect the master node to the sink are stored as routing entries in the routing table of that node. These paths are the diagonal paths between the sink and the master node. In case of congestion occurrence, a novel congestion control mechanism is also proposed in order to relieve the congested areas. Simulation results have shown that our proposed protocol has the capability to extend the lifetime of the sensor network and to utilize the available storage.
Extracting nonlinear features for multispectral images by FCMC and KPCA
Authors: Zhan-Li Sun, De-Shuang Huang, Yiu-Ming Cheun
Venue: Digital Signal Processing (2005)

Classification is a very important task for scene interpretation and other applications of multispectral images. Feature extraction is a key step for classification. By extracting more nonlinear features than corresponding number of linear features in original feature space, classification accuracy for multispectral images can be improved greatly. Therefore, in this paper, an approach based on the fuzzy c-means clustering (FCMC) and kernel principal component analysis (KPCA) is proposed to resolve the problem of multispectral images. The main contribution of this paper is to provide a good preprocessed method for classifying these images. Finally, some experimental results demonstrate that our proposed method is effective and efficient for analyzing the multispectral images.
VoroGame: a hybrid P2P architecture for massively multiplayer games
Authors: Eliya Buyukkaya, Maha Abdallah, Romain Cavagna
Venue: Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference (2009)

Peer-to-peer (P2P) architectures have recently become very popular in massively multiplayer games (MMGs). While P2P gaming offers high scalability compared to client/server architectures, it introduces several major issues related to data distribution and game state consistency. In this paper, we report our initial version of VoroGame, a P2P architecture for MMGs that addresses these issues by combining a structured P2P overlay based on a distributed hash table (DHT) for data distribution, with a Voronoi diagram used for virtual game world decomposition and semantic overlay support. The resulting hybrid architecture enables a fully distributed management of data and state information, and ensures efficient dissemination of game state updates to relevant peers.