ppxscal/embedding_network huggingface dataset:
Convergence-speed enhancement of two classes of (Ωα)-fair rate allocation algorithms
Authors: P. Goudarzi, F. Sheikholeslam
Venue: Proceedings of the 4th WSEAS International Conference on Telecommunications and Informatics (2005)

Fairness is an important aspect of any rate allocation strategy. Many fairness criteria have been proposed by different researchers. Mo and Walrand have introduced the notion of (Ω,α)-fairness in their pioneering work in 2000. Different fairness criteria such as proportional, minimum potential delay and max-min fairness are derived as special cases of (Ω,α)-fairness. In the current paper, a fast second-order rate allocation algorithm is proposed that can improve the convergence speed of conventional methods. Under certain (and almost) practical premises about the network topology, an end-to-end implementation of well-known proportional and minimum potential delay fair rate allocation algorithms is introduced. The proposed algorithm has been compared with the conventional method and TCP using simulation. The simulation results show that the proposed method, outperforms the conventional ones in convergence rate.
Automatic discovery and transfer of MAXQ hierarchies
Authors: Neville Mehta, Soumya Ray, Prasad Tadepalli, Thomas Dietterich
Venue: Proceedings of the 25th international conference on Machine learning (2008)

We present an algorithm, HI-MAT (Hierarchy Induction via Models And Trajectories), that discovers MAXQ task hierarchies by applying dynamic Bayesian network models to a successful trajectory from a source reinforcement learning task. HI-MAT discovers subtasks by analyzing the causal and temporal relationships among the actions in the trajectory. Under appropriate assumptions, HI-MAT induces hierarchies that are consistent with the observed trajectory and have compact value-function tables employing safe state abstractions. We demonstrate empirically that HI-MAT constructs compact hierarchies that are comparable to manually-engineered hierarchies and facilitate significant speedup in learning when transferred to a target task.
ACM's place in the global picture
Authors: Wendy Hall
Venue: Communications of the ACM (2008)

ACM's new president intends to make international initiatives a top priority, hoping to share the Association's riches with a greater global audience.
A comparison of the osteogenic potential of adult rat mesenchymal stem cells cultured in 2-D and on 3-D collagen glycosaminoglycan scaffolds
Authors: E. Farrell, E. M. Byrne, J. Fischer, F. J. O'Brien, B. C. O'Connell, P. J. Prendergast, V. A. Campbell
Venue: Technology and Health Care (2007)

Adult mesenchymal stem cells (MSCs) have the capability to differentiate along several lineages including those of bone, cartilage, tendon and muscle, thus offering huge potential for the field of tissue engineering. The purpose of this study was to characterise the differentiation capacity of rat MSCs cultured on standard plastic coverslips in 2 dimensions and on a novel collagen glycosaminoglycan scaffold in the presence of a standard combination of osteoinductive factors. Cells were cultured for 3, 7, 14 and 21 days and several markers of osteogenesis were analysed. While the initial response of the cells in 3-D seemed to be faster than cells cultured in 2-D, as evidenced by collagen type I expression, later markers showed that osteogenic differentiation of MSCs took longer in the 3-D environment of the collagen GAG scaffold compared to standard 2-D culture conditions. Furthermore, it was shown that complete scaffold mineralisation could be evoked within a 6 week timeframe. This study further demonstrates the potential use of MSC-seeded collagen GAG scaffolds for bone tissue engineering applications.
Honeycomb: A Novel Approach for Construction of Stable ALM Overlay
Authors: Baiqiang Liu, Takeshi Tsuchiya, Keiichi Koyanagi
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

We propose a novel approach for construction of stable peer-to-peer overlay for Application Layer Multicast using honeycomb structure. This structure is focused on single source Audio/Video streaming on Internet. Bandwidth, stability and failure recovery are primary metrics in this application domain. In our Honeycomb approach, we propose an algorithm for clustering peers into a stable honeycomb structure, utilizing nature stability of honeycomb to let failure recovery to be done regionally and quickly with impact only on a small number of peers with no burden on the source server. Based on basic Honeycomb overlay, we propose a mechanism to efficiently use bandwidth by exchanging suited peers’ position in overlay. Finally, Simulations using NS-2 prove the stability of Honeycomb.
Surface inspection of polyurethane foam by image processing and artificial neural networks techniques
Authors: Arantza Bereciartua, José Angel Gutiérrez Olabarria, Artzai Picón, Alfonso Maestro Martínez, Jefe de Proyectos
Venue: Proceedings of the 4th WSEAS International Conference on Signal Processing, Computational Geometry & Artificial Vision (2004)

Quality assurance is a necessity in the industrial processes. The machine vision technology is an efficient technology for the reliable and fast control of different types of products. This technology allows obtaining a big amount of visual information, superficial and dimensional at a high speed. The objective of this article is to describe a successful application of machine vision technology in a Foam production, a productive sector where this technology is scarcely inserted. The aim of this project is to obtain on-line visual parameters of the process in order to modify the variables of production immediately in an automated way. Those parameters were obtained off-line by means of human visual inspection two days later in a laboratory analysis before this project. The difficulty lies in the fact that visual characteristics of both samples (on-line and off-line) are very different.
Investigation of 3D geometry of bulk wheat and pea pores using X-ray computed tomography images
Authors: S. Neethirajan, D. S. Jayas, N. D. G. White, H. Zhang
Venue: Computers and Electronics in Agriculture (2008)

Quantitative characterization of pore topology inside grain bulks is necessary to predict the air traverse time and the cooling or fumigation pattern for the design of storage management strategies. Quantification of 3D microarchitecture of the inter-granular airspace in the grain bulks can also contribute to the development of predictive models of insect movement and for designing acoustic systems for insect infestation detection. In this study, inter-connected 3D array of void spaces was characterized by geometrical quantities such as specific surface area, pore throat size and nodal pore volume. These features were obtained from a 13.1cmx13.1cmx5cm volume of wheat and pea bulks. The grain bulks were imaged using a high resolution X-ray computed tomography system at 200@mm resolution. The spatial distributions were computed based on 3D medial axis analysis of the void space in the images using 3DMA-Rock software and a high performance Polaris computer. The other features calculated were medial axis tortuosity, throat surface area and porosity from the 3D images. Characterization of pore throat network provides reliable observation for facilitating realistic prediction of permeability and the nature of air and gas distribution inside grain bulks.
Fine-grained relevance feedback for XML retrieval
Authors: Hanglin Pan, Ralf Schenkel, Gerhard Weikum
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

This demonstration presents an XML IR system that allows users to give feedback of different granularities and types, using Dempster-Shafer theory of evidence to compute expanded and reweighted queries.
Improving the schedulability of soft real-time open dynamic systems: The inheritor is actually a debtor
Authors: Rodrigo Santos, Giuseppe Lipari, Jorge Santos
Venue: Journal of Systems and Software (2008)

This paper presents the Clearing Fund Protocol, a three layered protocol designed to schedule soft real-time sets of precedence related tasks with shared resources. These sets are processed in an open dynamic environment. Open because new applications may enter the system at any time and dynamic because the schedulability is tested on-line as tasks request admission. Top-down, the three layers are the Clearing Fund, the Bandwidth Inheritance and two versions of the Constant Bandwidth Server algorithms. Bandwidth Inheritance applies a priority inheritance mechanism to the Constant Bandwidth Server. However, a serious drawback is its unfairness. In fact, a task executing in a server can potentially steal the bandwidth of another server without paying any penalty. The main idea of the Clearing Fund Algorithm is to keep track of processor-time debts contracted by lower priority tasks that block higher priority ones and are executed in the higher priority servers by having inherited the higher priority. The proposed algorithm reduces the undesirable effects of those priority inversions because the blocked task can finish its execution in its own server or in the server of the blocking task, whichever has the nearest deadline. If demanded, debts are paid back in that way. Inheritors are therefore debtors. Moreover, at certain instants in time, all existing debts may be waived and the servers are reset making a clear restart of the system. The Clearing Fund Protocol showed definite better performances when evaluated by simulations against Bandwidth Inheritance, the protocol it tries to improve.
Fuzzy logic weighted multi-criteria of dynamic route lifetime for reliable multicast routing in ad hoc networks
Authors: Bey-Ling Su, Ming-Shi Wang, Yueh-Ming Huang
Venue: Expert Systems with Applications: An International Journal (2008)

In this paper, we proposed the fuzzy logic modified AODV routing (FMAR) protocol for multicast routing in mobile ad hoc networks. The fuzzy logic weighted multi-criteria of the protocol is used to dynamically evaluate the active route lifetime in order to determine the appropriate routes. Multiple routing paths are established to provide extra schemas of video streaming or multicast transmission and enhance the robust transmission against unreliability and limited bandwidth of wireless links. Due to frequent node movements, the topologies of mobile ad hoc networks change rapidly. The evaluation of dynamic route lifetime is challenging in the wireless networks. The fuzzy weighted logic multi-criteria are based on the remained energies of the nodes on the routes, the number of hop-counts and the sent controlled packages. The simulation results of the FMAR show that the protocol is quite efficient and superior to AODV with the respects to the node mobility, the packet delivery ratio, average route acquisition latency delay, the routing overhead and the average end-to-end delay.
Mesh Composition on Models with Arbitrary Boundary Topology
Authors: Juncong Lin, Xiaogang Jin, Charlie Wang, Kin-Chuen Hui
Venue: IEEE Transactions on Visualization and Computer Graphics (2008)

This paper presents a new approach for the mesh composition on models with arbitrary boundary topology. After cutting the needed parts from existing mesh models and putting them into the right pose, an implicit surface is adopted to smoothly interpolate the boundaries of models under composition. An interface is developed to control the shape of the implicit transient surface by using sketches to specify the expected silhouettes. After that, a localized Marching Cubes algorithm is investigated to tessellate the implicit transient surface so that the mesh surface of composed model is generated. Different from existing approaches in which the models under composition are required to have pairwise merging boundaries, the framework developed based on our techniques have the new function to fuse models with arbitrary boundary topology.
Classified road detection from satellite images based on perceptual organization
Authors: J. Yang, R. S. Wang
Venue: International Journal of Remote Sensing (2007)

Extracting roads from satellite images is an important task in both research and practice. This work presents an improved model for road detection based on the principles of perceptual organization and classification fusion in human vision system (HVS). The model consists of four levels: pixels, primitives, structures and objects, and two additional sub-processes: automatic classification of road scenes and global integration of multiform roads. Based on the model, a novel algorithm for detecting roads from satellite images is also proposed, in which two types of road primitives, namely blob-like primitive and line-like primitive are defined, measured, extracted and linked using different methods for dissimilar road scenes. A hierarchical search strategy driven by saliency measurement is adopted in both linking processes. The blob primitives are linked using heuristic grouping and the line primitives are connected through genetic algorithm (GA) evolution. Finally, all of the linked road segments are normalized with centre-main lines and integrated into global smooth road curves through tensor voting. Experimental results show that the algorithm is capable of detecting multiform roads from real satellite images with high adaptability and reliability.
Improving the Analysis of Lawfully Intercepted Network Packet Data Captured for Forensic Analysis
Authors: Joshua Broadway, Benjamin Turnbull, Jill Slay
Venue: Proceedings of the 2008 Third International Conference on Availability, Reliability and Security (2008)

Lawful interception of a suspects’ personal Internet communications can be a very effective evidence collection mechanism for use in criminal investigations. Once a lawful interception warrant has been obtained, software applications known as packet sniffers are used to capture all network packets being sent to and from a suspect’s personal computer. Existing packet sniffer and protocol analyser applications, both open-source and commercial, have limitations in their usefulness in criminal investigations. This research outlines a process and framework, the Highly Extensible Network Packet Analysis (HENPA) framework, which takes the output of a packet sniffer and processes the data to extract potential forensic evidence.
A unified fault-tolerant routing scheme for a class of cluster networks
Authors: Khaled Day, Bassel Arafeh, Abderezak Touzene
Venue: Journal of Systems Architecture: the EUROMICRO Journal (2008)

Large cluster systems with thousands of nodes have become a cost-effective alternative to traditional supercomputers. In these systems cluster nodes are interconnected using high-degree switches. Regular direct interconnection network topologies including tori (k-ary n-cubes) and meshes are among adapted choices for interconnecting these high-degree switches. We propose a generalized fault-tolerant routing scheme for highly connected regular interconnection networks and derive conditions for its applicability. The scheme is based on the availability of efficiently identifiable disjoint routes between network nodes. When routing paths become faulty, alternative disjoint routes are identified and taken. The methods used to identify the routing paths, to propagate failure information, and to switch from a routing path to another incur little communication and computation overhead. If the faults occur reasonably apart in time, then packets are efficiently routed along paths of minimal or near-minimal lengths. In the unlikely case where several faults occur in a short period of time, the scheme still delivers packets but possibly along longer paths. The proposed scheme and its properties are first presented in general terms for any interconnection topology satisfying certain derived connectivity conditions. The applicability of the general scheme is then illustrated on examples of well known regular topologies satisfying the derived connectivity conditions including the binary hypercube, the k-ary n-cube and the star graph networks.
An efficient clustering method for k-anonymization
Authors: Jun-Lin Lin, Meng-Cheng Wei
Venue: Proceedings of the 2008 international workshop on Privacy and anonymity in information society (2008)

The k-anonymity model is a privacy-preserving approach that has been extensively studied for the past few years. To minimize the information loss due to anonymization, it is crucial to group similar data together and then anonymize each group individually. This work proposes a clustering-based k-anonymization method that runs in O(n2/k) time. We experimentally compare our method with another clustering-based k-anonymization method recently proposed by Byun et al. Even though their method has a time complexity of O(n2), the experiments show that our method outperforms their method with respect to information loss and resilience to outliers.
ResIn: a combination of results caching and index pruning for high-performance web search engines
Authors: Gleb Skobeltsyn, Flavio Junqueira, Vassilis Plachouras, Ricardo Baeza-Yates
Venue: Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval (2008)

Results caching is an efficient technique for reducing the query processing load, hence it is commonly used in real search engines. This technique, however, bounds the maximum hit rate due to the large fraction of singleton queries, which is an important limitation. In this paper we propose ResIn - an architecture that uses a combination of results caching and index pruning to overcome this limitation. We argue that results caching is an inexpensive and efficient way to reduce the query processing load and show that it is cheaper to implement compared to a pruned index. At the same time, we show that index pruning performance is fundamentally affected by the changes in the query traffic that the results cache induces. We experiment with real query logs and a large document collection, and show that the combination of both techniques enables efficient reduction of the query processing costs and thus is practical to use in Web search engines.
Comparing acceleration techniques for the dixon and macaulay resultants (abstract only)
Authors: Robert Lewis
Venue: ACM Communications in Computer Algebra (2008)

The Bezout-Dixon resultant method for solving systems of polynomial equations lends itself to various heuristic acceleration techniques, previously reported by the present author [6], which can be extraordinarily effective. In this paper we will discuss how well these techniques apply to the Macaulay resultant. In brief, we find that they do work there with some difficulties, but the Dixon method is greatly superior. That they work at all is surprising and begs theoretical explanation.
A Hierarchical Queueing Model for Streaming Video over Multi-Hop Wireless Networks
Authors: Hao Wang
Venue: Proceedings of the Fifth International Conference on Information Technology: New Generations (2008)

In our previous work, we proposed a distributed buffer (DB) scheme to tackle the problem of transporting layered video over erroneous multi-hop wireless networks. In DB scheme, some intermediate nodes are selected as DB nodes, which are used to pre-buffer video packets before the video streaming starts. In this paper, a novel hierarchical queueing model for DB nodes is proposed. The video playback quality including buffer overflow probability and video quality throughput can be computed based on the proposed queueing model. The simulation result matches the queueing performance of video streaming application.
Incremental margin algorithm for large margin classifiers
Authors: Saul C. Leite, Raul Fonseca Neto
Venue: Neurocomputing (2008)

In this contribution, we introduce a new on-line approximate maximal margin learning algorithm based on an extension of the perceptron algorithm. This extension, which we call fixed margin perceptron (FMP), finds the solution of a linearly separable learning problem given a fixed margin. It is shown that this algorithm converges in (R^2-@c"f^2)/(@c^*-@c"f)^2 updates, where @c"f
Hybridization Model of Linear and Nonlinear Time Series Data for Forecasting
Authors: Roselina Sallehuddin, Siti Mariyam Shamsuddin, Siti Zaiton Mohd Hashim
Venue: Proceedings of the 2008 Second Asia International Conference on Modelling & Simulation (AMS) (2008)

The aim of this paper is to propose a novel approach in hybridizing linear and nonlinear model by incorporating several new features. The intended features are multivariate information, hybridization succession alteration, and cooperative feature selection. To assess the performance of the proposed hybrid model allegedly known as Grey Relational Artificial Neural Network(GRANN_ARIMA), extensive comparisons are done with individual model (Artificial Neural Network(ANN), Autoregressive integrated Moving Average(ARIMA) and Multiple Linear Regression(MR)) and conventional hybrid model (ARIMA_ANN) with Root Mean Square Error(RMSE), Mean Absolute Deviation(MAD), Mean Absolute Percentage Error (MAPE) and Mean Square error( MSE ). The experiments have shown that the proposed hybrid model has outperformed other models with 99.5% forecasting accuracy for small-scale data and 99.84% for large-scale data. The obtained empirical results have also proved that the GRANN-ARIMA is more accurate and robust due to its promising performance and capability in handling small and large scale time series data. In addition, the implementation of cooperative feature selection has assisted the forecaster to automatically determine the optimum number of input factor amid with its important ness and consequence on the generated output.
Minimum-latency gossiping in multi-hop wireless networks
Authors: Scott C.-H. Huang, Hongwei Du, E-K. Park
Venue: Proceedings of the 9th ACM international symposium on Mobile ad hoc networking and computing (2008)

We studied the minimum-latency gossiping (all-to-all broadcast) problem in multi-hop wireless networks defined as follows. Each node in the network is initially given a message and the objective is to design a minimum-latency schedule such that each node distributes its message to all other nodes. We considered the unit-size message model, in which different messages cannot be combined as one message, and the unit disk graph model, in which a link exists between two nodes if and only if their Euclidean distance is less than 1. This problem is known to be NP-hard in such models. In this work we designed a gossiping scheme that significantly improved all current gossiping algorithms in terms of approximation ratio. Our work has approximation ratio 27, a great improvement of the current state-of-the-art algorithm (which has ratio 1000+).
Electronic Mosquito: designing a semi-invasive Microsystem for blood sampling, analysis and drug delivery applications
Authors: Giorgio E. Gattiker, Karan V. I. S. Kaler, Martin P. Mintchev
Venue: Microsystem Technologies (2005)

In this study we present an innovative design idea for a semi-invasive blood sampling, analysis and drug delivery device called &#x201c;Electronic Mosquito&#x201d; (&#x201c;e-Mosquito&#x201d;). The major building blocks of the device are discussed. The principle of operation is described and its feasibility is demonstrated. The integration of the microsystem is outlined and its practical implementation proposed.