ppxscal/embedding_network huggingface dataset:
Agent-Based Resource Discovery and Selection for Dynamic Grids
Authors: George Kakarontzas, Ilias K. Savvas
Venue: Proceedings of the 15th IEEE International Workshops on Enabling Technologies: Infrastructure for Collaborative Enterprises (2006)

The massive amount of resources on computational grids raises the question of efficient resource discovery and selection. In this paper we present an agent-based approach to these two phases of a grid scheduling process. The approach is based on client agents which act on behalf of grid users, and search for resources in a network of resource representatives that are registries of resource characteristics. After potentially suitable resources are discovered, client agents carry out negotiations directly with agents representing local resource management systems. This selection process first determines the willing resources with a contractnet protocol and then uses current load information and a more accurate post-discovery search to determine the optimum set of resources for the task in hand.
User experience design and experimental evaluation of extensible and dynamic viewers for data structures
Authors: James H. Cross,  II
Venue:  (2007)

Many techniques for the visualization of data structures and algorithms have been proposed and shown to be pedagogically effective. Yet, they are not widely adopted because they lack suitable methods for automatically generating the visualizations, lack integration among visualizations, and lack integration with basic integrated development environment (IDE) support. In this work, additionally it was identified that the lack of adoption was because these tools do not focus on one of the main problems students in an introductory level data structures and algorithms class face; that is, the transition from abstract and static concepts to dynamic implementation. To effectively use visualizations when developing code, it is useful to automatically generate multiple synchronized views without leaving the IDE. The jGRASP IDE has been extended to provide object viewers that automatically generate dynamic, state-based visualizations of data structures in Java. Such seamless integration of a lightweight IDE with a set of pedagogically effective software visualizations is unique and is currently unavailable in any other environment.Formal and repeatable controlled experiments were conducted to investigate the effect of these viewers on the performance of students. These studies indicated a statistically significant improvement over traditional methods of visual debugging that use breakpoints. Six controlled experiments were conducted to test various hypotheses. The goal of Experiments I and III was to determine if students would be able to code more accurately and in less time using the jGRASP data structure viewers for a relatively easy (singly linked list) and a relatively hard (linked binary tree) to understand data structure. The goals of Experiment II and IV was to determine if students would be able to find and correct more logical errors accurately and faster using jGRASP viewers for a relatively easy (singly linked list) and a relatively hard (linked binary tree) to understand data structure. Experiment V was conducted using min-max heap to test if students would be able to transition from concept to implementation faster and more accurately using jGRASP viewers for data structures that are covered only conceptually in lectures. Experiment VI was conducted using linked priority queue to test if students would be able to apply concepts for data structures that were not covered in lectures faster and more accurately using jGRASP viewers. In all six experiments, the group using jGRASP viewers performed significantly better than the other group. Thus, this research has shown that automatic generation of visualizations for data structures tightly integrated within an IDE helps students not only learn concepts but also aids in transitioning from static concept to dynamic implementation for both relatively easy and hard to learn data structures.
Address obfuscation: an efficient approach to combat a board range of memory error exploits
Authors: Sandeep Bhatkar, Daniel C. DuVarney, R. Sekar
Venue: Proceedings of the 12th conference on USENIX Security Symposium - Volume 12 (2003)

Attacks which exploit memory programming errors (such as buffer overflows) are one of today's most serious security threats. These attacks require an attacker to have an in-depth understanding of the internal details of a victim program, including the locations of critical data and/or code. Program obfuscation is a general technique for securing programs by making it difficult for attackers to acquire such a detailed understanding. This paper develops a systematic study of a particular kind of obfuscation called address obfuscation that randomizes the location of victim program data and code. We discuss different implementation strategies to randomize the absolute locations of data and code, as well as relative distances between data locations. We then present our implementation that transforms object files and executables at link-time and load-time. It requires no changes to the OS kernel or compilers, and can be applied to individual applications without affecting the rest of the system. It can be implemented with low runtime overheads. Address obfuscation can reduce the probability of successful attacks to be as low as a small fraction of a percent for most memory-error related attacks. Moreover, the randomization ensures that an attack that succeeds against one victim will likely not succeed against another victim, or even for a second time against the same victim. Each failed attempt will typically crash the victim program, thereby making it easy to detect attack attempts. These aspects make it particularly effective against large-scale attacks such as Code Red, since each infection attempt requires significantly more resources, thereby slowing down the propagation rate of such attacks.
Concepts and components of full-system simulation of distributed memory parallel computers
Authors: Francisco Javier Ridruejo, Jose Miguel-Alonso, Javier Navaridas
Venue: Proceedings of the 16th international symposium on High performance distributed computing (2007)

In this work we discuss a range of approaches to full-system simulation of distributed memory parallel computers, with emphasis on the interconnection network. We present our environment, based on Simics®, and discuss how unforeseen interactions and fine tuning of components can affect results.
A single-chip MPEG-2 MP@ML audio/video encoder/decoder with a programmable video interface unit
Authors: C. T. Chen
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02 (2001)

We present a single-chip, MPEG-2 main profile at main level, audio and video encoder and decoder. It combines a RISC core, a 24-bit DSP, video and audio interface units, and several dedicated processing units. A programmable video interface unit supports multiple modes of pre- and post-processing and on-screen display (OSD). The codec has been implemented using a standard-cell library in 0.18 /spl mu/m CMOS technology.
Energy-efficient scheduling algorithms for real-time systems
Authors: Steve Goddard
Venue:  (2006)

Over the past several years, many embedded real-time systems have emerged with energy conservation requirements. Most of these systems comprise battery-operated microprocessors and I/O devices. The increasingly complex software and faster hardware used by these systems introduce more energy consumption, but battery technology is not keeping up. Therefore, aggressive energy conservation techniques are needed to extend their lifetimes. Traditionally, the research community has focused on processor-based power management techniques, with many articles published on processor energy conservation. On the other hand, research of power conservation for I/O devices as well as the overall system has received little attention. In this dissertation, we first analyze the problem of online energy aware I/O scheduling for embedded real-time systems. We introduce the concept of device slack to represent the length of time that a device can be put in the low power state without causing any job to miss its deadline. Based on the concept of device slack, we propose two online energy-aware I/O device scheduling algorithms based on the preemptive periodic task model: Energy-Efficient Device Scheduling (EEDS) and Energy-Efficient Device Scheduling with Non-preemptible Resources (EEDS_NR). The EEDS algorithm keeps track of device slack for devices and performs device power state transitions to save energy, without jeopardizing temporal correctness. Although EEDS can achieve excellent energy conservation, it can only support fully preemptive system. The EEDS_NR algorithm generalize EEDS to support non-preemptive shared critical regions. Next, the trade-off between I/O-based energy conservation and processor-based energy conservation is studied. Dynamic Voltage Scaling (DVS)-based scheduling algorithms can effectively reduce the processor energy consumption at the cost of increased execution time, which in turn increases the I/O device standby energy consumption. On the other hand, I/O-based Dynamic Power Management (DPM) techniques save device energy by aggressively reducing the time that devices are active, which requires the highest processor speed. Therefore, DVS alone or DPM alone may not achieve the same level of energy conservation that a scheduling algorithm considering both can achieve. To this end, we introduce and evaluate the System-wide Energy-Aware EDF (SYS_EDF) algorithm, which integrates device scheduling and processor voltage scaling to reduce the overall system energy consumption. In summary, this dissertation discusses the design, the theoretical correctness, and the evaluation of a set of energy-efficient scheduling algorithms for real-time systems.
A novel neural network analysis method applied to biological neural networks
Authors: John S. Conery, Shawn R. Lockery
Venue:  (2006)

This thesis makes two major contributions: it introduces a novel method for analysis of artificial neural networks and provides new models of the nematode Caenorhabditis elegans nervous system. The analysis method extracts neural network motifs, or subnetworks of recurring neuronal function, from optimized neural networks. The method first creates models for each neuron relating network stimulus to neuronal response, then clusters the model parameters, and finally combines the neurons into multi-neuron motifs based on their cluster category. To infer biological function, this analysis method was applied to neural networks optimized to reproduce C. elegans behavior, which converged upon a small number of motifs. This allowed both a quantitative exploration of network function as well as discovery of larger motifs. Neural network models of C. elegans anatomical connectivity were optimized to reproduce two C. elegans behaviors: chemotaxis (orientation towards a maximum chemical attractant concentration) and thermotaxis (orientation towards a set temperature). Three chemotaxis motifs were identified. Experimental evidence suggests that chemotaxis is driven by a differentiator motif with two important features. The first feature was a fast, excitatory pathway in parallel with one or more slow, inhibitory pathways. The second feature was inhibitory feedback on all self-connections and recurrent loops, which regulates neuronal response. Six thermotaxis motifs were identified. Every motif consisted of two circuits, each a previously discovered chemotaxis motif with most having a dedicated sensory neuron. One circuit was thermophilic (heat-seeking) and the other was cryophilic (cold-seeking). Experimental evidence suggests that the cryophilic circuit is a differentiator motif and the thermophilic circuit functions by klinokinesis.
Programming of PIC Micro-Controller for Power Factor Correction
Authors: Nader Barsoum
Venue: Proceedings of the First Asia International Conference on Modelling & Simulation (2007)

In recent years, the power quality of the AC system has become a great concern due to the rapidly increased numbers of electronic equipment, power electronics and high voltage power system. In order to reduce harmonic contamination in power lines and improve transmission efficiency, power factor correction research became a hot topic. Many control methods for the Power Factor Correction (PFC) were proposed. This paper describes the design and development of a three-phase power factor corrector using PIC (Programmable Interface Circuit) micro-controlling chip. This involves sensing and measuring the power factor value from the load using PIC and sensors, then using proper algorithm to determine and trigger sufficient switching capacitors in order to compensate excessive reactive components, thus withdraw PF near to unity; as a result acquires higher efficiency and better quality AC output. Various power factor correction methods will also be discussed upon their applications in a specific sections.
Crossing Graphs as Joins of Graphs and Cartesian Products of Median Graphs
Authors: Bos&caron;tjan Bres&caron;ar, Sandi Klavz&#x016F;ar
Venue: SIAM Journal on Discrete Mathematics (2007)

For a partial cube $G$ its crossing graph $G^\#$ is the graph whose vertices are the &Thgr;-classes of $G$, two classes being adjacent if they cross on some cycle in $G$. The following problem posed in [S. Klavz&caron;ar and H. M. Mulder, SIAM J. Discrete Math., 15 (2002), pp. 235-251, Problem 7.1] is considered: What can be said about the partial cube $G$ if $G^\#$ is the join $A\oplus B$ of graphs $A$ and $B$ with at least one edge? It is proved that for arbitrary graphs $A$ and $B$, where at least one of them contains an edge, there exists a Cartesian prime partial cube $G$ such that $G^\# = A\oplus B$. On the other hand, if $G$ is a median graph, then $G^\# = A\oplus B$ if and only if $G=H\,\square\, K$, where $H^\# = A$ and $K^\# = B$. Along the way some new facts about partial cubes are obtained; for instance, a bipartite graph of radius 2 is a partial cube if and only if it is $K_{2,3}$-free.
Two-stage approach for pose invariant face recognition
Authors: E. Demir
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 04 (2000)

In this work pose-invariant face recognition is attempted using a two-stage approach. In the first stage, the orientation of the face is recognized, and in the second stage, the face is recognized among a subset of faces with the same orientation in the training set. We have generated our own database and tried several different techniques for pose invariant face recognition. We have used both linear techniques such as principal component analysis (PCA) and linear discriminant analysis (LDA) and unsupervised clustering techniques such as C-means and fuzzy C-means. The classification algorithms used with all of these techniques are nearest mean and k-nearest neighbor (k-NN). This work presents a comparison of these techniques on our database. With all techniques, it is observed that the recognition performance is enhanced when view information is incorporated as a preliminary step.
Robust talker-independent audio document retrieval
Authors: G. J. F. Jones, J. T. Foote, K. Spark Jones, S. J. Young
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

The goal of the video mail retrieval (VMR) project is to integrate state-of-the-art document retrieval methods with speech recognition to yield a robust and efficient retrieval system. The work presented extends VMR towards an open-vocabulary, talker-independent system for retrieving spontaneously-spoken audio and video messages. We present results showing successful retrieval using a standard large-vocabulary (LV) recogniser, despite the lack of a matched language model and vocabulary. We further show that integrating a LV recogniser with conventional word spotting (WS) gives more robust retrieval performance than either method alone. This paper gives details of the message archive used, the speech recognition methodologies, the information retrieval methods, and experimental results.
JMAS: a java-based mobile actor system for distributed parallel computation
Authors: Legand L. Burge, K. M. George
Venue: Proceedings of the 5th conference on USENIX Conference on Object-Oriented Technologies & Systems - Volume 5 (1999)

JMAS is a prototype network computing infrastructure based on mobile actors [10] using Java technology. JMAS requires a programming style different from commonly used approaches to distributed computing. JMAS allows a programmer to create mobile actors, initialize their behaviors, and send them messages using constructs provided by the JMAS Mobile Actor API. Applications are decomposed by the programmer into small, self-contained sub-computations and distributed among a virtual network of Distributed Run-Time Managers (D-RTM); which execute and manage all mobile computations. This system is well suited for course grain computations for network computing clusters. Performance evaluation is done using two benchmarks: a Mersenne Prime Application, and the Traveling Salesman Problem.
Color LinesView: AnApproach toVisualization of Families of Function Graphs
Authors: Kresimir Matkovic, Denis Gracanin, Zoltan Konyha, Helwig Hauser
Venue: Proceedings of the 11th International Conference Information Visualization (2007)

Data sets often include information that can be represented as a mapping that describes how a dependent variable depends on an independent variable. Such a mapping, usually represented as a function graph, can be parameterized to provide a family of function graphs. The challenge is how to efficiently aggregate individual function graph views to represent the whole family and allow visual analysis and search for patterns. We propose a novel view, called the color lines view, which provides a two dimensional, rectangular view where each line represents a single function graph. The points on the line correspond to values of the independent variable. The point colors represent the value of the dependent variable. The lines, placed next to each other in parallel, show a family of function graphs. The color lines view offers sorting and brushing features which support visual analysis procedures that are difficult to perform with previously existing views.
Machine-learning-based transformation of passive japanese sentences into active by separating training data into each input particle
Authors: Masaki Murata, Tamotsu Shirado, Toshiyuki Kanamaru, Hitoshi Isahara
Venue: Proceedings of the COLING/ACL on Main conference poster sessions (2006)

We developed a new method of transforming Japanese case particles when transforming Japanese passive sentences into active sentences. It separates training data into each input particle and uses machine learning for each particle. We also used numerous rich features for learning. Our method obtained a high rate of accuracy (94.30%). In contrast, a method that did not separate training data for any input particles obtained a lower rate of accuracy (92.00%). In addition, a method that did not have many rich features for learning used in a previous study (Murata and Isahara, 2003) obtained a much lower accuracy rate (89.77%). We confirmed that these improvements were significant through a statistical test. We also conducted experiments utilizing traditional methods using verb dictionaries and manually prepared heuristic rules and confirmed that our method obtained much higher accuracy rates than traditional methods.
Finding a Guard that Sees Most and a Shop that Sells Most
Authors: Otfried Cheong, Alon Efrat, Sariel Har-Peled
Venue: Discrete Computational Geometry (2007)

We present a near-quadratic time algorithm that computes a point inside a simple polygon P in the plane having approximately the largest visibility polygon inside P, and a near-linear time algorithm for finding the point that will have approximately the largest Voronoi region when added to an n-point set in the plane. We apply the same technique to find the translation that approximately maximizes the area of intersection of two polygonal regions in near-quadratic time, and the rigid motion doing so in near-cubic time.
Maximum margin clustering made practical
Authors: Kai Zhang, Ivor W. Tsang, James T. Kwok
Venue: Proceedings of the 24th international conference on Machine learning (2007)

Maximum margin clustering (MMC) is a recent large margin unsupervised learning approach that has often outperformed conventional clustering methods. Computationally, it involves non-convex optimization and has to be relaxed to different semidefinite programs (SDP). However, SDP solvers are computationally very expensive and only small data sets can be handled by MMC so far. To make MMC more practical, we avoid SDP relaxations and propose in this paper an efficient approach that performs alternating optimization directly on the original non-convex problem. A key step to avoid premature convergence is on the use of SVR with the Laplacian loss, instead of SVM with the hinge loss, in the inner optimization subproblem. Experiments on a number of synthetic and real-world data sets demonstrate that the proposed approach is often more accurate, much faster and can handle much larger data sets.
On the restricted forwarding index problem in communication networks
Authors: Min Xu, Xujin Chen, Xiaodong Hu
Venue: Computers Mathematics with Applications (2007)

In a communication network it is desirable that all pairs of nodes can exchange messages at the same time. But under the capacity constraints on nodes or links this desired property may not be satisfied; only some node pairs can communicate with each other while the rest have to be blocked. A natural question is what is the maximum number of node pairs that can communicate synchronously with the load restriction? In this paper, we first show that the problem is NP-complete. Then we present two approximation algorithms for the problems under the node load constraint and the link load constraint, respectively.
A new inverse filter criterion for blind deconvolution of spiky signals using Gaussian mixtures
Authors: I. Santamaria-Caballero
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

This paper presents a new Bussgang-type technique for blind deconvolution of spiky signals. Based on a Gaussian mixture model for the spiky signal, the method obtains a deconvolution filter and a zero-memory nonlinearity to estimate the signal. A new updating procedure for the mixture parameters (and, therefore, for the nonlinear estimator) is included in the algorithm: it allows to apply the algorithm without any prior knowledge about the signal and noise. A simulation example illustrates the performance of the proposed method.