ppxscal/embedding_network huggingface dataset:
Processing of 3D DIC microscopy images for data visualization
Authors: P. A. Feineigle
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 04 (1996)

Differential interference contrast (DIC) microscopy is a popular method for studying the three dimensional structure of living cells. Currently, no volume rendering tools exist which support visualisation of 3D DIC data. The authors develop a transformation method which removes the differential appearance of DIC imager, producing data which is suitable for volume rendering, and compare this method to an edge-enhancing approach based on a variance filter.
Accurate prediction of power consumption in sensor networks
Authors: O. Landsiedel, K. Wehrle, S. Gotz
Venue: Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors (2005)

Energy consumption is a crucial characteristic of sensor networks and their applications as sensor nodes are commonly battery-driven. Although recent research focuses strongly on energy-aware applications and operating systems, energy consumption is still a limiting factor. Once sensor nodes are deployed, it is challenging and sometimes even impossible to change batteries. As a result, erroneous lifetime prediction causes high costs and may render a sensor network, useless before its purpose is fulfilled. In this paper, we present AEON (accurate prediction of power consumption), a novel evaluation tool to quantitatively predict energy consumption of sensor nodes and whole sensor networks. Our energy model, based on measurements of node current draw and the execution of real code, enables accurate prediction of the actual energy consumption of sensor nodes. Consequently, it prevents erroneous assumptions on node and network lifetime. Moreover, our detailed energy model allows us to compare different low power and energy aware approaches in terms of energy efficiency. Thus, it enables a highly precise estimation of the overall lifetime of a sensor network.
New approaches for clustering high dimensional data
Authors: Wei Wang
Venue:  (2006)

Clustering is one of the most effective methods for analyzing datasets that contain a large number of objects with numerous attributes. Clustering seeks to identify groups, or clusters, of similar objects. In low dimensional space, the similarity between objects is often evaluated by summing the difference across all of their attributes. High dimensional data, however, may contain irrelevant attributes which mask the existence of clusters. The discovery of groups of objects that are highly similar within some subsets of relevant attributes becomes an important but challenging task. My thesis focuses on various models and algorithms for this task. We first present a flexible clustering model, namely OP-Cluster (Order Preserving Cluster). Under this model, two objects are similar on a subset of attributes if the values of these two objects induce the same relative ordering of these attributes. OP-Clustering algorithm has demonstrated to be useful to identify co-regulated genes in gene expression data. We also propose a semi-supervised approach to discover biologically meaningful OP-Clusters by incorporating existing gene function classifications into the clustering process. This semi-supervised algorithm yields only OP-clusters that are significantly enriched by genes from specific functional categories. Real datasets are often noisy. We propose a noise-tolerant clustering algorithm for mining frequently occurring itemsets. This algorithm is called approximate frequent itemsets (AFI). Both the theoretical and experimental results demonstrate that our AFI mining algorithm has higher recoverability of real clusters than any other existing itemset mining approaches. Pair-wise dissimilarities are often derived from original data to reduce the complexities of high dimensional data. Traditional clustering algorithms taking pair-wise dissimilarities as input often generate disjoint clusters from pair-wise dissimilarities. It is well known that the classification model represented by disjoint clusters is inconsistent with many real classifications, such gene function classifications. We develop a Poclustering algorithm, which generates overlapping clusters from pair-wise dissimilarities. We prove that by allowing overlapping clusters, Poclustering fully preserves the information of any dissimilarity matrices while traditional partitioning algorithms may cause significant information loss.
Graph Treewidth and Geometric Thickness Parameters
Authors: Vida Dujmovic, David R. Wood
Venue: Discrete Computational Geometry (2007)

Consider a drawing of a graph G in the plane such that crossing edges are coloured differently. The minimum number of colours, taken over all drawings of G, is the classical graph parameter thickness. By restricting the edges to be straight, we obtain the geometric thickness. By additionally restricting the vertices to be in convex position, we obtain the book thickness. This paper studies the relationship between these parameters and treewidth. Our first main result states that for graphs of treewidth k, the maximum thickness and the maximum geometric thickness both equal &#x2308;k/2&#x2309;. This says that the lower bound for thickness can be matched by an upper bound, even in the more restrictive geometric setting. Our second main result states that for graphs of treewidth k, the maximum book thickness equals k if k &#x2264; 2 and equals k + 1 if k &#x2265; 3. This refutes a conjecture of Ganley and Heath [Discrete Appl. Math. 109(3):215-221, 2001]. Analogous results are proved for outerthickness, arboricity, and star-arboricity.
Flexible packet filtering: providing a rich toolbox
Authors: Kurt J. Lidl, Deborah G. Lidl, Paul R. Borman
Venue: Proceedings of the BSD Conference 2002 on BSD Conference (2002)

The BSD/OS IPFW packet filtering system is a well engineered, flexible kernel framework for filtering (accepting, rejecting, logging, or modifying) IP packets. IPFW uses the well understood, widely available Berkeley Packet Filter (BPF) system as the basis of its packet matching abilities, and extends BPF in several straightforward areas. Since the first implementation of IPFW, the system has been enhanced several times to support additional functions, such as rate filtering, network address translation (NAT), and traffic flow monitoring. This paper examines the motivation behind IPFW and the design of the system. Comparisons with some contemporary packet filtering systems are provided. Potential future enhancements for the IPFW system are discussed.
A class of possibilistic portfolio selection model with interval coefficients and its application
Authors: Jun Li, Jiuping Xu
Venue: Fuzzy Optimization and Decision Making (2007)

Because of the existence of non-stochastic factors in stock markets, several possibilistic portfolio selection models have been proposed, where the expected return rates of securities are considered as fuzzy variables with possibilistic distributions. This paper deals with a possibilistic portfolio selection model with interval center values. By using modality approach and goal attainment approach, it is converted into a nonlinear goal programming problem. Moreover, a genetic algorithm is designed to obtain a satisfactory solution to the possibilistic portfolio selection model under complicated constraints. Finally, a numerical example based on real world data is also provided to illustrate the effectiveness of the genetic algorithm.
Modeling Device Driver Effects in Real-Time Schedulability Analysis: Study of a Network Driver
Authors: Mark Lewandowski, Mark J. Stanovich, Theodore P. Baker, Kartik Gopalan, An-I Andy Wang
Venue: Proceedings of the 13th IEEE Real Time and Embedded Technology and Applications Symposium (2007)

Device drivers are integral components of operating systems. The computational workloads imposed by device drivers tend to be aperiodic and unpredictable because they are triggered in response to events that occur in the device, and may arbitrarily block or preempt other time-critical tasks. This characteristic poses significant challenges in real-time systems, where schedulability analysis is essential to guarantee system-wide timing constraints. At the same time, device driver workloads cannot be ignored. Demand-based schedulability analysis is a technique that has been successful in validating the timing constraints in both single and multiprocessor systems. In this paper we present two approaches to demand-based schedulability analysis of systems that include device drivers. First, we derive load-bound functions using empirical measurement techniques. Second, we modify the scheduling of network device driver tasks in Linux to implement an algorithm for which a load-bound function can be derived analytically. We demonstrate the practicality of our approach through detailed experiments with a network device under Linux. Our results show that, even though the network device driver does not conform to conventional periodic or sporadic task models, it can be successfully modeled using hyperbolic load-bound functions that are fitted to empirical performance measurements.
An adaptive multi-rate speech coder for digital cellular telephony
Authors: E. Paksoy
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 01 (1999)

We have developed an adaptive multi-rate (AMR) speech coder designed to operate under the GSM digital cellular full rate (22.8 kb/s) and half rate (11.4 kb/s) channels and to maintain high quality in the presence of highly varying background noise and channel conditions. Within each total rate, several codec modes with different source/channel bit rate allocations are used. The speech coders in each codec mode are based on the CELP algorithm operating at rates ranging from 11.85 kb/s down to 5.15 kb/s, where the lowest rate coder is a source controlled multi-modal speech coder. The decoders monitor the channel quality at both ends of the wireless link using the soft values for the received bits and assist the base station in selecting the codec mode that is appropriate for a given channel condition. The coder was submitted to the GSM AMR standardization competition and met the qualification requirements in an independent formal MOS test.
Scouts, promoters, and connectors: The roles of ratings in nearest-neighbor collaborative filtering
Authors: Bharath Kumar Mohan, Benjamin J. Keller, Naren Ramakrishnan
Venue: ACM Transactions on the Web (TWEB) (2007)

Recommender systems aggregate individual user ratings into predictions of products or services that might interest visitors. The quality of this aggregation process crucially affects the user experience and hence the effectiveness of recommenders in e-commerce. We present a characterization of nearest-neighbor collaborative filtering that allows us to disaggregate global recommender performance measures into contributions made by each individual rating. In particular, we formulate three roles---scouts, promoters, and connectors---that capture how users receive recommendations, how items get recommended, and how ratings of these two types are themselves connected, respectively. These roles find direct uses in improving recommendations for users, in better targeting of items and, most importantly, in helping monitor the health of the system as a whole. For instance, they can be used to track the evolution of neighborhoods, to identify rating subspaces that do not contribute (or contribute negatively) to system performance, to enumerate users who are in danger of leaving, and to assess the susceptibility of the system to attacks such as shilling. We argue that the three rating roles presented here provide broad primitives to manage a recommender system and its community.
Reducing Program Comprehension Effort in Evolving Software by Recognizing Feature Implementation Convergence
Authors: Jay Kothari, Trip Denton, Ali Shokoufandeh, Spiros Mancoridis
Venue: Proceedings of the 15th IEEE International Conference on Program Comprehension (2007)

The implementations of software features evolve as an application matures. We define a measure of feature implementation overlap that determines how similar features are in their execution by examining their call graphs. We consider how this measure changes over time, and evaluate the hypothesis that over time and subsequent versions of a software application, the implementations of semantically similar features converge. As the features of an application converge in their implementation, we are able to more effectively determine groups of semantically similar features and to reduce the cost of program comprehension by selecting few key features that give an overview of the system. We present a case study analyzing the features of the Jext, Firefox, and Gaim software systems to support our hypothesis.
Universally Composable Three-Party Key Distribution
Authors: TingMao Chang, YueFei Zhu, Jin Zhou, YaJuan Zhang
Venue: Proceedings of the The Second International Conference on Availability, Reliability and Security (2007)

In this paper, we formulate and realize a definition of security for three-party key distribution within the universally composable (UC) framework. That is, an appropriate ideal functionality that captures the basic security requirements of three-party key distribution is formulated. We show that UC definition of security for three-party key distribution protocol is strictly more stringent than a previous definition of security which is termed AKE-security. Finally, we present a real-life protocol that securely realizes the formulated ideal functionality with respect to non-adaptive adversaries.
A cognitive-based approach to improve distributed requirements elicitation processes
Authors: G. N. Aranda, A. Vizcaino, A. Cechich, M. Piattini
Venue: Proceedings of the Fourth IEEE International Conference on Cognitive Informatics (2005)

Technology used by virtual teams during a distributed requirement elicitation process is usually selected according to predetermined business politics, personal criteria of managers, etc. However, when technology is not appropriate for all members of the team, it is possible that some stakeholders would not feel completely comfortable, and hence influence their participation negatively. In order to mitigate these effects during a distributed requirements elicitation process, we propose a model based on psychology theories to identify suitable elicitation techniques according to cognitive aspects of most stakeholders in the group.
Real-time scheduling for pipelined execution of data flow graphs on a realistic multiprocessor architecture
Authors: J. Jonsson
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 06 (1996)

Multimedia and digital signal processing applications have swiftly emerged as important areas for embedded computer systems. Therefore, it is imperative that computer architectures are devised that can cope with the increased burden of processing power implied by these applications. We present a heuristic static real-time scheduling method called real time data flow (RTDF), for mapping data flow graphs onto fixed-size homogeneous multiprocessor architectures. The primary objective of RTDF is to minimize the iteration period of an application. Several other methods with this goal have been proposed in particular in the digital signal processing domain. Similar to many of these, RTDF attempts to minimize the iteration period by exploiting pipelining parallelism. In contrast, however; RTDF assumes an architecture model where communication network characteristics such as message service capacity, communication distance and communication link contention are modeled in a realistic fashion. Therefore, with the aid of RTDF, systems can be designed that support applications with high sample rates without having to resort to dedicated architectures. We show experimentally that RTDF achieves near-optimal iteration periods when communication cost is negligible and that communication overhead only affects the iteration periods of graphs with loops.
Least-mean-log-likelihood adaptive algorithm in single-layer perceptron based communication channel equalisation
Authors: Changjing Shang
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 03 (1996)

This paper presents a novel approach to adapting the weights of single-layer perceptron based communication channel equalisers, using the log-likelihood cost function and the resulting least-mean-log-likelihood adaptive algorithm. It provides promising theoretical and experimental results, illustrating that developing equalisers following this approach allows faster convergence, lower estimation error and better bit error rate performance in comparison with the traditional Rosenblatt (1962) and back-propagation algorithms.
Confining root programs with domain and type enforcement (DTE)
Authors: Kenneth M. Walker, Daniel F. Sterne, M. Lee Badger, Michael J. Petkac, David L. Sherman, Karen A. Oostendorp
Venue: Proceedings of the 6th conference on USENIX Security Symposium, Focusing on Applications of Cryptography - Volume 6 (1996)

The pervasive use of the root privilege is a central problem for UNIX security because an attacker who subverts a single root program gains complete control over a computing system. Domain and type enforcement (DTE) is a strong, configurable operating system access control technology that can minimize the damage root programs can cause if subverted. DTE does this by preventing groups of root programs from accessing critical files in inappropriate access modes. This paper illustrates how a DTE-enhanced UNIX prototype, driven by simple, machine-interpretable DTE policies, can provide strong protection against specific classes of attacks by malicious programs that gain root privilege. We present a sequence of policy components that protect system binaries against Rootkit, a widely-used hacker toolkit, and protect password, system log, user, and device special files against other root-based attacks. Tradeoffs among DTE policy complexity, scope of protection, and other factors are discussed.
Example-based single document image super-resolution: a global MAP approach with outlier rejection
Authors: Dmitry Datsenko, Michael Elad
Venue: Multidimensional Systems and Signal Processing (2007)

Regularization plays a vital role in inverse problems, and especially in ill-posed ones. Along with classical regularization techniques based on smoothness, entropy, and sparsity, an emerging powerful regularization is one that leans on image examples. In this paper, we propose an efficient scheme for using image examples as driving a powerful regularization, applied to the image scale-up (super-resolution) problem. In this work, we target specifically scanned documents containing written text, graphics, and equations. Our algorithm starts by assigning per each location in the degraded image several candidate high-quality patches. Those are found as the nearest-neighbors (NN) in an image-database that contains pairs of corresponding low- and high-quality image patches. The found examples are used for the definition of an image prior expression, merged into a global MAP penalty function. We use this penalty function both for rejecting some of the irrelevant outlier examples, and then for reconstructing the desired image. We demonstrate our algorithm on several scanned documents with promising results.
A new class of affine higher order time-frequency representations
Authors: R. L. Murray
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 03 (1999)

We propose a new class of affine higher order time-frequency representations (HO-TFRs) unifying HO-TFRs which satisfy the desirable properties of scale covariance and time-shift covariance. This new class extends to higher order (N>2) the affine class of quadratic (N=2) time-frequency representations. In this paper, we provide five alternative formulations of the class in terms of multi-dimensional smoothing kernels. We discuss important class members, including the new higher order scalogram that is related to the wavelet transform. We also list additional desirable properties and derive the associated kernel constraints. Finally, we consider a subclass of affine HO-TFRs that intersects with a Cohen's class of time and frequency shift covariant HO-TFRs. A formulation for HO-TFRs satisfying three covariances in this higher order affine-Cohen intersection is derived.
Experiences about ERASMUS: an interchange project
Authors: S. Alonso, M. Bollain, C. Cuvillo, M. C. Fernandez, A. Garcia, E. Santos
Venue: Proceedings of the Frontiers in Education Conference, on 1995. Proceedings., 1995 - Volume 02 (1995)

Describes what the ERASMUS project is, our experiences of it, and a brief statistical survey related to our participation as a host and home institution. The ERASMUS program started in June 1987 and it aims at supporting, promoting and stimulating cooperation among European universities. The universities participating in ERASMUS are financed to exchange teaching staff, exchange students and develop joint curricula. This program awards grants to students who wish to fulfil part of the requirements for obtaining their degree in a university other than that which they are currently attending. European universities are encouraged to form groups called ICPs (Inter-university Cooperation Programmes) in order to facilitate the coordination and organization job. Each institution is member of a group in which all the members are of the same kind (referred to the study orientation). In the University School of Computer Science of the Universidad Politecnica de Madrid, we consider that ERASMUS brings an excellent opportunity for students to get to know other cultures, work with different groups of people and learn how a "professional" job is done in another country. This is why we try to focus our participation on these three points and why we have chosen the final dissertation project as the subject that students must attend.
On the Use of Fuzzy Modeling in Virtualized Data Center Management
Authors: Jing Xu, Ming Zhao, Jose Fortes, Robert Carpenter, Mazin Yousif
Venue: Proceedings of the Fourth International Conference on Autonomic Computing (2007)

One of the most important goals of data-center management is to reduce cost through efficient use of resources. Virtualization techniques provide the opportunity of carving individual physical servers into multiple virtual containers that can be run and managed separately. A key challenge that comes with virtualization is the simultaneous on-demand provisioning of shared resources to virtual containers and the management of their capacities to meet service quality targets at the least cost. This paper proposes a two-level resource management system with local controllers at the virtual-container level and a global controller at the resource-pool level. Autonomic resource allocation is realized through the interaction of the local and global controllers. A novelty of the controller designs is their use of fuzzy logic to efficiently and robustly deal with the complexity of the virtualized data center and the uncertainties of the dynamically changing workloads. Experimental results obtained through a prototype implementation demonstrate that, for the scenarios under consideration, the proposed resource management system can significantly reduce resource consumption while still achieving application performance targets.