ppxscal/embedding_network huggingface dataset:
Adaptive location update area design for wireless cellular networks under 2D Markov walk model
Authors: Jun Zheng, Yan Zhang, Ling Wang, Jinlin Chen
Venue: Computer Communications (2007)

In wireless cellular networks, location management operation expends the limited wireless resources to keep track the location information of a mobile terminal. Various dynamic location update (LU) schemes have been proposed to improve the efficiency of location management. However, most of them only work for certain mobility patterns. In this paper, we propose a new scheme that the LU area is adaptively designed according to the mobility pattern and traffic parameters. The 2D Markov walk is used as the mobility model which describes a broad class of mobility patterns. A recursive algorithm is developed to compute the location management cost of a general LU area shape. Due to the high computational complexity of the adaptive LU area design problem, we use an iterative greedy heuristic algorithm to find an approximation solution of the problem efficiently. The effects of the mobility patterns and traffic parameters on the designed LU area shape are investigated. Experimental results show that the LU area designed by the heuristic algorithm can adaptively change according to the given mobility pattern and traffic parameters. Compared with some existing dynamic LU schemes, the proposed adaptive LU scheme is more flexible and efficient for location management.
Texture Gradients and Perceptual Constancy under Haptic Exploration
Authors: Barry Hughes, Jin Wang, Daryan Rosic, Katie Palmer
Venue: Proceedings of the Second Joint EuroHaptics Conference and Symposium on Haptic Interfaces for Virtual Environment and Teleoperator Systems (2007)

Participants perceive a distal surface texture to be of a certain roughness despite being explored in different ways: by active or passive touch or at different speeds. Understanding the basis and extent of this roughness constancy is an important theoretical goal. The literature suggests that it may stem from how one class of cutaneous afferents codes texture element spacings. In different experiments using raised dot surfaces, we investigated participants' abilities to discriminate spatial density gradients of different directions and magnitudes. This was done under conditions where fingers changed and where performance over extended practice could be observed. The data confirm that perceptual constancy is a feature of haptic texture perception but we identify a subtle bias in perception and we find evidence that practice, even without feedback as to accuracy, can enable even subtle spatial changes to be perceived. We consider these data in terms of models of haptic texture perception and perceptual learning.
Driving the intelligent testbanch: are we there yet?
Authors: H. D. Foster
Venue: Proceedings of the High-Level Design Validation and Test Workshop, 2004. Ninth IEEE International (2004)

In this paper we present techniques for comparison between behavioral level and register transfer level (RTL) design descriptions by mapping the designs into virtual controllers and virtual datapaths. We also discuss about how the equivalence between behavioral level and RTL designs can be defined precisely using the proposed "attribute statements" in an interactive fashion. Implementation issues as well as considerations on real life industrial design examples are presented as well.
BulkSC: bulk enforcement of sequential consistency
Authors: Luis Ceze, James Tuck, Pablo Montesinos, Josep Torrellas
Venue: ACM SIGARCH Computer Architecture News (2007)

While Sequential Consistency (SC) is the most intuitive memory consistency model and the one most programmers likely assume, current multiprocessors do not support it. Instead, they support more relaxed models that deliver high performance. SC implementations are considered either too slow or -- when they can match the performance of relaxed models -- too difficult to implement. In this paper, we propose Bulk Enforcement of SC (BulkSC), anovel way of providing SC that is simple to implement and offers performance comparable to Release Consistency (RC). The idea is to dynamically group sets of consecutive instructions into chunks that appear to execute atomically and in isolation. The hardware enforces SC at the coarse grain of chunks which, to the program, appears as providing SC at the individual memory access level. BulkSC keeps the implementation simple by largely decoupling memory consistency enforcement from processor structures. Moreover, it delivers high performance by enabling full memory access reordering and overlapping within chunks and across chunks. We describe a complete system architecture that supports BulkSC and show that it delivers performance comparable to RC.
Sample path moderate deviations for the cumulative fluid produced by an increasing number of exponential on-off sources
Authors: Kurt Majewski
Venue: Queueing Systems: Theory and Applications (2007)

We consider the superposition of the cumulative fluid generated by an increasing number of stationary iid on-off sources with exponential iid on- and off-time distributions. We establish a family of sample path large deviation principles when the fluid is centered and then scaled with a factor between the inverse of the number of sources and its square root. The common rate function in this family also appears in a large deviation principle for the tail probabilities of an integrated Ornstein---Uhlenbeck process. When the produced fluid is centered and scaled with the square root of the inverse of the number of sources it converges to this integrated Ornstein---Uhlenbeck process in distribution. We discuss several representations of the rate function. We apply the results to queueing systems loaded with on-off traffic and approaching critical loading.
High performance noise reduction for biomedical multidimensional data
Authors: S. Tabik, E. M. Garzón, I. García, J. J. Fernández
Venue: Digital Signal Processing (2007)

Anisotropic nonlinear diffusion (AND) is one of the most powerful noise reduction techniques in the field of image processing. This method is based on a partial differential equation (PDE) tightly coupled with a massive set of eigensystems. Denoising large 3D images in biomedicine and structural cellular biology by AND is extremely expensive from a computational point of view, with huge memory needs. In this work, high performance computing techniques have been applied to AND. An strategy for optimal memory usage has been designed, which has allowed a remarkable reduction of the memory requirements. Parallel implementations of AND have been developed with special focus on clusters of symmetric multiprocessors (SMPs), currently a dominant platform in high performance computing. Different programming models have been used for the parallelization of AND: (1) Message-passing paradigm using MPI and (2) a hybrid paradigm that uses message passing among nodes plus the shared address space paradigm between the processors within the nodes. The parallel approaches have been evaluated on a cluster of dual-Xeon nodes, a representative example of clusters of SMPs. The conclusion drawn is that the hybrid approach is the most suitable for the parallelization of AND for this kind of computing platforms.
Glitch-Aware Pattern Generation and Optimization Framework for Power-Safe Scan Test
Authors: V. R. Devanathan, C. P. Ravikumar, V. Kamakoti
Venue: Proceedings of the 25th IEEE VLSI Test Symmposium (2007)

Excessive dynamic voltage drop in the power supply rails during test mode is known to result in false failures and impact yield when testing devices that use low-cost wire-bond packages. Identifying and debugging such test failures is a complex and effort-intensive process, especially when scan compression is involved. From a design cycle-time view point, it is best to avoid this problem by generating "power-safe" scan patterns. The generation of power-safe patterns must take into consideration the DFT architecture, physical design, timing and power constraints. In this paper, we propose such a framework and show experimental results on some benchmark circuits. Our framework can address a non-uniform power grid and region-based power constraints. We show that glitching activity on nodes must be considered in order to correctly handle constraints on instantaneous peak power. Our framework includes a power profiler that can analyze a pattern source for violations and a PODEM-based pattern generation engine for generating power-safe patterns.
Use of intelligent system techniques for storage and retrieval of biometrics data with application to personal identification
Authors: Jane Jia You
Venue:  (2006)

Biometrics (or biometric recognition) refers to the technology recognizing individuals based on their physiological and/or behavioral characteristics. It has advantages over token-based and knowledge-based personal recognition technologies. The important biometric systems including face, fingerprint, iris and palmprint are in fact image-based recognition systems. For identification purpose, these systems can be regarded as Content-Based Image Retrieval (CBIR) systems. The storage and retrieval requirements of image-based biometric systems, nevertheless, make them to be a special type of CBIR systems. First, personal physiological characteristics cannot be properly described by traditional text-based methods. Second, there are no generally accepted indexing and classification methods being used in common biometrics systems. Third, the captured biometric images always contain noise and variations due to change in capture environments and user habit. Fourth, in real world applications, they should be scalable for large databases and should provide relevant security mechanisms. Finally, they may make its own decision or provide help to make decision on whether a claim is accepted or rejected. In this research, we focus on the storage and retrieval of some image-based biometric systems supported by personal physiological characteristics. We have considered the storage and retrieval of biometric templates as an application of target and category search in narrow domain. We have incorporated some primitive visual-based image features including texture, lines and points, as content descriptors of biometric images. Various intelligent system techniques, e.g. machine learning and fuzzy, have been used to extract and represent the visual-based image features of palmprint and face images. We have developed methods that can compactly represent and effectively retrieve palmprint and face templates and we are the first to consider retrieval in large palmprint databases. We originally identify and study three design issues of cancelable biometrics, which is a security and privacy enhancement method proposed for template protection. We are among the first to consider the three issues integrally when designing and evaluating cancelable biometrics.
ArchVoc - Towards an Ontology for Software Architecture
Authors: Lenin T. Babu, Seetha M. Ramaiah, T. V. Prabhakar, D Rambabu
Venue: Proceedings of the 29th International Conference on Software Engineering Workshops (2007)

Knowledge management of any domain requires controlled vocabularies, taxonomies, thesauri, ontologies, concept maps and other such artifacts. This paper describes an effort to identify the major concepts in software architecture that can go into such meta knowledge. The concept terms are identified through two different techniques (1) manually, through backof- the-book index of some of the major texts in Software Architecture (2) through a semi-automatic technique by parsing the Wikipedia pages. Only generic architecture knowledge is considered. Apart from identifying the important concepts of software architecture, we could also see gaps in the software architecture content in the Wikipedia.
Porting and maintaining with X and Motif: a retrospective view
Authors: Paul Davey
Venue: Proceedings of the USENIX Applications Development Symposium Proceedings on USENIX Applications Development Symposium Proceedings (1994)

In 1989 I accepted a job with IXI Ltd. in Cambridge, England, a small software house specializing in the X Window System. The flagship product, X.desktop, was then moving into its third major version (2.0), the first based on Motif. Initially IXI was establishing X.desktop, and the concept of desktop software for Unix and X, but as time went the initial issues of rapid portability and flexibility, were replaced by other factors as the company, market and product all grew larger and more complex. Maturing code, increasing numbers of programmers and staff turnover all played their part in making the management of the ongoing project more and more challenging. When overseeing the porting and maintenance of X.desktop in 1992, I found myself dealing concurrently with three major versions (2.0, 3.0 and 3.5), existing on over 30 platforms (with more than 50 active configurations). After successfully streamlining the porting and maintenance process I was then asked to organize the Motif toolkit team along similar lines in August 1993. This was subtlety different from the X.desktop work since the code originated externally (from the Open Software Foundation), and had to meet open as opposed to proprietary standards. Keen competition in the market providing Motif development libraries on Sun meant that high quality and ease of use was highly important. As with X.desktop a rapid response to customer problems was another important factor in keeping customers satisfied. This talk will examine some of the lessons learned about the development of multiplatform applications and toolkits over the software life cycle of X.desktop. Some additional examples are taken from the work porting and enhancing the Motif toolkit. Although a premier X application X.desktop code was only partly X based, much of it being either Unix system related or just plain data manipulation. The uses (and abuses) of standard Unix software tools such as yacc, lex and SCCS will be illustrated. The parallel development of a problem and bug tracking systems will be described as it resulted in the customized internal tool in use at the end of 1993.
Revisiting a Formal Framework for Modeling Aspects in the Design Phase
Authors: Virginia de Paula, Thais Batista
Venue: Proceedings of the 29th International Conference on Software Engineering Workshops (2007)

Software architecture description languages (ADLs) and formal methods have been successfully used together during the design phase allowing the semantic validation of systems early in the development process. Recently, a lot of Aspect- Oriented ADLs (AO ADLs) have been proposed however, most of them, neglects the modeling of aspect-oriented (AO) concepts using formal specification. In this paper we present AOZCL, an aspect-oriented extension to a formal framework (ZCL) with a built-in ADL. AOZCL supports the formal modeling of aspect-oriented architectures. Besides the linguistic issues, we want to carry out more rigorous analysis of the architecture and their crosscutting concerns. To analyze the components' behavior, ZCL uses state machines. We also present the states machines of components considering aspects to realize the behavioral implications of crosscutting concerns. We use a case study to illustrate the use of AOZCL as an ADL.
Adaptive Algorithm-Based Fault Tolerance for Parallel Computing in Linear Systems
Authors: Javed I. Khan, W. Lin, D. Y. Y. Yun
Venue: Proceedings of the 1994 International Conference on Parallel Processing - Volume 03 (1994)

This paper presents a dynamically adaptive stabilization scheme for parallel matrix computation. The scheme performs automatic error detection and correction through inserting redundant, but concurrent tracer computations within the folds of the regular computation. It also eliminates the costly row interchange used in classical pivoting. A fault-tolerant double wavefront matrix algorithmfor a MIMD array multi-processor with toroidal inter connection has been designed to demonstrate the strength of the proposed scheme. This algorithm can compute: i) matrix inverse ii) solution vector to the linear system and Hi) predetermined linear combination of the solution vector from identical algorithmic framework. This efficient tri-solution algorithm excels most other known methods in parallel performance.
Algorithms for estimating the cluster tree of a density
Authors: Werner Stuetzle
Venue:  (2006)

The goal of clustering is to identify distinct groups in a data set, and assign a group label to each observation. To cast clustering as a statistical problem, we regard the data as an independent and identically distributed sample from some unknown probability density p. We adopt the premise that groups correspond to modes of the density. Our goal then is to find the modes and assign each observation to the "domain of attraction" of a mode. We do this by estimating the cluster tree of the density, a representation of the hierarchical structure of its level sets. Leaves of the cluster tree correspond to modes of the density. An obvious way of estimating the cluster tree of the underlying density p from a sample is to first compute a density estimate p&circ; and then use the cluster tree of p&circ; as an estimate for the cluster tree of p. We first present an algorithm that computes the cluster tree for piecewise constant density estimates. Exact computation of the cluster tree for general density estimates seems infeasible. Our second contribution is a graph-based approach for approximating the cluster tree of any density estimate. A problem with this graph-based approach is that it requires the edge weights of a graph which are not given in closed form but instead are solutions of an optimization problem; the weight of an edge connecting two observations is the minimum of the estimated density along the edge. Our third contribution is an algorithm that exactly implements the graph-based approach for smooth density estimates.
Project based computer-aided engineering applications
Authors: C. G. Jensen
Venue: Proceedings of the 30th Annual Frontiers in Education - Volume 02 (2000)

The Computer-Aided Engineering Applications (Mechanical Engineering 371) course taught at Brigham Young University (BYU) in Provo, Utah (USA), uses sophisticated commercial computer aided engineering (CAE)/computer aided design (CAD)/computer aided manufacturing (CAM) systems to teach advanced modeling, analysis, design and manufacturing skills. Lectures for ME 371 are mathematically based, where the students are taught the mathematics of curves, surfaces, solids, finite element analysis (FEA), mass properties, numerical control (NC) tool paths, etc., but not the graphical user interface (GUI) methods for creating these entities and executing applications. With a combination of mathematical lectures and GUI based laboratory assignments, students are able to fully understand the basic geometric parameters, constraints and relationships prompted by the CAD system. The paper presents a blueprint for teaching the mathematics of high-end CAE/CAD/CAM systems to undergraduates and the development of CAD skills that reinforce the theory presented in lecture.
A variable-length category-based n-gram language model
Authors: T. R. Niesler, P. C. Woodland
Venue: Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01 (1996)

A language model based on word-category n-grams and ambiguous category membership with n increased selectively to trade compactness for performance is presented. The use of categories leads intrinsically to a compact model with the ability to generalise to unseen word sequences, and diminishes the sparseness of the training data, thereby making larger n feasible. The language model implicitly involves a statistical tagging operation, which may be used explicitly to assign category assignments to untagged text. Experiments on the LOB corpus show the optimal model-building strategy to yield improved results with respect to conventional n-gram methods, and when used as a tagger, the model is seen to perform well in relation to a standard benchmark.
Design for a network-based education system that evolves by peer and instructor interaction
Authors: A. J. Surkan
Venue: Proceedings of the 28th Annual Frontiers in Education - Volume 01 (1998)

A framework for a globally-distributed computer network education-delivery system is proposed. Also presented are some structural details of designs to promote the system's continued evolution requiring the generation and reuse of successful teaching and learning items. The system's growth is predicated on the basic idea that learning amongst peers in common or related domains can be most effective when the students are self-paced in contributing and evaluating items to be used simultaneously by others. With this system, item content will finally be delivered by a integration of all the multimedia channels made practically feasible by technology. The system is to facilitate the definition of concept-related clusters for learning items that are appropriate for students interested in solving a variety of classes of problems. Initially, links or bindings among the classes of clusters can be based on classification knowledge that is normally identified in traditional educational systems. Learning items will be accumulated and retained on the basis of statistical performance measures. The knowledge to define item clusters will be embedded in programs written to be intelligent agents. These agents will contain algorithms or methods for dynamically improving cluster definitions. Program systems will accumulate information on each student and on the items. This facilitates the assignment of a grade to each student to indicate his/her level of mastery or ability to perform in each area identified as a cluster center.
Software for systematic and imaginative exploration
Authors: Daryl H. Hepting
Venue: Proceedings of the 6th ACM SIGCHI conference on Creativity cognition (2007)

This paper describes a software system that has been designed to enhance individual creativity. It was once thought that the era of information visualization would empower people and enable a democratization of visual thinking. Today, many barriers to this democratization still exist. The software, called cogito, is designed from the perspective that it is possible, with appropriate support, to meaningfully explore a very large set of alternatives without becoming overwhelmed. This paper discusses the design choices made for the software, the architecture of the system, and the experience gained in a variety of applications.
Defending against hitlist worms using network address space randomization
Authors: S. Antonatos, P. Akritidis, E. P. Markatos, K. G. Anagnostakis
Venue: Computer Networks: The International Journal of Computer and Telecommunications Networking (2007)

Worms are self-replicating malicious programs that represent a major security threat for the Internet, as they can infect and damage a large number of vulnerable hosts at timescales where human responses are unlikely to be effective. Sophisticated worms that use precomputed hitlists of vulnerable targets are especially hard to contain, since they are harder to detect, and spread at rates where even automated defenses may not be able to react in a timely fashion. This paper examines a new proactive defense mechanism called Network Address Space Randomization (NASR) whose objective is to harden networks specifically against hitlist worms. The idea behind NASR is that hitlist information could be rendered stale if nodes are forced to frequently change their IP addresses. NASR limits or slows down hitlist worms and forces them to exhibit features that make them easier to contain at the perimeter. We explore the design space for NASR and present a prototype implementation as well as experiments examining the effectiveness and limitations of the approach.