ppxscal/embedding_network huggingface dataset:
A Module System for Isolating Untrusted Software Extensions
Authors: Philip W. L. Fong, Simon A. Orr
Venue: Proceedings of the 22nd Annual Computer Security Applications Conference (2006)

With the recent advent of dynamically extensible software systems, in which software extensions may be dynamically loaded into the address space of a core application to augment its capabilities, there is a growing interest in protection mechanisms that can isolate untrusted software components from a host application. Existing language-based environments such as the JVM and the CLI achieves software isolation by an interposition mechanism known as stack inspection. Expressive as it is, stack inspection is known to lack declarative characterization and is brittle in the face of evolving software configurations. A run-time module system, ISOMOD, is proposed for the Java platform to facilitate software isolation. A core application may create namespaces dynamically and impose arbitrary name visibility policies to control whether a name is visible, to whom it is visible, and in what way it can be accessed. Because ISOMOD exercises name visibility control at load time, loaded code runs at full speed. Furthermore, because ISOMOD access control policies are maintained separately, they evolve independently from core application code. In addition, the ISOMOD policy language provides a declarative means for expressing a very general form of visibility constraints. Not only can the ISOMOD policy language simulate a sizable subset of permissions in the Java 2 security architecture, it does so with policies that are robust to changes in software configurations. The ISOMOD policy language is also expressive enough to completely encode a capability type system known as Discretionary Capability Confinement. In spite of its expressiveness, the ISOMOD policy language admits an efficient implementation strategy. In short, ISOMOD avoids the technical difficulties of interposition by trading off an acceptable level of expressiveness. Name visibility control in the style of ISOMOD is therefore a lightweight alternative to interposition.
Modeling the Behavior of Lurkers in Online Communities Using Intentional Agents
Authors: Yong Du
Venue: Proceedings of the International Conference on Computational Inteligence for Modelling Control and Automation and International Conference on Intelligent Agents Web Technologies and International Commerce (2006)

Lurkers are members of an online community who read but seldom or never post messages. It has been reported that most members of online communities are lurkers. Understanding the reasons of lurking and the strategies of delurking can help the healthy development of online communities, which can potentially promote Internet commerce. This paper applies goal-oriented modeling on the behaviors of lurkers using the i* intentional modeling framework.
Drawing bipartite graphs as anchored maps
Authors: Kazuo Misue
Venue: Proceedings of the 2006 Asia-Pacific Symposium on Information Visualisation - Volume 60 (2006)

A method of drawing anchored maps for bipartite graphs is presented. Suppose that the node set of a bipartite graph is divided into set A and set B. On an anchored map of the bipartite graph, the nodes in A, which are called "anchor nodes," are arranged on the circumference, and the nodes in B, which are called "free nodes," are arranged at suitable positions in relation to the adjacent anchor nodes. This article describes aesthetic criteria that are employed according to the purpose of drawing anchored maps and a method to arrange the anchor nodes so that they satisfy the criteria. The effectiveness of the proposed method is discussed in terms of the aesthetics of drawing results.
"Presemantic" Cognition in Semantic Dementia: Six Deficits in Search of an Explanation
Authors: Karalyn Patterson, Matthew A. Lambon Ralph, Elizabeth Jefferies, Anna Woollams, Roy Jones, John R. Hodges, Timothy T. Rogers
Venue: Journal of Cognitive Neuroscience (2006)

On the basis of a theory about the role of semantic knowledge in the recognition and production of familiar words and objects, we predicted that patients with semantic dementia would reveal a specific pattern of impairment on six different tasks typically considered "pre-" or "non-" semantic: reading aloud, writing to dictation, inflecting verbs, lexical decision, object decision, and delayed copy drawing. The prediction was that all tasks would reveal a frequency-by-typicality interaction, with patients performing especially poorly on lower-frequency items with atypical structure (e.g., words with an atypical spelling-to-sound relationship; objects with an atypical feature for their class, such as the hump on a camel, etc). Of 84 critical observations (14 patients performing 6 tasks), this prediction was correct in 84/84 cases; and a single component in a factor analysis accounted for 87% of the variance across seven measures: each patient's degree of impairment on atypical items in the six experimental tasks and a separate composite score reflecting his or her degree of semantic impairment. Errors also consistently conformed to the predicted pattern for both expressive and receptive tasks, with responses reflecting residual knowledge about the typical surface structure of each domain. We argue that these results cannot be explained as associated but unrelated deficits but instead are a principled consequence of a primary semantic impairment.
Hierarchical Statistical Learning of Generic Parts of Object Structure
Authors: Sanja Fidler, Gregor Berginc, Ales Leonardis
Venue: Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1 (2006)

With the growing interest in object categorization various methods have emerged that perform well in this challenging task, yet are inherently limited to only a moderate number of object classes. In pursuit of a more general categorization system this paper proposes a way to overcome the computational complexity encompassing the enormous number of different object categories by exploiting the statistical properties of the highly structured visual world. Our approach proposes a hierarchical acquisition of generic parts of object structure, varying from simple to more complex ones, which stem from the favorable statistics of natural images. The parts recovered in the individual layers of the hierarchy can be used in a top-down manner resulting in a robust statistical engine that could be efficiently used within many of the current categorization systems. The proposed approach has been applied to large image datasets yielding important statistical insights into the generic parts of object structure.
On the relationship between capacity and distance in an underwater acoustic communication channel
Authors: Milica Stojanovic
Venue: Proceedings of the 1st ACM international workshop on Underwater networks (2006)

Path loss of an underwater acoustic communication channel depends not only on the transmission distance, but also on the signal frequency. As a result, the useful bandwidth depends on the transmission distance, a feature that distinguishes an underwater acoustic system from a terrestrial radio one. This fact influences the design of an acoustic network: a greater information throughput is available if messages are relayed over multiple short hops instead of being transmitted directly over one long hop.We asses the bandwidth dependency on the distance using an analytical method that takes into account physical models of acoustic propagation loss and ambient noise. A simple, single-path time-invariant model is considered as a first step. To assess the fundamental bandwidth limitation, we take an information-theoretic approach and define the bandwidth corresponding to optimal signal energy allocation -- one that maximizes the channel capacity subject to the constraint that the transmission power is finite. Numerical evaluation quantifies the bandwidth and the channel capacity, as well as the transmission power needed to achieve a pre-specified SNR threshold, as functions of distance. These results lead to closed-form approximations, which may become useful tools in the design and analysis of acoustic networks.
Onboard classifiers for science event detection on a remote sensing spacecraft
Authors: Rebecca Castano, Dominic Mazzoni, Nghia Tang, Ron Greeley, Thomas Doggett, Ben Cichy, Steve Chien, Ashley Davies
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Typically, data collected by a spacecraft is downlinked to Earth and preprocessed before any analysis is performed. We have developed classifiers that can be used onboard a spacecraft to identify high priority data for downlink to Earth, providing a method for maximizing the use of a potentially bandwidth limited downlink channel. Onboard analysis can also enable rapid reaction to dynamic events, such as flooding, volcanic eruptions or sea ice break-up.Four classifiers were developed to identify cryosphere events using hyperspectral images. These classifiers include a manually constructed classifier, a Support Vector Machine (SVM), a Decision Tree and a classifier derived by searching over combinations of thresholded band ratios. Each of the classifiers was designed to run in the computationally constrained operating environment of the spacecraft. A set of scenes was hand-labeled to provide training and testing data. Performance results on the test data indicate that the SVM and manual classifiers outperformed the Decision Tree and band-ratio classifiers with the SVM yielding slightly better classifications than the manual classifier.The manual and SVM classifiers have been uploaded to the EO-1 spacecraft and have been running onboard the spacecraft for over a year. Results of the onboard analysis are used by the Autonomous Sciencecraft Experiment (ASE) of NASA's New Millennium Program onboard EO-1 to automatically target the spacecraft to collect follow-on imagery. The software demonstrates the potential for future deep space missions to use onboard decision making to capture short-lived science events.
Is there a future for empirical software engineering?
Authors: Victor R. Basili
Venue: Proceedings of the 2006 ACM/IEEE international symposium on Empirical software engineering (2006)

This talk provides a personal perspective on the evolution of empirical software engineering. The evolution has included the focus of the studies, e.g., from attempting to demonstrate the effectiveness of various processes to the building of knowledge around a domain or a set of processes. The study designs have changed from strictly quantitative studies to all forms of controlled experiments, quasi-experiments, preexperimental designs, case studies, field studies, and focus group activities. There has been recognition of the importance and influence of context variables and the domain in interpreting the results of studies. The issue of meta-analysis has become more important and is still an elusive goal. A community of empiricists has evolved that allows for the replication of studies leading to the identification of context variables.But there still does not exist a community consensus on the right ways to build bodies of knowledge or a "blessed" set of approaches. We argue over what is appropriate evidence when we review papers. We struggle with the concept of experimental replication. We do not know how to break an empirical study into significant small enough chunks for publication in the various standard forums. We have not convinced the software engineering community that empirical study is a necessary or even valuable research paradigm for the field.What other problems that remain? How can they be solved? What will the future hold for empirical study? This talk will address these issues and propose a possible path towards a mature empirical software engineering discipline.
Enterprise Resource Planning Diffusion: Measuring the Impact of Network Exposure and Power
Authors: Robert Pellerin, Gilbert Babin, Pierre-Majorique Leger, Kim St-Georges
Venue: Proceedings of the International Conference on Software Engineering Advances (2006)

Observations in industrial sectors indicate that companies that evolve in an industry in which a specific ERP system has been adopted by a number of members are more likely to adopt the same software. In this paper, we investigate two main effects influencing this diffusion pattern: the exposure of a firm in the network to its neighbours and the power of a firm within the network. To perform this analysis, we propose two models: a direct model that characterized the influence of immediate related ties, as well as an indirect model that characterized the influence of ties of ties. Network ties are here defined by interlock between board directorates. The statistical analysis of Canadian firm's data suggests that network ties, especially indirect exposure, influence the diffusion of ERP systems. The influence of direct and indirect exposure and firm power also appear to differ significantly from one ERP system to another.
Treatment of Laser Pointer and Speech Information in Lecture Scene Retrieval
Authors: Wataru Nakano, Takashi Kobayashi, Yutaka Katsuyama, Satoshi Naoi, Haruo Yokota
Venue: Proceedings of the Eighth IEEE International Symposium on Multimedia (2006)

We have previously proposed a unified presentation contents search mechanism named UPRISE (Unified Presentation Slide Retrieval by Impression Search Engine), and have also proposed a method to use laser pointer information in lecture scene retrieval. In this paper, we discuss the treatment of the laser pointer and speech information, and propose two methods to filter the laser pointer information using keyword occurrence in slides and speech. We also propose weighting schemata with filtered laser pointer information using slide text and speech information. We evaluate our approach by using actual lecture videos and presentation slides.
OWPL: A Gradual Approach for Software Process Improvement In SMEs
Authors: Simon Alexandre, Alain Renault, Naji Habra
Venue: Proceedings of the 32nd EUROMICRO Conference on Software Engineering and Advanced Applications (2006)

This paper describes an experience with a Software Process Improvement (SPI) approach particularly adapted to small structures with low software maturity level (e.g. small and medium enterprises in software businesses, small software teams in bigger businesses, small software teams in public organisations). A characterisation of Software Process in-the-small is first made on basis of a deep analysis of software processes actually followed by a number of small and medium enterprises (SMEs). The approach proposes a gradual Software Process Improvement framework based on three nested models. It allows SMEs to start SPI in a very targeted manner, to quickly progress within a limited budget and, eventually, to reach an acceptable level according to SPI standard models such as CMM and SPICE.
Algorithms for discovering bucket orders from data
Authors: Aristides Gionis, Heikki Mannila, Kai Puolamäki, Antti Ukkonen
Venue: Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining (2006)

Ordering and ranking items of different types are important tasks in various applications, such as query processing and scientific data mining. A total order for the items can be misleading, since there are groups of items that have practically equal ranks.We consider bucket orders, i.e., total orders with ties. They can be used to capture the essential order information without overfitting the data: they form a useful concept class between total orders and arbitrary partial orders. We address the question of finding a bucket order for a set of items, given pairwise precedence information between the items. We also discuss methods for computing the pairwise precedence data.We describe simple and efficient algorithms for finding good bucket orders. Several of the algorithms have a provable approximation guarantee, and they scale well to large datasets. We provide experimental results on artificial and a real data that show the usefulness of bucket orders and demonstrate the accuracy and efficiency of the algorithms.
A utility-based sensing and communication model for a glacial sensor network
Authors: Paritosh Padhy, Rajdeep K. Dash, Kirk Martinez, Nicholas R. Jennings
Venue: Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems (2006)

This paper reports on the development of a utility-based mechanism for managing sensing and communication in cooperative multi-sensor networks. The specific application considered is that of GLACSWEB, a deployed system that uses battery-powered sensors to collect environmental data related to glaciers which it transmits back to a base station so that it can be made available world-wide to researchers. In this context, we first develop a sensing protocol in which each sensor locally adjusts its sensing rate based on the value of the data it believes it will observe. Then, we detail a communication protocol that finds optimal routes for relaying this data back to the base station based on the cost of communicating it (derived from the opportunity cost of using the battery power for relaying data). Finally, we empirically evaluate our protocol by examining the impact on efficiency of the network topology, the size of the network, and the degree of dynamism of the environment. In so doing, we demonstrate that the efficiency gains of our new protocol, over the currently implemented method over a 6 month period, are 470%, 250% and 300% respectively.
A neural network classifier for cyclostationary signals
Authors: B. F. Rice, S. R. Smith, R. A. Threlkeld
Venue: Proceedings of the Acoustics, Speech, and Signal Processing,1994. on IEEE International Conference - Volume 04 (1994)

A signal classifier based on features that measure cyclostationarity has been developed and tested on simulated signals. The results demonstrate that features that represent the "cyclostationary signature" of a signal can be be used to automatically categorize a wide variety of signal types. The signature consists of a vector of "structure coefficients" that are computed on the outputs of various non-linear transformations of the target signal. This approach can considerably simplify and shorten the development time of the classifier. It is necessary to precede the computation of the signature with rejection of narrowband interference. The decision logic for the classifier is implemented using the probabilistic neural network.
Optimization of data exchange in parallel computers with distributed memory
Authors: E. V. Adutskevich, N. A. Likhoded
Venue: Cybernetics and Systems Analysis (2006)

The problem of optimization of communications during the execution of a program on a parallel computer with distributed memory is investigated. Statements are formulated that make it possible to determine the possibility of organization of data broadcast and translation. The conditions proposed are represented in the form suitable for practical application and can be used for automated parallelization of programs.
Short-range ferromagnetic order and metal-insulator transition in amorphous RexSi1-x (Re=Gd,Tb,Y) nano-composites
Authors: S. Caprara, V. V. Tugushev
Venue: Microelectronic Engineering (2005)

The theoretical description and numerical calculations are presented for different a-Re"xSi"1"-"x (Re=Gd,Tb,Y, 0.1
Rate-Distortion Optimized Progressive Geometry Compression
Authors: Zhang WenBo, Liu Bo, Zhang Hongbin
Venue: Proceedings of the International Conference on Computer Graphics, Imaging and Visualisation (2006)

During progressive transmission of 3D geometry models, the transmission order of details at different region has great effects on the quality of reconstructed models at low bit-rate. This work presents a ratedistortion (R-D) optimized progressive geometry compression scheme to improve the quality of reconstructed models by adjusting the transmission order of details. In this scheme, the input mesh is partitioned into parts, then each part is encoded into bit-stream independently, and the encoded bit-streams are truncated into segments while getting the R-D characteristics of every segment, at last all segments are assembled into a codestream based on R-D optimization, which ensure the region with rich detail will be transmitted early and make the reconstructed mesh achieve better quality as soon as possible. Experimental results show that, as compared with the well-known PGC method, the proposed one provides better R-D performance. Moreover, it provides a novel way to realize the region of interest (ROI) coding of 3D meshes.
Automatic workload synthesis for early design studies and performance model validation
Authors: Lizy Kurian John
Venue:  (2005)

Computer designers rely on simulation systems to assess the performance of their designs before the design is transferred to silicon and manufactured. Simulators are used in early design studies to obtain projections of performance and power over a large space of potential designs. Modern simulation systems can be four orders of magnitude slower than native hardware execution. At the same time, the numbers of applications and their dynamic instruction counts have expanded dramatically. In addition, simulation systems need to be validated against cycle-accurate models to ensure accurate performance projections. In prior work, long running applications are used for early design studies while hand-coded microbenchmarks are used for performance model validation. One proposed solution for early design studies is statistical simulation, in which statistics from the workload characterization of an executing application are used to create a synthetic instruction trace that is executed on a fast performance simulator. In prior work, workload statistics are collected as average behaviors based on instruction types. In the present research, statistics are collected at the granularity of the basic block. This improves the simulation accuracy of individual instructions. The basic block statistics form a statistical flow graph that provides a reduced representation of the application. The synthetic trace generated from a traversal of the flow graph is combined with memory access models, branching models and novel program synthesis techniques to automatically create executable code that is useful for performance model validation. Runtimes for the synthetic versions of the SPEC CPU, STREAM, TPC-C and Java applications are orders of magnitude faster than the runtimes of the original applications with performance and power dissipation correlating to within 2.4% and 6.4%, respectively, on average. The synthetic codes are portable to a variety of platforms, permitting validations between diverse models and hardware. Synthetic workload characteristics can easily be modified to model different or future workloads. The use of statistics abstracts proprietary code, encouraging code sharing between industry and academia. The significantly reduced execution times consolidate the traditionally disparate workloads used for early design studies and model validation.
A Flexible and Extensible Architecture For Context-Aware Annotation in E-Learning
Authors: Faical Azouaou, Cyrille Desmoulins
Venue: Proceedings of the Sixth IEEE International Conference on Advanced Learning Technologies (2006)

This article aims at proposing a flexible and extensible architecture for the context-aware annotation tool MemoNote dedicated to education. For that aim we define the configurations in which MemoNote must be able to adapt to context. The proposed architecture is assessed against scenarios based on these configurations.