ppxscal/embedding_network huggingface dataset:
Predicting build failures using social network analysis on developer communication
Authors: Timo Wolf, Adrian Schroter, Daniela Damian, Thanh Nguyen
Venue: Proceedings of the 2009 IEEE 31st International Conference on Software Engineering (2009)

A critical factor in work group coordination, communication has been studied extensively. Yet, we are missing objective evidence of the relationship between successful coordination outcome and communication structures. Using data from IBM's Jazz™ project, we study communication structures of development teams with high coordination needs. We conceptualize coordination outcome by the result of their code integration build processes (successful or failed) and study team communication structures with social network measures. Our results indicate that developer communication plays an important role in the quality of software integrations. Although we found that no individual measure could indicate whether a build will fail or succeed, we leveraged the combination of communication structure measures into a predictive model that indicates whether an integration will fail. When used for five project teams, our predictive model yielded recall values between 55% and 75%, and precision values between 50% to 76%.
Reliable p-hub location problems and protection models for hub network design
Authors: Morton E. O'Kelly
Venue:  (2008)

This dissertation addresses a series of new hub location problems and network design models, which are termed reliable p-hub location problems, and p-hub protection problems. The essential motivation to propose these problems arises from the increasing vulnerability in current telecommunication and transportation networks where the networks have converged into more hub-and-spoke type systems. The models presented in the chapters aim to enhance both a network&rsquo;s performance and its resiliency to the potential disruptions in transportation and telecommunication networks.The major research objectives and contributions are outlined below.First, the reliable p-hub location problems are addressed in terms of network reliability. The models demonstrate how optimal hub locations are determined under various reliability or capability conditions of network facilities. Geographical closeness of hubs can enhance network performance by increasing efficiency of traffic exchanges among hub facilities. The dispersion of hub facilities can be considered in hub network design which can protect the excessive concentration of flows from particular hub facilities.Second, the p-hub protection problems are focused on hub network design in a survivable network design. Three standard models are addressed based on single, multiple and survivable routing schemes. As extensions, capacitated and minimum threshold models are presented. The relationship between network costs, redundancy of linkages, and the survivability of networks in order to protect hub activity levels are examined.Finally, efficient heuristics to solve the reliable hub network design models are presented. In particular, a tabu search heuristic (TABUSA) and a hybrid-type heuristic (TABUEX) are developed to solve the most difficult models which are developed based on single and survivable routing schemes. From the computational results, both search approaches demonstrate their efficiency in solving the problems, offering the viability to apply larger size problems effectively within a reasonable computational time.As concluding remarks, this dissertation provides good insights for reliable and survivable hub network design. The models are also expected to be utilized as decision tools for geographers, network planners, and policy makers in designing critical network infrastructures.
Study on the Offset Color Reproduction Control System Based on Fuzzy Neural Network
Authors: Liming Guan, Jian Lin
Venue: Proceedings of the 6th International Symposium on Neural Networks: Advances in Neural Networks - Part II (2009)

The recursive CFNN model was established against the characteristics of offset color reproduction quality control. The neural network can be used to construct the fuzzy system, and the self-adaptive and self-learning capability of neural networks was used to automatically adjust fuzzy system parameters, BP network could be learned and trained by the gradient descent algorithm. Based on the test data for the study and testing of network, system error is less than the national standard error requirements, the results proved the effectiveness and feasibility of the algorithm.
Electrical characterization of metal-ferroelectric (Mn-substituted BiFeO3)-insulator (HfO2)-semiconductor capacitors for nonvolatile memory applications
Authors: Pi-chun Juan, Chen-Hao Wang
Venue: Microelectronic Engineering (2009)

Metal-ferroelectric (Mn-substituted BiFeO"3)-insulator (HfO"2)-semiconductor has been fabricated by co-sputtering technique. X-ray diffraction (XRD) patterns have proven the existence of a substitution phase. The shift in binding energy of Fe ions and the change in atom ratio of Mn to Fe were analyzed by X-ray photoelectron spectra (XPS). The memory windows as functions of insulator film thickness and annealing temperature were compared. The maximum memory window is 3V at the sweep voltage of 8V with thicker (60nm) HfO"2. The leakage current and the charge injection effect can be reduced with increasing the amount of substituting Mn for Fe-site.
Semanta --- Semantic Email in Action
Authors: Simon Scerri, Ioana Giurgiu, Brian Davis, Siegfried Handschuh
Venue: Proceedings of the 6th European Semantic Web Conference on The Semantic Web: Research and Applications (2009)

Semanta is a system supporting Semantic Email, implemented as an add-in to two popular Mail User Agents, using existing email transport technology and integrated with the Social Semantic Desktop. It enables machines to support email users with correctly interpreting, handling and keeping track of action items within email messages, visualizing email workflows, and extracting tasks and appointments from email messages.
Meme-tracking and the dynamics of the news cycle
Authors: Jure Leskovec, Lars Backstrom, Jon Kleinberg
Venue: Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining (2009)

Tracking new topics, ideas, and "memes" across the Web has been an issue of considerable interest. Recent work has developed methods for tracking topic shifts over long time scales, as well as abrupt spikes in the appearance of particular named entities. However, these approaches are less well suited to the identification of content that spreads widely and then fades over time scales on the order of days - the time scale at which we perceive news and events. We develop a framework for tracking short, distinctive phrases that travel relatively intact through on-line text; developing scalable algorithms for clustering textual variants of such phrases, we identify a broad class of memes that exhibit wide spread and rich variation on a daily basis. As our principal domain of study, we show how such a meme-tracking approach can provide a coherent representation of the news cycle - the daily rhythms in the news media that have long been the subject of qualitative interpretation but have never been captured accurately enough to permit actual quantitative analysis. We tracked 1.6 million mainstream media sites and blogs over a period of three months with the total of 90 million articles and we find a set of novel and persistent temporal patterns in the news cycle. In particular, we observe a typical lag of 2.5 hours between the peaks of attention to a phrase in the news media and in blogs respectively, with divergent behavior around the overall peak and a "heartbeat"-like pattern in the handoff between news and blogs. We also develop and analyze a mathematical model for the kinds of temporal variation that the system exhibits.
Advanced Programming Using Visual Basic 2008, 4th edition
Authors: Julia Case Bradley, Anita C. Millspaugh
Venue:  (2009)

The author team of Julia Bradley and Anita Millspaugh remain the guiding light for countless. students around the world in Programming in Visual Basic 2008. How better to master the most popular object-oriented programming language than to use the bestselling textbook? Be at the cutting edge of technology with examples, feedback questions, and a full Hands-On Programming Example. Apply the concepts yourself with Case Studies and Exercises. Screen captures, step-by-step exercises, and thorough appendices ensure that Programming Excellence Begins Here..
A two-asset stochastic model for long-term portfolio selection
Authors: James J. Kung
Venue: Mathematics and Computers in Simulation (2009)

In mean-variance (M-V) analysis, an investor with a holding period [0,T] operates in a two-dimensional space-one is the mean and the other is the variance. At time 0, he/she evaluates alternative portfolios based on their means and variances, and holds a combination of the market portfolio (e.g., an index fund) and the risk-free asset to maximize his/her expected utility at time T. In our continuous-time model, we operate in a three-dimensional space-the first is the spot rate, the second is the expected return on the risky asset (e.g., an index fund), and the third is time. At various times over [0,T], we determine, for each combination of the spot rate and expected return, the optimum fractions invested in the risky and risk-free assets to maximize our expected utility at time T. Hence, unlike those static M-V models, our dynamic model allows investors to trade at any time in response to changes in the market conditions and the length of their holding period. Our results show that (1) the optimum fraction y*(t) in the risky asset increases as the expected return increases but decreases as the spot rate increases; (2) y*(t) decreases as the holding period shortens; and (3) y*(t) decreases as the risk aversion parameter-@c is larger.
Parallel smoothing of quad meshes
Authors: Young In Yeo, Tianyun Ni, Ashish Myles, Vineet Goel, J&#x00f6;rg Peters
Venue: The Visual Computer: International Journal of Computer Graphics (2009)

For use in real-time applications, we present a fast algorithm for converting a quad mesh to a smooth, piecewise polynomial surface on the Graphics Processing Unit (GPU). The surface has well-defined normals everywhere and closely mimics the shape of Catmull&#x2013;Clark subdivision surfaces. It consists of bicubic splines wherever possible, and a new class of patches&#x2014;c-patches&#x2014;where a vertex has a valence different from&#x00a0;4. The algorithm fits well into parallel streams so that meshes with 12,000 input quads, of which 60% have one or more non-4-valent vertices, are converted, evaluated and rendered with 9&#x00d7;9 resolution per quad at 50 frames per second. The GPU computations are ordered so that evaluation avoids pixel dropout.
A unified data-centric approach towards an extensible internet architecture
Authors: Jonathan M. Smith, Boon Thau Loo
Venue:  (2008)

The Internet's role is changing dramatically, from a means of connecting together PCs and servers to a ubiquitous communications medium interconnecting mobile personal devices, environmental sensors, and Web services. As new services (voice, video, emergency response, etc.) are being deployed on the infrastructure, there have been increased demands on extending the existing Internet architecture for new capabilities, such as efficient and resilient routing among mobile and wired nodes, location of proximity-based services, and wide-area service discovery and composition. This dissertation presents an extensible Internet architecture M OSAIC&mdash;based on declarative languages and composable views over router, network and host state at different layers&mdash;to meet the demand of the emerging network services. The proposed architecture explicitly separates logical state representation and acquisition from physical implementation, to enable more extensible and adaptive protocols and distributed systems, because programmers can focus on high-level logical operations whose implementations may be separately and transparently optimized. The main contributions made by this dissertation are: (1) a unified network architecture (MOSAIC) under which new networks can be developed, deployed, selected, and dynamically composed according application and administrator needs; (2) a declarative programming language (Mozlog) to concisely specify high-level network protocol specifications; (3) a runtime system prototype that can translate Mozlog specifications into efficient implementations. To validate the approach, we evaluate the work in the context of a heterogeneous, dynamic Internet environment where end hosts are connected via both wired and wireless media and have diverse application requirements. We demonstrate that in MOSAIC, new network services can be readily introduced by either concisely specifying protocols in Mozlog or dynamically selecting and composing existing network services at low overheads.
Effective electrical conductivity estimation for a novel multi-phase composite material
Authors: Oltean Dan, Motoc Luca Dana, Luca Vasile
Venue: Proceedings of the 8th WSEAS international conference on Microelectronics, nanoelectronics, optoelectronics (2009)

The paper aims to present a novel configuration of a mixed conductive particles embedded into a non-conductive polymeric matrix, that we call a multi-phase composite material, developed to exhibit predictable electrical conductivities. Graphite and iron particles, having different volume fractions, were blend together into a PVAc matrix with the aim of sizing the influencing factors on sample's measured electrical conductivities. The retrieved values were plotted against some theoretical models from literature.
Robust techniques for visual surveillance
Authors: Larry S. David
Venue:  (2008)

The work described here aims at improving the performance of three building blocks of visual surveillance systems: foreground detection, object tracking and event detection.First, a new background subtraction algorithm is presented for foreground detection. The background model is built with a set of codewords for every pixel. The codeword contains the pixel's principle color and a tangent vector that represents the color variation at that pixel. As the scene illumination changes, a pixel's color is predicted using a linear model of the codeword and the codeword, in turn, is updated using the new observation. We carried out a number of experiments on sequences that have extensive lighting change and compare with previously developed algorithms.Second, we describe a multi-resolution tracking framework developed with efficiency and robustness in mind. Efficiency is achieved by processing low resolution data whenever possible. Robustness results from multiple level coarse-to-fine searching in the tracking state space. We combine sequential filtering both in time and resolution levels int a probabilistic framework. A color blob tracker is implemented and the tracking results are evaluated in a number of experiments.Third, we present a tracking algorithm based on motion analysis of regional affine invariant image features. The tracked object is represented with a probabilistic occupancy map. Using this map as support, regional features are detected and matched across frames. The motion of pixels is then established based on the feature motion. The object occupancy map is in turn updated according to the pixel motion consistency. We describe experiments to measure the sensitivity of our approach to inaccuracy in initialization, and compare it with other approaches.Fourth, we address the problem of visual event recognition in surveillance where noise and missing observations are serious problems. Common sense domain knowledge is exploited to overcome them. The knowledge is represented as first-order logic production rules with associated weights to indicate their confidence. These rules are used in combination with a relaxed deduction algorithm to construct a network of grounded atoms, the Markov Logic Network. The network is used to perform probabilistic inference for input queries about events of interest. The system's performance is demonstrated on a number of videos from a parking lot domain that contains complex interactions of people and vehicles.
Privacy-conscious P2P data sharing scheme with bogus profile distribution
Authors: Makoto Iguchi, Shigeki Goto
Venue: Web Intelligence and Agent Systems (2009)

With the increasing use of P2P (peer-to-peer) network technology in everyday services, the issue of privacy protection has gained considerable importance. This paper describes a method to realize an anonymity-conscious P2P data sharing network. The proposed network allows users to extract data possessed by other users who have similar profiles, thereby providing them with a collaborative filtering-based data recommendation. In the proposed P2P network protocol, bogus user profiles are distributed intentionally throughout the network to protect users' anonymity without harming the overall effectiveness of the data exchange. We conduct a series of simulations to prove that our proposed method protects the profile's privacy and performs efficient data exchange.
Mixture of Gaussians Model for Robust Pedestrian Images Detection
Authors: Dymitr Ruta
Venue: Proceeding of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence (2008)

Automated pedestrian detection is a forward looking challenge for future driver support systems in automotive industry. Such system would have to make safety critical decisions based on poor quality images shot in real-time from the unstable moving vehicles. The proposed system offers a simple yet very effective detection methodology based on mixture of Gaussians (MoG) aided by an Expectation-Maximisation (EM) clustering algorithm. The algorithm operates on a number of features built by aggregation of different variations of the first and second order pixel gradients related to the aggregated templates of pedestrian and non-pedestrian classes. For each class the algorithm fits a fixed number of clusters and using Gaussian kernels optimises the parameters of the Gaussian Mixture model such that the probabilities of belonging to the intraclass clusters is maximised. Given a new image the system instantly generates relative features and uses mixture model to build posterior probability densities for all clusters and after aggregation and renormalisation, posterior class probabilities. The system has been fine-tuned against its parameters and feature subsets and tested using almost 10000 real images provided by DaimlerChrysler. Reaching the testing performance in excess of 95% the model was announced the winner of the NISIS Competition 2007.
Bounding the Size of Equimatchable Graphs of Fixed Genus
Authors: Ken-ichi Kawarabayashi, Michael D. Plummer
Venue: Graphs and Combinatorics (2009)

A graph G is said to be equimatchable if every matching in G extends to (i.e., is a subset of) a maximum matching in G. In an earlier paper with Saito, the authors showed that there are only a finite number of 3-connected equimatchable planar graphs. In the present paper, this result is extended by showing that in a surface of any fixed genus (orientable or non-orientable), there are only a finite number of 3-connected equimatchable graphs having a minimal embedding of representativity at least three. (In fact, if the graphs considered are non-bipartite, the representativity three hypothesis may be dropped.) The proof makes use of the Gallai-Edmonds decomposition theorem for matchings.
Stroke extraction based on ambiguous zone detection: a preprocessing step to recover dynamic information from handwritten Chinese characters
Authors: Zhewen Su, Zhongsheng Cao, Yuanzhen Wang
Venue: International Journal on Document Analysis and Recognition (2009)

A method of stroke extraction based on ambiguous zone detection is presented to facilitate the recovery of dynamic information from static handwritten Chinese character images. First, ambiguous zones are detected using feature points of the skeleton and the contour information around them. Then, a graph is built to represent each character, and the continuity of sub-strokes is analyzed using Bayesian classification. Several constraint conditions are proposed to search stroke paths in the graph and two criteria are also utilized to deal with multi-traced sub-strokes. Finally, strokes are reconstructed by B-spline interpolation. Experimental results show that the proposed method can detect the ambiguous zones accurately, and is feasible and effective for stroke extraction.
Robust character region extraction against camera motion and illumination variation
Authors: Miyoung Choi, Gyeyoung Kim, Hyungil Choi
Venue: Proceedings of the 7th WSEAS international conference on Computational intelligence, man-machine systems and cybernetics (2008)

In this paper, we propose the method that can anticipate the changes in illumination, filter out the reflectance component, clustering the colors and use the Saliency map to extract the character region, for the purpose of acquiring the character region extraction which is robust against the variation of illumination. We use outline information at down sampling in difference image by current image and reference images to have worked at continuous image in order to efficiently perceive whether or not there is by the occurrence of camera motion. We judge so that camera motion occurred if a action the average block which you defined is larger the critical value that decided experimentally, and carry out algorithm for global motion compensation. Natural scene images normally have an illumination component as well as a reflectance component. It is well known that a reflectance component usually obstructs the task of extracting and recognizing objects like character in the scene, since it blurs out an overall image. We propose an approach that efficiently removes reflectance components while preserving illumination components. We decided whether an input image hits Normal or Polarized for determining the light environment, using the histogram which consisted of a red component. In the normal image, we acquired the character region without additional processing. Otherwise we removed light reflecting from the object using homomorphic filtering in the polarized image. And then this decided the each character region based on the color clustering technique and the Saliency Map. Finally, we localized character region on these two candidate regions.
The Impact of Alias Analysis on VLIW Scheduling
Authors: Marco Garatti, Roberto Costa, Stefano Crespi Reghizzi, Erven Rohou
Venue: Proceedings of the 4th International Symposium on High Performance Computing (2009)

This experiment studies the speed-up increase that alias analysis (AA) produces on code for very long instruction word machines. AA is done on-demand when requested by the scheduler, in order to eliminate critical arcs of the data dependence graph. Different heuristic criteria are investigated for deciding when to compute alias information,and they show that only a fraction of the alias relation really contributes to the program speed-up. A qualitative study shows that the quality of the initial code affects the speedup alias analysis can give. The results should help compiler designers for VLIW machines in making cost effective AA decisions.