ppxscal/embedding_network huggingface dataset:
Evolution and Growth in Large Libre Software Projects
Authors: Gregorio Robles, Juan Jose Amor, Jesus M. Gonzalez-Barahona, Israel Herraiz
Venue: Proceedings of the Eighth International Workshop on Principles of Software Evolution (2005)

Software evolution research has recently focused on new development paradigms, studying whether laws found in more classic development environments also apply. Previous works have pointed out that at least some laws seem not to be valid for these new environments and even Lehman has labeled those (up to the moment few) cases as anomalies and has suggested that further research is needed to clarify this issue. In this line, we consider in this paper a large set of libre (free, open source) software systems featuring a large community of users and developers. In particular, we analyze a number of projects found in literature up to now, including the Linux kernel. For comparison, we include other libre software kernels from the BSD family, and for completeness we consider a wider range of libre software applications. In the case of Linux and the other operating system kernels we have studied growth patterns also at the subsystem level. We have observed in the studied sample that super-linearity occurs only exceptionally, that many of the systems follow a linear growth pattern and that smooth growth is not that common. These results differ from the ones found generally in classical software evolution studies. Other behaviors and patterns give also a hint that development in the libre software world could follow different laws than those known, at least in some cases.
A New Clustering Algorithm of Large Datasets with O(N) Computational Complexity
Authors: Nuannuan Zong, Feng Gui, Malek Adjouadi
Venue: Proceedings of the 5th International Conference on Intelligent Systems Design and Applications (2005)

In fields such as Bioinformatics, Cytometry, Geographic Information Systems, just to name a few, huge amount of data, often multidimensional in nature, has more than ever highlighted the need for new algorithms to reduce the computational requirements needed for data analysis and interpretation. In this study, we present a new unsupervised clustering algorithm Density-based Adaptive Window Clustering Algorithm, which reduces the computational load to ~O(N) number of computations, making it more attractive and faster than current hierarchical algorithms. This method relies on weighting a dataset to grid points on a mesh, and identifies the density peaks by reducing low density points, ranking and correlation calculation. The adaptive windows used are a modification of the recently proposed k-windows clustering algorithm to shape the desired clusters. The new algorithm makes it easier for users to observe and analyze data for enhanced interpretation and improved real-world applications, especially in clinical practices.
A New Technique for Eliminating Data Migration in Logistic Evolution Storage System
Authors: HUAI-YANG LI, CHANG-SHENG XIE, CAI BIN, YAN LIU
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

In order to change the status that distributed storage system can't adapt to dynamic workloads, we introduce a new concept of evolution redundancy in logistic evolution storage system. It associates the redundancy level that characterizes the storage organization to sets of data and not to storage areas while eliminating data migration for reconfiguration. Inside storage node, the storage space is divided into some sequential region that can automatically adjust data layout on the basis of workload without data migration. Then evolution redundancy makes the map between logic block address and physical block address become very simply so as to avoid bottleneck incurred by complex map. For saving storage space during transforming between various RAID levels, we propose independent disks group by which our system not only implement evolution redundancy but also achieve well performance/cost. Finally, we carry out a large number of simulations to validate transformation threshold between different RAID levels.
Non-redundant clustering
Authors: Thomas Hofmann
Venue:  (2005)

Data mining and knowledge discovery attempt to reveal concepts, patterns, relationships, and structures of interest in data. Typically, data may have many such structures. Most existing data mining techniques allow the user little say in which structure will be returned from the search. Those techniques which do allow the user control over the search typically require supervised information in the form of knowledge about a target solution. In the spirit of exploratory data mining, we consider the setting where the user does not have information about a target solution. Instead we suppose the user can provide information about solutions which are not desired . These undesired solutions may be previously obtained from data mining algorithms, or they may be known to the user a priori. The goal is then to discover novel structure in the dataset which is not redundant with respect to the known structure. Techniques should guide the search away from this known structure and towards novel, interesting structures. We describe and formally define the task of non-redundant clustering. Three different algorithmic approaches are derived for non-redundant clustering. Their performance is experimentally evaluated on data sets containing multiple clusterings. We explore how these techniques may be extended to systematically enumerate clusterings in a data set. Finally, we also investigate whether non-redundant approaches may be incorporated to enhance state-of-the-art supervised techniques.
Example-Based Robust Outlier Detection in High Dimensional Datasets
Authors: Cui Zhu, Hiroyuki Kitagawa, Christos Faloutsos
Venue: Proceedings of the Fifth IEEE International Conference on Data Mining (2005)

Detecting outliers is an important problem. Most of its applications typically possess high dimensional datasets. In high dimensional space, the data becomes sparse which implies that every object can be regarded as an outlier from the point of view of similarity. Furthermore, a fundamental issue is that the notion of which objects are outliers typically varies between users, problem domains or, even, datasets. In this paper, we present a novel robust solution which detects high dimensional outliers based on user examples and tolerates incorrect inputs. It studies the behavior of projections of such a few examples, to discover further objects that are outstanding in the projection where many examples are outlying. Our experiments on both real and synthetic datasets demonstrate the ability of the proposed method to detect outliers corresponding to the user examples.
Generation of visual editors as eclipse plug-ins
Authors: Karsten Ehrig, Claudia Ermel, Stefan Hänsgen, Gabriele Taentzer
Venue: Proceedings of the 20th IEEE/ACM international Conference on Automated software engineering (2005)

Visual Languages (VLs) play an important role in software system development. Especially when looking at well-defined domains, a broad variety of domain specific visual languages are used for the development of new applications. These languages are typically developed specifically for a certain domain in a way that domain concepts occur as primitives in the language alphabet. Visual modeling environments are needed to support rapid development of domain-specific solutions.In this contribution we present a general approach for defining visual languages and for generating language-specific tool environments. The visual language definition is again given in a visual manner and precise enough to completely generate the visual environment. The underlying technology is Eclipse with its plug-in capabilities on the one hand, and formal graph transformation techniques on the other hand. More precisely, we present an Eclipse plug-in generating Java code for visual modeling plug-ins which can be directly executed in the Eclipse Runtime-Workbench.
A Medical Image Segmentation Method Based on Watershed Transform
Authors: CHEN Jia-xin, LIU Sen
Venue: Proceedings of the The Fifth International Conference on Computer and Information Technology (2005)

The watershed transform is a popular segmentation method coming from the field of mathematical morphology. In order to solve the over-segmentation of watershed algorithm's applied to medical images, we first transform the original image into a morphological gradient image by using morphology methods and treat it with an opening-closing filter bank to get a reference image with less noise interference; then we segment the reference image by using the watershed algorithm; finally, according to the test criterion with respect to the gray mean of the region boundary and the region area, we merge the segment field. Experiments applying to segmentation of medical images by using watershed algorithm show that the image processing before and after segmentation prevents the over-segmentation effectively.
Situated creation of multimedia activities for distance learners: motivational and cultural issues
Authors: Christine Develotte, François Mangenot, Katerina Zourou
Venue: ReCALL (2005)

This paper discusses the design and implementation of a task-oriented collaborative learning (and training) experimental project that was carried out with future language teachers. More specifically, a class of sixteen French students enrolled in a Masters of Education course were asked to create multimedia resources for a group of Australian students with no prior knowledge of French. This paper deals only with issues concerning French students&rsquo; multimedia creations, not with the second phase of interactions with the Australian target group. The theoretical background is situated and collaborative learning and training: the French students worked in pairs, creating multimedia activities based on their culture for real students in a different location. They communicated with each other during weekly classes and via a groupware tool. A triangulated data method was used incorporating the students&rsquo; multimedia outcome, questionnaires and semi-directive interviews. The following issues are discussed: what is the effect of such situated learning settings on motivation, commitment and computer literacy? What image did the French students have of the Australian students and which cultural aspects did they try to convey?
Simple 3D Glyphs for Spatial Multivariate Data
Authors: Camilla Forsell, Stefan Seipel, Mats Lind
Venue: Proceedings of the Proceedings of the 2005 IEEE Symposium on Information Visualization (2005)

We present an effort to evaluate the possible utility of a new type of 3D glyphs intended for visualizations of multivariate spatial data. They are based on results from vision research suggesting that our perception of metric 3D structure is distorted and imprecise relative to the actual scene before us (e.g., [1]); only a class of qualitative properties of the scene is perceived with accuracy. These properties are best characterized as being invariant over affine but not Euclidean transformations. They are related, but not identical to, the non-accidental properties (NAPs) described by Lowe [2] on which the notion of geons is based [3]. A large number of possible 3D glyphs for the visualization of spatial data can be constructed using such properties. One group is based on the local sign of surface curvature. We investigated these properties in a visualization experiment. The results are promising and the implications for visualization are discussed.
A Machine Learning Approach for Automatic Performance of a Trumpet
Authors: James Bilitski
Venue: Proceedings of the Sixth International Conference on Computational Intelligence and Multimedia Applications (2005)

The artificial mouth is a robotic device that simulates a human mouth. It consists of moveable lips and an adjustable air supply. In this study the use of a genetic algorithm to compute air pressure and lip pressure values so that the artificial mouth can correctly play five notes on a trumpet was investigated. The genetic algorithm is discussed. Results from experimentation showed solutions being found in as little as two generations.
Spatial Measurements for Medical Augmented Reality
Authors: Bernhard Reitinger, Pascal Werlberger, Alexander Bornik, Reinhard Beichel, Dieter Schmalstieg
Venue: Proceedings of the 4th IEEE/ACM International Symposium on Mixed and Augmented Reality (2005)

This paper presents a set of Augmented Reality (AR) based interaction techniques for spatial analysis of medical datasets. Computer-aided medical planning tools such as our Virtual Liver Surgery Planning System require precise and intuitive interaction for the quantitative inspection of anatomical and pathological structures. We argue that AR is a superior tool compared to desktop 2D or 3D visualization for performing such analysis, because it allows true direct manipulation of 3D virtual objects in space, while rendering the medical data in the familiar context of the user's own body.
Incompressible Finite Elements via Hybridization. Part II: The Stokes System in Three Space Dimensions
Authors: Bernardo Cockburn, Jayadeep Gopalakrishnan
Venue: SIAM Journal on Numerical Analysis (2005)

We introduce a method that gives exactly incompressible velocity approximations to Stokes flow in three space dimensions. The method is designed by extending the ideas in Part I [B. Cockburn and J. Gopalakrishnan, SIAM J. Numer. Anal., 43 (2005), pp. 1627--1650] of this series, where the Stokes system in two space dimensions was considered. Thus we hybridize a vorticity-velocity formulation to obtain a new mixed method coupling approximations of tangential velocity and pressure on mesh faces. Once this relatively small tangential velocity-pressure system is solved, it is possible to recover a globally divergence-free numerical approximation of the fluid velocity, an approximation of the vorticity whose tangential component is continuous across interelement boundaries, and a discontinuous numerical approximation of the pressure. The main difference between our method here and that of the two-dimensional case treated in Part I is in the use of Nédélec elements, which necessitates development of new hybridization techniques. We also generalize the method to allow for varying polynomial degrees on different mesh elements and to incorporate certain nonstandard but physically relevant boundary conditions.
Face Tracking by Maximizing Classification Score of Face Detector Based on Rectangle Features
Authors: Akinori HIDAKA, Kenji NISHIDA, Takio KURITA
Venue: Proceedings of the Fourth IEEE International Conference on Computer Vision Systems (2006)

Face tracking continues to be an important topic in computer vision. We describe a tracking algorithm based on a static face detector. Our face detector is a rectanglefeature- based boosted classifier, which outputs the confidence whether an input image is a face. The function that outputs this confidence, called a score function, contains important information about the location of a moving target. A target that has moved will be located in the gradient direction of a score function from the location before moving. Therefore, our tracker will go to the region where the score is maximum using gradient information of this function. We show that this algorithm works by the combination of jumping to the gradient direction and precise search at the local region.
Sundials in the shade: a study of women's persistence in the first year of a computer science program in a selective university
Authors: Ursula Wagener
Venue:  (2005)

Currently women are underrepresented in departments of computer science, making up approximately 18% of the undergraduate enrollment in selective universities. Most attrition in computer science occurs early in this major, in the freshman and sophomore years, and women drop out in disproportionately greater numbers than their male counterparts. Taking an ethnographic approach to investigating women's experiences and progress in the first year courses in the computer science major at the University of Pennsylvania, this study examined the pre-college influences that led these women to the major and the nature of their experiences in and outside of class with faculty, peers, and academic support services. This study sought an understanding of the challenges these women faced in the first year of the major with the goal of informing institutional practice about how to best support their persistence. The research reviewed for this study included patterns of leaving majors in science, math and engineering (Seymour Hewitt 1997), the high school preparation needed to pursue math and engineering majors in college (Strenta, Elliott, Adair, Matier, Scott, 1994), and intervention programs that have positively impacted persistence of women in computer science (Margolis Fisher, 2002). The research method of this study employed a series of personal interviews over the course of one calendar year with fourteen first year women who had either declared on intended to declare the computer science major in the School of Engineering and Applied Science at the University of Pennsylvania. Other data sources were focus groups and personal interviews with faculty, administrators, admissions and student life professionals, teaching assistants, female graduate students, and male first year students at the University of Pennsylvania. This study found that the women in this study group came to the University of Pennsylvania with a thorough grounding in mathematics, but many either had an inadequate background in computer science, or at least perceived inadequacies in their background, which prevented them from beginning the major on an equal footing with their mostly male peers and caused some to lose confidence and consequently interest in the major. Issues also emanated from their gender-minority status in the Computer and Information Science Department, causing them to be socially isolated from their peers and further weakening their resolve to persist. These findings suggest that female first year students could benefit from multiple pathways into the major designed for students with varying degrees of prior experience with computer science. In addition, a computer science community within the department characterized by more frequent interaction and collaboration with faculty and peers could positively impact women's persistence in the major.
Eliciting confidentiality requirements in practice
Authors: Seda Gürses, Jens H. Jahnke, Christina Obry, Adeniyi Onabajo, Thomas Santen, Morgan Price
Venue: Proceedings of the 2005 conference of the Centre for Advanced Studies on Collaborative research (2005)

Confidentiality, the protection of unauthorized disclosure of information, plays an important role in information security of software systems. Security researchers have developed numerous approaches on how to implement confidentiality, typically based on cryptographic algorithms and tight access control. However, less work has been done on defining systematic methods on how to elicit and define confidentiality requirements in the first place. Moreover, most of these approaches are illustrated with simulated examples that do not capture the richness of real world experience. This paper reports on our experiences eliciting confidentiality requirements in a real world project in the health care area. The method applied originates from the M.Sc. thesis of one of the authors and is still considered work in progress. Still, valuable insight into issues of confidentiality requirements engineering can be gained from this case study and we expect that its publication will become a basis for discussion and the definition of a further research agenda in this area.
Trove: a physical game running on an ad-hoc wireless sensor network
Authors: Sarah Mount, Elena Gaura, Robert M. Newman, Alastair R. Beresford, Sam R. Dolan, Michael Allen
Venue: Proceedings of the 2005 joint conference on Smart objects and ambient intelligence: innovative context-aware services: usages and technologies (2005)

This paper describes Trove, a physical game implemented on a wireless sensor network (WSN). Architecturally, the WSN is a decentralized system, exhibiting local node processing and information extraction, collaborative inter-node behaviour and local decision making capabilities. From the perspective of the players, Trove is a multi-player, real time, physical game. The user-centered narrative, configuration and game play of Trove ate presented as well as its design and implementation.Trove will be used at Coventry University as a pedagogical aid in under- and postgraduate modules which incorporate concepts from pervasive computing and sensor networks; and also for the dissemination of research work to members of the public. Although educational through its use, the work presented here concerns, from a technical viewpoint, the very specifics of physical WSN design, implementation and deployment and forms a good basis for further proof of concept experimentation within the domain.
Scheduling AND/OR Precedence Constraints Jobs to Minimize the Makespan by Mapping from CPM to AND/OR Network
Authors: Tao Wang, Da-Xin Liu
Venue: Proceedings of the 11th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (2005)

Scheduling AND/OR precedence constraints jobs to produce a feasible schedule is a well studied problem in real time jobs scheduling field ..many approaches and algorithms are presented to solve this problem. However, few of them use the project scheduling method applied in the real time jobs scheduling. In this paper, a new idea of scheduling the AND/OR precedence constraints by a network analysis method CPM is introduced. The minimum makespan of AND/OR precedence constraints jobs is the important performance objective. The AND/OR and CPM models are introduced and used to schedule the jobs with precedence constraints. Moreover, an ES algorithm is presented to solve the problem of scheduling AND/OR precedence constraints to minimize the makespan. The algorithm can compute the job¿s ES in polynomial time and its capacity is O (n_a+n_olog n_o+ n_a).
iCARE: intelligent customer assistance for recommending eyewear
Authors: Edwin Costello, John Doody, Lorraine McGinty, Barry Smyth
Venue: Proceedings of the 11th international conference on Intelligent user interfaces (2006)

Consumers are often overwhelmed by the range of product choices available, especially online, and recommender systems have emerged as an important tool for helping users to navigate through complex product spaces based on their preferences. In this paper we describe work that concentrates on how research ideas from two complimentary research communities (recommender systems and intelligent user interfaces) can be married to improve online recommender systems. In particular, we are interested in content-based recommendation domains that rely heavily on explicit feature-level feedback from users. Oftentimes this type of feedback is difficult for users to provide and we look at how this might be addressed through product visualization techniques in this paper, focusing on the iCARE System for recommending suitable eyeglasses to individual users.
Face to Face Collaborative AR on Mobile Phones
Authors: Anders Henrysson, Mark Billinghurst, Mark Ollila
Venue: Proceedings of the 4th IEEE/ACM International Symposium on Mixed and Augmented Reality (2005)

Mobile phones are an ideal platjorm for augmented reality. In this paper we describe how they also can be used to support face to face collaborative AR applications. We have created a custom port of the ARToolKit library to the Symbian mobile phone operating system and then developed a sample collaborative AR game based on this. We describe the game in detail and user feedback from people who have played it. We also provide general design guidelines that could he useful for others who are developing mobile phone collaborative AR applications.