ppxscal/embedding_network huggingface dataset:
Computation of the alignment of myocardial contractile pathways using a magnetic tablet and an optical method
Authors: C. W. Cryer, H. Navidi-Kasmai, P. P. Lunkenheimer, K. Redmann
Venue: Technology and Health Care (1997)

The computation of the inclination angle of myocardial contractile pathways, based on the data from (1) optically and (2) manually digitized hearts is described. The measured raw data comprised: (1) A list epi of points on an epicardial surface S. (2) For each selected contractile pathway f, a list of points along the contractile pathway. For any point {\scriptstyle{\bfm p}} on a contractile pathway f, the angle of inclination \alpha_{\scriptscriptstyle{\bfm p}} = \alpha_{\scriptscriptstyle{\bfm p}} ({\scriptstyle{\bfm p}},f,S) is defined to be the angle (in degrees) between the tangent {\rm t}_{\scriptscriptstyle{\bfm p}}={\rm t}_{\scriptscriptstyle{\bfm p}}(f) to the contractile pathway f at the point {\scriptstyle{\bfm p}} and the tangent plane T_{{\bfm v}_{\bfm p}} to the surface S at the surface point {\scriptstyle{\bfm v}}_{\scriptscriptstyle{\bfm p}} = {\scriptstyle{\bfm v}}({\scriptstyle{\bfm p}},S) which is nearest to {\scriptstyle{\bfm p}}. Thus \alpha_{\scriptscriptstyle{\bfm p}} is a generalization of the imbrication angle of Streeter. The angle of inclination was computed using two separate numerical methods: (1) A discrete method, applying finite differences to the raw data, to compute the tangents {\rm t}_{\scriptscriptstyle{\bfm p}} and the tangent planes T_{{\bfm v}_{\bfm p}}, after which the results were smoothed. (2) A smoothing method in which the data was first smoothed to obtain an approximation S_{epi} to the epicardial surface and spline approximations to the contractual pathways f. We describe the results for two typical hearts: a manually digitized dilated pig heart and an optically digitized constricted cow heart. For each heart we first present the depths and angles of inclination of typical contractual pathways and then summarize the results in the form of histograms. The results are discussed in detail in the accompanying paper of Lunkenheimer, Redmann et al. [P.P. Lunkenheimer, K. Redmann, K.-H. Dietl, C. Cryer, K.-D. Richter, W.F. Whimster and P. Niederer, The hearts fibre alignment assessed by comparing two digitizing systems. Methodological investigation into the inclination angle towards wall thickness, Technology and Health Care 5 (1997), 65-77], where the digitization methods are also described.
Memory Trends in the 70's
Authors: R. H. Fuller
Venue: Computer (1970)

A modern data storage system is designed in three independent phases. The first design, that of the memory element and subsystem, has the objectives of providing functionally simple storage units of high capacity and operating speed at low cost. This discipline embraces the design of core, film, semiconductor and optical static memories as well as a variety of moving media memories.
Software Engineering
Authors: R. T. Yeh
Venue: Computer (1975)

The state of software engineering is diverse, disorderly, and expanding, Coined less than seven years ago, the term is used today to describe such disparate activities as programming methodology, software development, and programming tools and standards. But for all the confusion surrounding it, this new discipline does seem to promise solutions to some of the most vexing problems of modern software development efforts: reliability and complexity. Clearly, the subject deserves to be explored.
Performance of space-frequency combining at the antenna array of a MC-CDMA system
Authors: Wei Yang, Junshi Chen, Zhenhui Tan, Shixin Cheng
Venue: Wireless Personal Communications: An International Journal (2007)

In this paper, a multicarrier code-division multiple-access (MC-CDMA) system employing antenna array at base station with quaternary phase shift keying (QPSK) modulation is proposed. This receiver adopts a space-frequency two-dimensional (2-D) Rake receiver structure. Based on the detailed analysis of the interference characteristics of the proposed system, the bit error rate (BER) performance of the system is provided. With regard to spatial domain combining, the optimum and suboptimum combining weight is derived, while the suboptimum set of weights is simplified on sense of that only the knowledge of array vector of desired user alone is sufficient for the combining. Simulation results verify the analysis and show that better performance is achieved for the proposed antenna array MC-CDMA system than the corresponding single antenna approach.
Price formation and its dynamics in online auctions
Authors: Ravi Bapna, Wolfgang Jank, Galit Shmueli
Venue: Decision Support Systems (2008)

This research uses functional data modeling to study the price formation process in online auctions. It conceptualizes the price evolution and its first and second derivatives (velocity and acceleration respectively) as the primary objects of interest. Together these three functional objects permit us to talk about the dynamics of an auction, and how the influence of different factors vary throughout the auction. For instance, we find that the incremental impact of an additional bidder's arrival on the rate of price increase is smaller towards the end of the auction. Our analysis suggests that ''stakes'' do matter and that the rate of price increase is faster for more expensive items, especially at the start and the end of an auction. We observe that higher seller ratings (which correlate with experience) positively influence the price dynamics, but the effect is weaker in auctions with longer durations. Interestingly, we find that the price level is negatively related to auction duration when the seller has low rating whereas in auctions with high-rated sellers longer auctions achieve higher price levels throughout the auction, and especially at the start and end. Our methodological contributions include the introduction of functional data analysis as a useful toolkit for exploring the structural characteristics of electronic markets.
Designing clustering-based web crawling policies for search engine crawlers
Authors: Qingzhao Tan, Prasenjit Mitra, C. Lee Giles
Venue: Proceedings of the sixteenth ACM conference on Conference on information and knowledge management (2007)

The World Wide Web is growing and changing at an astonishing rate. Web information systems such as search engines have to keep up with the growth and change of the Web. Due to resource constraints, search engines usually have difficulties keeping the local database completely synchronized with the Web. In this paper, we study how tomake good use of the limited system resource and detect as many changes as possible. Towards this goal, a crawler for the Web search engine should be able to predict the change behavior of the webpages. We propose applying clustering-based sampling approach. Specifically, we first group all the local webpages into different clusters such that each cluster contains webpages with similar change pattern. We then sample webpages from each cluster to estimate the change frequency of all the webpages in that cluster. Finally, we let the crawler re-visit the cluster containing webpages with higher change frequency with a higher probability. To evaluate the performance of an incremental crawler for a Web search engine, we measure both the freshness and the quality of the query results provided by the search engine. We run extensive experiments on a real Web data set of about 300,000 distinct URLs distributed among 210 websites. The results demonstrate that our clustering algorithm effectively clusters the pages with similar change patterns, and our solution significantly outperforms the existing methods in that it can detect more changed webpages and improve the quality of the user experience for those who query the search engine.
Main-memory operation buffering for efficient R-tree update
Authors: Laurynas Biveinis, Simonas Šaltenis, Christian S. Jensen
Venue: Proceedings of the 33rd international conference on Very large data bases (2007)

Emerging communication and sensor technologies enable new applications of database technology that require database systems to efficiently support very high rates of spatial-index updates. Previous works in this area require the availability of large amounts of main memory, do not exploit all the main memory that is indeed available, or do not support some of the standard index operations. Assuming a setting where the index updates need not be written to disk immediately, we propose an R-tree-based indexing technique that does not exhibit any of these drawbacks. This technique exploits the buffering of update operations in main memory as well as the grouping of operations to reduce disk I/O. In particular, operations are performed in bulk so that multiple operations are able to share I/O. The paper presents an analytical cost model that is shown to be accurate by empirical studies. The studies also show that, in terms of update I/O performance, the proposed technique improves on state of the art in settings with frequent updates.
High-level open evolvable systems design by process-oriented modeling: application to DNA replication mechanism
Authors: Behzad Bastani, Hoda Bastani
Venue: ACM SIGSOFT Software Engineering Notes (2007)

Open Evolvable Systems' design requires a methodological [1] and conceptual paradigm different from the conventional software design. Evolvable Systems' research [2, 6, 16, and 17] has established itself as a new research field, but the content is more domain-oriented than universal. Consequently, major contributions toward substantiation of that universal methodological and conceptual paradigm are yet to come. In this paper we present a new perspective and method for the general-purpose design of Evolvable Systems. The paper presents the attributes of the Evolvable Systems and discusses the distinction between Evolvable Systems' and conventional software design as well as the methodological ramifications. We pose and address the question of what is an efficient methodology for designing a system for which we do not know the boundaries? We present our version of Process-oriented Modeling as the key method in the high-level design of Evolvable Systems and show its utilization in implementation of one modeling case of a complex Evolvable System, the DNA replication process. We also present the dynamic aspects of the design process management and pre-code verifications in the framework of Quantified Controls and Simulations.
On the Performance of Shortest Path Routing Algorithms for Modeling and Simulation of Static Source Routed Networks -- an Extension to the Dijkstra Algorithm
Authors: Nuno M. Garcia, Przemyslaw Lenkiewicz, Mario M. Freire, Paulo P. Monteiro
Venue: Proceedings of the Second International Conference on Systems and Networks Communications (2007)

Shortest path routing algorithms, such as Dijkstra's algorithm present an overload problem when used to define routes for ring topologies in networks that implement source routing. This paper presents the effects of Dijkstra's shortest path routing in the simulation and modeling of static source routed networks, in particular we evaluated the effect of this routing scheme in the performance of Optical Burst Switched (OBS) networks. A new static shortest path algorithm is presented and its performance compared with the standard shortest path algorithm, using two new metrics. We propose the use of this routing algorithm in network simulators instead of standard Dijkstra, as it produces more symmetric and balanced routes over the network links, thus producing results that are closer to real networks which implement a more dynamic routing.
Bearing Fault Diagnosis Based on K-L Transform and Support Vector Machine
Authors: Shuang Lu, Fujin Yu, Jing Liu
Venue: Proceedings of the Third International Conference on Natural Computation - Volume 01 (2007)

In this paper, a new method of fault diagnosis based on K-L transform and support vector machine(SVM) is presented on the basis of statistical learning theory and the feature analysis of vibrating signal of ball bearing. The key to the fault bearings diagnosis is feature extracting and feature classifying. Multidimensional correlated variable is converted into low dimensional independent eigenvector by means of K-L transform. The pattern recognition and the nonlinear regression are achieved by the method of support vector machine. In the light of the feature of vibrating signals, eigenvector is obtained using K-L transform, fault diagnosis of ball bearing is recognized correspondingly using support vector machine multiple fault classifier. Theory and experiment show that the recognition of fault diagnosis of ball bearing based on K-L transform and support vector machine theory is available in the fault pattern recognizing and provides a new approach to the development of intelligent fault diagnosis.
Ordering Actions for Visibility
Authors: M. S. Mckendry
Venue: IEEE Transactions on Software Engineering (1985)

Several research projects are studying architectures for distributed computing that are founded on the notion of atomic actions operating on objects (instances of abstract data types). Such projects as Clouds at Georgia Tech and Archons at Carnegie-Mellon University are evaluating this approach as the foundation for constructing distributed operating systems. Objects are not new to operating systems. They provide substantial benefits in such dimensions as protection and synchronization, as well as their inherent organizational characteristics. This paper is concerned with synchronization to control ordering, a function often associated with objects. Conventional approaches require substantial extension for the action environment. Typically, they are based on (or equivalent to) general semaphores. Semaphores take no account of the visibility requirements of actions however, and consequently they can allow an action to progress beyond the point at which its effects can be undone. Also, they do not account for failures.
Outlier identification in high dimensions
Authors: Peter Filzmoser, Ricardo Maronna, Mark Werner
Venue: Computational Statistics Data Analysis (2008)

A computationally fast procedure for identifying outliers is presented that is particularly effective in high dimensions. This algorithm utilizes simple properties of principal components to identify outliers in the transformed space, leading to significant computational advantages for high-dimensional data. This approach requires considerably less computational time than existing methods for outlier detection, and is suitable for use on very large data sets. It is also capable of analyzing the data situation commonly found in certain biological applications in which the number of dimensions is several orders of magnitude larger than the number of observations. The performance of this method is illustrated on real and simulated data with dimension ranging in the thousands.
Insider attack and real-time data mining of user behavior
Authors: G. F. Anderson, D. A. Selby, M. Ramsey
Venue: IBM Journal of Research and Development (2007)

Early detection of employees' improper access to sensitive or valuable data is critical to limiting negative financial impacts to an organization, including regulatory penalties for misuse of customer data that results from these insider attacks. Implementing a system for detecting insider attacks is a technical challenge that also involves business-process changes and decision making that prioritizes the value of enterprise data. This paper focuses primarily on the techniques for detecting insider attacks, but also discusses the processes required to implement a solution. In particular, we describe a behavior-anomaly-based system for detecting insider attacks. The system uses peer-group profiling, composite feature modeling, and real-time statistical data mining. The analytical models are refined and used to update the real-time monitoring process. This continues in a cyclical manner as the system self-tunes. Finally, we describe an implementation of this detection approach in the form of the IBM Identity Risk and Investigation Solution (IRIS).
Image Reconstruction Based on Sub-Gaussian Random Projection
Authors: Hong Fong, Quanbing Zhang, Sui Wei
Venue: Proceedings of the Fourth International Conference on Image and Graphics (2007)

In this paper, we introduce the sub-Gaussian random projection into Compressed Sensing (CS) theory and present two new kinds of CS measurement matrices: sparse projection matrix and very sparse projection matrix. By the tail bounds for sub-Gaussian random projection, we present the proof of how these new matrices satisfying the necessary condition for CS measurement matrix. Further, we expatiate that owe to their sparsity, new matrices greatly simplify the projection operation during images reconstruction, which greatly improves the speed of reconstruction. The results of simulated and real experiments show that with a certain number of measurements, new matrices both achieve good measurement effect and can acquire exact reconstruction by them. Last, the comparison of reconstruction results respectively adopting new matrices and Gaussian measurement matrix is conducted.
Multiple Operand Addition and Multiplication
Authors: S. Singh
Venue: IEEE Transactions on Computers (1973)

The problem of adding k n-bit numbers, where k = 3 is considered. A novel scheme for adding such k numbers is described. Applying the bit-partitioning technique so that each partition contains m bits of each of these k numbers, where m=[log2(k-1)] is an integer = log2(k-1), the final sum can be obtained in m+1 addition cycles.
R69-8 Hybrid Computer Integration of Partial Differential Equations by Use of an Assumed Sum Separation of Variables
Authors: D. T. Greenwood
Venue: IEEE Transactions on Computers (1969)

The problem posed in this paper is the solution of Laplace's equation using the cylindrical coordinates r and z in an axially symmetric region. The boundary for this region consists of the surface r=b(z) and two end planes at z=0 and z=a. Assuming that the potential is specified on this boundary, the solution for V(r, z) is desired for all interior points. An example of an application is the design of an electron gun in which the solution for the electrostatic potential is used in computing electron trajectories. The ACM Portal is published by the Association for Computing Machinery. Copyright © 2010 ACM, Inc. Terms of Usage Privacy Policy Code of Ethics Contact Us Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real Player
Test Effort Estimation Models Based on Test Specifications
Authors: Eduardo Aranha, Paulo Borba
Venue: Proceedings of the Testing: Academic and Industrial Conference Practice and Research Techniques - MUTATION (2007)

In competitive markets, test teams should be able to estimate the required effort to perform their test activities on the schedule. In this paper, we present a test execution and a test automation effort estimation model and their use for test selection. All these models are based on the test specifications written in a controlled natural language. This characteristic may allow us to have better estimation accuracy, even for tests never executed before. The evaluation of these models and some additional benefits to industry are also discussed in the paper.
Characterization of strained silicon on relaxed SiGe layer made by H ion implantation and annealing in ultra-high vacuum ambient
Authors: Changchun Chen, Benhai Yu, Jiangfeng Liu, Qirun Dai
Venue: Microelectronic Engineering (2008)

Twenty-nanometer-thick Si cap layer/74-nm-thick Si"0"."7"2Ge"0"."2"8 epilayer/Si heterostructural sample was implanted by 25keV H^+ ion to a dose of 1x10^1^6cm^-^2 and subsequently annealed in ultra-high vacuum ambient at the temperature of 800^oC for 30min. Rutherford backscattering/ion channeling (RBS/C), Raman spectra, high resolution X-ray diffraction (HRXRD) and atomic force microscopy (AFM) were used to characterize the structural characteristic of Si/SiGe/Si heterostructure. Investigations by RBS/C demonstrate that the Si"0"."7"2Ge"0"."2"8 layer show good crystal quality (21.1% of channel minimum yield). The relaxation degree of partially relaxed Si"0"."7"2Ge"0"."2"8 layer was around 74%, which was obtained by HRXRD. The computation process of the relaxation degree of strain in SiGe layer according to HRXRD rocking curve was also thoroughly introduced. Raman analysis revealed that stress, @s and strain, @e in the thin strained-Si layer were around 1.2Gpa and 0.52%, respectively. In addition, the small surface roughness in the formed strained-Si/relaxed Si"0"."7"2Ge"0"."2"8 layer/Si heterostructural sample was observed via AFM image.
Assessing the Ability of Computation/Communication Overlap and Communication Progress in Modern Interconnects
Authors: Mohammad J. Rashti, Ahmad Afsahi
Venue: Proceedings of the 15th Annual IEEE Symposium on High-Performance Interconnects (2007)

Computation/communication overlap is one of the fundamental techniques in hiding communication latency. Independent progress support in messaging layer, network interface offload capability and application usage of non-blocking communications are believed to increase overlap and yield performance benefits. In this paper, we analyze four MPI implementations on top of three high-speed interconnects (InfiniBand, Myrinet and iWARP Ethernet) in their ability to support overlap and communication progress. The results confirm that the offload ability needs to be supported with communication progress to increase the level of overlap. Our progress engine micro-benchmark results show that in all examined networks transferring small messages makes an acceptable level of progress and overlap. On the other hand, in most cases, transferring large messages does not make progress independently, decreasing the chances of overlap in applications.
Gini Support Vector Machine: Quadratic Entropy Based Robust Multi-Class Probability Regression
Authors: Shantanu Chakrabartty, Gert Cauwenberghs
Venue: The Journal of Machine Learning Research (2007)

Many classification tasks require estimation of output class probabilities for use as confidence scores or for inference integrated with other models. Probability estimates derived from large margin classifiers such as support vector machines (SVMs) are often unreliable. We extend SVM large margin classification to GiniSVM maximum entropy multi-class probability regression. GiniSVM combines a quadratic (Gini-Simpson) entropy based agnostic model with a kernel based similarity model. A form of Huber loss in the GiniSVM primal formulation elucidates a connection to robust estimation, further corroborated by the impulsive noise filtering property of the reverse water-filling procedure to arrive at normalized classification margins. The GiniSVM normalized classification margins directly provide estimates of class conditional probabilities, approximating kernel logistic regression (KLR) but at reduced computational cost. As with other SVMs, GiniSVM produces a sparse kernel expansion and is trained by solving a quadratic program under linear constraints. GiniSVM training is efficiently implemented by sequential minimum optimization or by growth transformation on probability functions. Results on synthetic and benchmark data, including speaker verification and face detection data, show improved classification performance and increased tolerance to imprecision over soft-margin SVM and KLR.