ppxscal/embedding_network huggingface dataset:
Top Management Team Heterogeneity: Personality, Power, and Proxies
Authors: Patricia Pitcher, Anne D. Smith
Venue: Organization Science (2001)

This article reports partial results of an eight-year field study of the Top Management Teams (TMTs) of a global multidivisional financial services corporation and compares those results with large-sample work in the TMT literature. In particular, it investigates the operationalization of TMT cognitive diversity by the proxies of age, team tenure, industry experience, and functional background heterogeneity most often used in statistical work, and compares those operationalizations with cognitive diversity itself. In addition to highlighting which proxies seemed to most closely approximate cognitive diversity and why, it demonstrates the confounding impact of power on all operationalizations. A comparison of the field results with three representative studies with respect to the operationalization of the dependent variables of diversification, innovation, and performance helps to explain why previous TMT heterogeneity research has often produced inconsistent results or nonfindings. It offers some suggestions that should improve the robustness of statistical research and demonstrates the reciprocal usefulness of case and large-sample research.
Channeling innovation
Authors: James L. Fahey
Venue: Ubiquity (2002)

Despite its importance to business, innovation can be a confusing distraction. An effective process for managing innovation allows organizations to respond to markets while remaining focused on business objectives.
Recursive-Based PCG Methods for Toeplitz Systems with Nonnegative Generating Functions
Authors: Michael K. Ng, Hai-Wei Sun, Xiao-Qing Jin
Venue: SIAM Journal on Scientific Computing (2002)

In this paper, we consider the solutions of symmetric positive definite, but ill-conditioned, Toeplitz systems An x = b. Here we propose to solve the system by the recursive-based preconditioned conjugate gradient method. The idea is to use the inverse of Am (the principal submatrix of An with the Gohberg--Semencul formula as a preconditioner for An. The inverse of Am can be generated recursively by using the formula until m is small enough. The construction of the preconditioners requires only the entries of An and does not require the explicit knowledge of the generating function f of An. We show that if f is a nonnegative, bounded, and piecewise continuous even function with a finite number of zeros of even order, the spectra of the preconditioned matrices are uniformly bounded except for a fixed number of outliers. Hence the conjugate gradient method, when applied to solving the preconditioned system, converges very quickly. Numerical results are included to illustrate the effectiveness of our approach.
A Finite Algorithm for a Class of Nonlinear Multiplicative Programs
Authors: R. Cambini, C. Sodini
Venue: Journal of Global Optimization (2003)

The nonconvex problem of minimizing the product of a strictly convex quadratic function and the p-th power of a linear function over a convex polyhedron is considered. Some theoretical properties of the problem, such as the existence of minimum points and the generalized convexity of the objective function, are deepened on and a finite algorithm which solves the problem is proposed.
Facilitator Influence in Group Support Systems: Intended and Unintended Effects
Authors: Terri L. Griffith, Mark A. Fuller, Gregory B. Northcraft
Venue: Information Systems Research (1998)

This paper addresses facilitation, a developing area of Group Support Systems (GSS) research. The facilitator role is one of improving a group's communication and information flow; facilitators are meant to enhance the manner in which a group makes decisions without making those decisions for the group. However, there is a paradox in facilitation: The influence required to facilitate a group changes the group's outcomes. Additionally, strict impartiality for facilitation may be too much to expect because facilitators may unintentionally bias group outcomes, or because facilitators may have their own agendas. Acknowledgment, training, and standards for facilitators may prove useful ways for groups to retain the benefits of facilitation without incurring the costs of inappropriate facilitator influence. Implications are drawn for new research acknowledging the complexity of the GSS sociotechnical system, and the importance of sociotechnical facilitation in organizations.
MPICH-V: toward a scalable fault tolerant MPI for volatile nodes
Authors: George Bosilca, Aurelien Bouteiller, Franck Cappello, Samir Djilali, Gilles Fedak, Cecile Germain, Thomas Herault, Pierre Lemarinier, Oleg Lodygensky, Frederic Magniette, Vincent Neri, Anton Selikhov
Venue: Proceedings of the 2002 ACM/IEEE conference on Supercomputing (2002)

Global Computing platforms, large scale clusters and future TeraGRID systems gather thousands of nodes for computing parallel scientific applications. At this scale, node failures or disconnections are frequent events. This Volatility reduces the MTBF of the whole system in the range of hours or minutes.We present MPICH-V, an automatic Volatility tolerant MPI environment based on uncoordinated checkpoint/rollback and distributed message logging. MPICH-V architecture relies on Channel Memories, Checkpoint servers and theoretically proven protocols to execute existing or new, SPMD and Master-Worker MPI applications on volatile nodes.To evaluate its capabilities, we run MPICH-V within a framework for which the number of nodes, Channels Memories and Checkpoint Servers can be completely configured as well as the node Volatility. We present a detailed performance evaluation of every component of MPICH-V and its global performance for non-trivial parallel applications. Experimental results demonstrate good scalability and high tolerance to node volatility.
On the Parallel Execution Time of Tiled Loops
Authors: Karin Högstedt, Larry Carter, Jeanne Ferrante
Venue: IEEE Transactions on Parallel and Distributed Systems (2003)

Many computationally-intensive programs, such as those for differential equations, spatial interpolation, and dynamic programming, spend a large portion of their execution time in multiply-nested loops that have a regular stencil of data dependences. Tiling is a well-known compiler optimization that improves performance on such loops, particularly for computers with a multileveled hierarchy of parallelism and memory. Most previous work on tiling is limited in at least one of the following ways: they only handle nested loops of depth two, orthogonal tiling, or rectangular tiles. In our work, we tile loop nests of arbitrary depth using polyhedral tiles. We derive a prediction formula for the execution time of such tiled loops, which can be used by a compiler to automatically determine the tiling parameters that minimizes the execution time. We also explain the notion of rise, a measure of the relationship between the shape of the tiles and the shape of the iteration space generated by the loop nest. The rise is a powerful tool in predicting the execution time of a tiled loop. It allows us to reason about how the tiling affects the length of the longest path of dependent tiles, which is a measure of the execution time of a tiling. We use a model of the tiled iteration space that allows us to determine the length of the longest path of dependent tiles using linear programming. Using the rise, we derive a simple formula for the length of the longest path of dependent tiles in rectilinear iteration spaces, a subclass of the convex iteration spaces, and show how to choose the optimal tile shape.
A Fast Multithreaded Out-of-Core Visualization Technique
Authors: Peter Sulatycke, Kanad Ghose
Venue: Proceedings of the 13th International Symposium on Parallel Processing and the 10th Symposium on Parallel and Distributed Processing (1999)

Out-of-core rendering techniques are necessary for viewing large volume disk-resident data sets produced by many scientific applications or high resolution imaging systems. Traditional visualizers can provide real-time performance but require all of the data to be viewed to be in the RAM.We describe a multithreaded implementation of an out-of-core isosurface renderer that does not impose such restrictions and yet provides performance that scales well with the size of the data. Our renderer uses an interval tree data structure on disk with a layout that reduces disk seeks to read out only the relevant data from the disk. The low resulting disk latencies are hidden by using prefetching and multithreading to overlap the activities of the rendering computations and disk accesses. Our renderer outperforms the out-of-core isosurface renderer of the well-known vtk toolkit by about one order of magnitude and several orders of magnitude when compared against vtk toolkit's optimized in-core algorithm on large representative CT scan data. The multithreaded version also scales well with the number of threads.
A Pattern Reordering Approach Based on Ambiguity Detection for Online Category Learning
Authors: Eric Granger, Yvon Savaria, Pierre Lavoie
Venue: IEEE Transactions on Pattern Analysis and Machine Intelligence (2003)

Pattern reordering is proposed as an alternative to sequential and batch processing for online category learning. Upon detecting that the categorization of a new input pattern is ambiguous, the input is postponed for a predefined time, after which it is reexamined and categorized for good. This approach is shown to improve the categorization performance over purely sequential processing, while yielding a shorter input response time, or latency, than batch processing. In order to examine the response time of processing schemes, the latency of a typical implementation is derived and compared to lower bounds. Gaussian and softmax models are derived from reject option theory and are considered for detecting ambiguity and triggering pattern postponement. The average latency and Rand Adjusted clustering score of reordered, sequential, and batch processing are compared through computer simulation using two unsupervised competitive learning neural networks and a radar pulse data set.
The ToolFinger: supporting complex direct manipulation in virtual environments
Authors: Gerold Wesche
Venue: Proceedings of the workshop on Virtual environments 2003 (2003)

Virtual environments (VEs) such as the Responsive Workbench were designed to support interactive, complex applications. The possibility of direct manual interaction with virtual objects, using both hands in a natural, intuitive way is one of the great advantages of such configurations. The related work on interaction techniques for these environments is mainly concentrated on hand-oriented, spatial manipulation. With increasing complexity of applications, application control issues become more relevant, including the problem of tool selection. In this paper, we propose a new interaction technique, optimized for handling tool selection tasks comfortably, called the ToolFinger. The ToolFinger is a hand held 3D widget, resembling a pen, to which a set of tools is assigned in a way that selecting and applying a tool are no longer two separated tasks. The ToolFinger concept allows a fluent integration of tool selections and tool switches with the workflow of geometry editing. It benefits complex manipulation tasks in applications such as immersive geometric modelling, or interactive visualisation.
A randomized subexponential algorithm for parity games
Authors: Viktor Petersson, Sergei Vorobyov
Venue: Nordic Journal of Computing (2001)

We describe a randomized algorithm for Parity Games (equivalent to the Mu-Calculus Model Checking), which runs in expected time 2O(k1/(1+2epsilon)) when k is Omega(n1/2+epsilon), n is the number of vertices, and 0 > epsilon >= 1/2. That is, our algorithm is subexponential in the number of colors k of the game graph provided that k is not too small. All previously known algorithms were exponential in the number of colors, with the best one taking time and space O(k2 n sqrt(n)k). Our algorithm does not rely on Linear Programming subroutines and uses a low-degree polynomial space.
An investment in tomorrow's university students: enhancing the multimedia skills of today's K-12 teachers
Authors: John Minor Ross
Venue: Journal of Computing Sciences in Colleges (2001)

Teaching multimedia to computing majors is no longer new. The multimedia course experiences reported on herein, however, put a new slant on the topic-because of the target audience. Instead of narrowly focusing on traditional students, this course was designed, in addition, to develop the multimedia skills of classroom teachers, both inservice and preservice. The course pedagogy and target audience interests are outlined with only passing mentions of specific software. This is based on the belief that university computing professors should strive to understand K-12 problems before they offer technology solutions. Some fresh classroom challenges for teachers and professors, as well as possible far-reaching benefits, are also noted.
Sparse squares of polynomials
Authors: John Abbott
Venue: Mathematics of Computation (2002)

We answer a question left open in an article of Coppersmith and Davenport which proved the existence of polynomials whose powers are sparse, and in particular polynomials whose squares are sparse (i.e., the square has fewer terms than the original polynomial). They exhibit some polynomials of degree 12 having sparse squares, and ask whether there are any lower degree complete polynomials with this property. We answer their question negatively by reporting that no polynomial of degree less than 12 has a sparse square, and explain how the substantial computation was effected using the system CoCoA.
Mobile robot control using intelligent agents
Authors: K. Figueiredo, M. Vellasco, M. A. Pacheco
Venue: Second international workshop on Intelligent systems design and application (2002)

The agents' theory offers flexibility for solution of problems whose environment is dynamic and imprecise. The use of the computational intelligence together with the agents' theory seems to be a natural way of providing an agent with intelligence. In this paper we describe the use of intelligent agents, whose intelligence is based on a fuzzy logic system, applied to the control of a robot, simulated by the Khepera simulator [1]. Fuzzy Logic Systems have demonstrated, through the numerous applications in the area, to be an effective procedure for control problems [2][3]. The attitude to be taken at each moment by an agent is defined by a set of fuzzy rules based upon the robot position, its sensor values, distance and angle relative to the target. To prevent the robot from getting stuck by some obstacles, a path memory system was created, forcing the robot to seek new alternatives when it gets trapped [4]. The results obtained demonstrate a successful combination of Computational Intelligence and the Theory of Agents in a control system with ability to avoid deadlock situations.
Information Privacy Concerns, Procedural Fairness, and Impersonal Trust: An Empirical Investigation
Authors: Mary J. Culnan, Pamela K. Armstrong
Venue: Organization Science (1999)

This research addresses the tensions that arise between the collection and use of personal information that people provide in the course of most consumer transactions, and privacy. In today's electronic world, the competitive strategies of successful firms increasingly depend on vast amounts of customer data. Ironically, the same information practices that provide value to organizations also raise privacy concerns for individuals. This study hypothesized that organizations can address these privacy concerns and gain business advantage through customer retention by observing procedural fairness: customers will be willing to disclose personal information and have that information subsequently used to create consumer profiles for business use when there are fair procedures in place to protect individual privacy. Because customer relationships are characterized by social distance, customers must depend on strangers to act on their behalf. Procedural fairness serves as an intermediary to build trust when interchang eable organizational agents exercise considerable delegated power on behalf of customers who cannot specify or constrain their behavior. Our hypothesis was supported as we found that when customers are explicitly told that fair information practices are employed, privacy concerns do not distinguish consumers who are willing to be profiled from those who are unwilling to have their personal information used in this way.
A Multiclass Hybrid Production Center in Heavy Traffic
Authors: James S. Dyer, Thomas Edmunds, John C. Butler, Jianmin Jia, Vien Nguyen
Venue: Operations Research (1998)

This paper presents an analysis of a single-stage hybrid production system that makes multiple types of products, some of which are made to-order while others are made to-stock. The analysis begins with a formal heavy traffic limit theorem of the production system, which is modeled as a mixed queueing network. Taking insights from the limit theorem, the analysis continues with the development of an approximation procedure. Numerical experiments indicate that this procedure provides good estimates for performance measures such as fill rates and average inventory levels.
The graph model for conflict resolution with information-gap uncertainty in preferences
Authors: Yakov Ben-Haim, Keith W. Hipel
Venue: Applied Mathematics and Computation (2002)

Information-gap models, for formally modeling the uncertainty of preferences of decision makers involved in a conflict, are devised for employment with the graph model for conflict resolution. These information-gap models are designed for handling a variety of situations for expressing severe preference-uncertainty of a decision maker, including both transitive and intransitive preferences among the states or possible scenarios in a conflict. Applications of these decision technologies to the game of chicken and the Cuban Missile Crisis of 1962 illustrate how the information-gap models can be conveniently utilized in practice and how strategic insights can be gained through rigorous examination of the robustness of equilibrium solutions to uncertainty in preferences. It is also shown that uncertainty-analyses can lead to modification of a decision maker's prior preferences.
Clustering based acyclic multi-way partitioning
Authors: Eric S. H. Wong, Evangeline F. Y. Young, W. K. Mak
Venue: Proceedings of the 13th ACM Great Lakes symposium on VLSI (2003)

In this paper, we present a clustering based algorithm for acyclic multi-way partitioning. Many existing partitioning algorithms have shown that clustering can effectively improve the solution quality. However, most of them do not consider the signal direction and thus cannot maintain the acyclic property. Our algorithm is based on clustering by computing the modified fan-out free cones. Fan-out free cone clustering can reduce a graph to a smaller and sparser one, and maintain the acyclic property at the same time. Experimental results showed that our algorithm compares favorably with the previous best acyclic multi-way partitioning algorithm in cut-size.
Towards a comprehensive collection of diagnostic patterns for protein sequence classification
Authors: Björn Olsson, Kim Laurio
Venue: Information Sciences&mdash;Informatics and Computer Science: An International Journal (2002)

The PROSITE collection of patterns for family classification of protein sequences requires much manual labour for motif finding and pattern updating, and yet has only moderate classification accuracy. Out of 1026 families with patterns in PROSITE release 16.0, there was only 523 (51%) with a diagnostic pattern, i.e., a pattern which discriminates perfectly between family and non-family sequences in the training set. Therefore, there is a need to find reliable methods for automating the processes of motiffinding and pattern construction, so that improved speed can be combined with greater classification accuracy.In this paper we present our approach to automating the construction of a collection of patterns, and we announce release 1.0 of the pattern collection built by motif-finding by analysis of multiple alignments (MAMA). MAMA is found to improve the classification accuracy over PROSITE by finding many more diagnostic patterns. On 926 tested families, MAMA finds such patterns for 771 (83%). Furthermore, both the average specificity and sensitivity of MAMA patterns are found to be higher than for PROSITE.A WWW interface that allows users to submit sequences and scan for matches in the MAMA pattern collection is available, together with a listing of all the patterns in MAMA release 1.0.
Changes in syllable magnitude and timing due to repeated correction
Authors: Caroline Menezes, Bryan Pardo, Donna Erickson, Osamu Fujimura
Venue: Speech Communication (2003)

In a semi-spontaneous conversational setting, subjects were made to repeat the same correction of one digit in a three-digit sequence consisting of "five" or "nine" followed by "Pine Street". Articulatory and acoustic signals were recorded by the University of Wisconsin Microbeam Facility for four speakers of American English. By analyzing jaw movements, syllable magnitude and time values were evaluated, to represent the rhythmic organization of the utterance by a linear string of syllable pulses. Preliminary results suggest that not only does the magnitude of the corrected syllable increase by the correction of a digit, but also, in most cases, there is some systematic increase of syllable magnitude both in the corrected digit and other digits in the same utterance, as the same correction is repeated. Considerable difference among different speakers is observed and discussed in terms of syllable magnitude and timing patterns.
Algorithms for Hybrid MILP/CP Models for a Class of Optimization Problems
Authors: Vipul Jain, Ignacio E. Grossmann
Venue: INFORMS Journal on Computing (2001)

The goal of this paper is to develop models and methods that use complementary strengths of Mixed Integer Linear Programming (MILP) and Constraint Programming (CP) techniques to solve problems that are otherwise intractable if solved using either of the two methods. The class of problems considered in this paper have the characteristic that only a subset of the binary variables have non-zero objective function coefficients if modeled as an MILP. This class of problems is formulated as a hybrid MILP/CP model that involves some of the MILP constraints, a reduced set of the CP constraints, and equivalence relations between the MILP and the CP variables. An MILP/CP based decomposition method and an LP/CP-based branch-and-bound algorithm are proposed to solve these hybrid models. Both these algorithms rely on the same relaxed MILP and feasibility CP problems. An application example is considered in which the least-cost schedule has to be derived for processing a set of orders with release and due dates using a set of dissimilar parallel machines. It is shown that this problem can be modeled as an MILP, a CP, a combined MILP-CP OPL model (Van Hentenryck 1999), and a hybrid MILP/CP model. The computational performance of these models for several sets shows that the hybrid MILP/CP model can achieve two to three orders of magnitude reduction in CPU time.