Identifying and overcoming the challenges of implementing a project management office

With the ongoing challenge of successfully managing information technology (IT) projects, organizations are recognizing the need for greater project management discipline. For many organizations, this has meant ratcheting up project management skills, processes, and governance structures by implementing a project management office (PMO). While anecdotal evidence suggests that implementing a PMO can be quite difficult, few studies discuss the specific challenges involved, and how organizations can overcome them. To address this gap in existing knowledge, we conducted a Delphi study to (1) identify the challenges of implementing a PMO for managing IT projects, (2) rank these challenges in order of importance, (3) discover ways in which some organizations have overcome the top-ranked challenges, and (4) understand the role of PMO structure, metrics, and tools in the implementation of a PMO.We identified 34 unique challenges to implementing a PMO and refined this list to 13 challenges that our Delphi panelists considered most important. The top-three challenges were (1) rigid corporate culture and failure to manage organizational resistance to change, (2) lack of experienced project managers (PMs) and PMO leadership, and (3) lack of appropriate change management strategy. Through follow-up interviews with selected panelists, we identified a series of actions that can be taken to overcome these challenges including having a strong PMO champion, starting small and demonstrating the value of the PMO, obtaining support from opinion leaders, hiring an experienced program manager who understands the organization, bringing the most talented PMs into the PMO implementation team, adopting a flexible change management strategy, and standardizing processes prior to PMO implementation. The interviews were also used to better understand the role of PMO structure, metrics, and tools. In terms of PMO structure, we found that ‘light’ PMOs were more likely to be implemented successfully. Most organizations eschew formal metrics, instead relying on subjective indicators of PMO success. Lastly, it appears that PMO tools are difficult to implement unless a project management culture has been established.     

Intelligent adaptive observer-based optimal control of overhead transmission line de-icing robot manipulator

In cold season, wet snow ice accretion on overhead transmission lines increases wind load effects which in turn increases line tension. This increased line tension causes undesirable effects in power systems. This paper discusses the design of an observer-based boundary sliding mode control (BSMC) for 3 DOF overhead transmission line de-icing robot manipulator (OTDIRM). A robust radial basis functional neural network (RBFNN) observer-based neural network (NN) controller is developed for the motion control of OTDIRM, which is a combination of BSMC, NN approximation and adaptation law. The RBFNN-based adaptive observer is designed to estimate the positions and velocities. The weights of both NN observer and NN approximator are tuned off-line using particle swarm optimization. Using Lyapunov analysis the closed loop tracking error was verified for a 3 DOF OTDIRM. Finally, the robustness of the proposed neural network-based adaptive observer boundary sliding mode control (NNAOBSMC) was verified against the input disturbances and uncertainties.     

Beyond utilitarian factors: User experience and travel company website successes

Travel websites are extensively used by travelers for their travel bookings, yet little is known about the hedonic effectiveness of such experiences for the customer. The end users of these websites are customers who may not always be sophisticated information system (IS) users. Further, traditional utility based measures of customer evaluation are dated with respect to the interactive nature of the technology in use and the hedonic benefits that may result from the use of the technology. The evaluation of IS needs to include hedonic measures facilitated by the interactive technology in addition to the traditional utility based measures. We propose and test an evaluation model for retail travel websites that combines the traditional utility based measures with hedonic measures which collectively create a more comprehensive measure for the IS evaluation of consumer focused websites. Thus rooted in theory, the model extends DeLone and McLean’s model of IS Success by adding the construct of User Experience. The model was tested on a sample of 255 customers of travel websites targeted at the Indian market. The results indicate that both utility based and hedonic measures are important factors for customer IS (travel website in this study) evaluation. The larger implications for theory and practice of IS evaluation are explained.     

Universal instability modes in internal and external flows

Two prototypical external and internal flows have been studied which display linear temporal instability followed by nonlinear saturation taking the flows to a new equilibrium state. Direct simulation results are obtained using a specific formulation and numerical methods with very high accuracy. These results are analyzed via proper orthogonal decomposition (POD), which reveal similar modes for flow past a circular cylinder and flow inside a lid-driven cavity, indicating universality of such modes. Unlike many other efforts on reduced order modeling via POD, here the emphasis has been on understanding the physical aspect of the flow instability which requires very high accuracy of the simulation. Then, the obtained POD modes are related to the instability modes (in the classical sense of defining the latter) and new generic types of instability modes are identified in the studied external and internal flows. These new modes have been reported for flow past a circular cylinder [Sengupta TK, Singh N, Suman VK. Dynamical system approach to instability of flow past a circular cylinder. J Fluid Mech 2010;656:82–115] which help one in understanding the instability sequence and the relative importance of these modes in the flow evolution starting from an impulsive start. Present comparative study, furthermore, reveals universality of such instability modes by showing their presence for the flow inside a lid-driven cavity as well. Despite seeming dissimilarities between these two flows, similarities between the instability portrait of these two flows suggest universality of such modes. From the equilibrium amplitude of vorticity time-series, we establish the presence of multiple modes and multiple bifurcation sequences for these flows in parameter space. Existing theory due to Landau and Stuart that considers only a single dominant mode and its self-interaction does not explain all these features. We invoke a multi-modal interaction model in the cited reference above, termed as Landau–Stuart–Eckhaus (LSE) equation in recognition of Eckhaus’ work in modifying the classical Stuart–Landau equation. We also show that the new instability modes do not follow either the classical Stuart–Landau or the newly proposed LSE model equations and for this reason we call these as anomalous modes. Two specific classes of anomalous modes are identified and classified in the present work. Empirical expressions for the evolution of these anomalous modes are presented and their unambiguous role during instabilities is discussed.     

Timestamping messages and events in a distributed system using synchronous communication

Determining order relationship between events of a distributed computation is a fundamental problem in distributed systems which has applications in many areas including debugging, visualization, checkpointing and recovery. Fidge/Mattern’s vector-clock mechanism captures the order relationship using a vector of size N in a system consisting of N processes. As a result, it incurs message and space overhead of N integers. Many distributed applications use synchronous messages for communication. It is therefore natural to ask whether it is possible to reduce the timestamping overhead for such applications. In this paper, we present a new approach for timestamping messages and events of a synchronously ordered computation, that is, when processes communicate using synchronous messages. Our approach depends on decomposing edges in the communication topology into mutually disjoint edge groups such that each edge group either forms a star or a triangle. We show that, to accurately capture the order relationship between synchronous messages, it is sufficient to use one component per edge group in the vector instead of one component per process. Timestamps for events are only slightly bigger than timestamps for messages. Many common communication topologies such as ring, grid and hypercube can be decomposed into edge groups, resulting in almost 50% improvement in both space and communication overheads. We prove that the problem of computing an optimal edge decomposition of a communication topology is NP-complete in general. We also present a heuristic algorithm for computing an edge decomposition whose size is within a factor of two of the optimal. We prove that, in the worst case, it is not possible to timestamp messages of a synchronously ordered computation using a vector containing fewer than components when N ≥ 2. Finally, we show that messages in a synchronously ordered computation can always be timestamped in an offline manner using a vector of size at most . An earlier version of this paper appeared in 2002 Proceedings of the IEEE International Conference on Distributed Computing Systems (ICDCS). The author V. K. Garg was supported in part by the NSF Grants ECS-9907213, CCR-9988225, an Engineering Foundation Fellowship. This work was done while the author C. Skawratananond was a Ph.D. student at the University of Texas at Austin.     

Efficient computation of Morse-Smale complexes for three-dimensional scalar functions

The Morse-Smale complex is an efficient representation of the gradient behavior of a scalar function, and critical points paired by the complex identify topological features and their importance. We present an algorithm that constructs the Morse-Smale complex in a series of sweeps through the data, identifying various components of the complex in a consistent manner. All components of the complex, both geometric and topological, are computed, providing a complete decomposition of the domain. Efficiency is maintained by representing the geometry of the complex in terms of point sets.     

Clustering categorical data: an approach based on dynamical systems

We describe a novel approach for clustering collections of sets, and its application to the analysis and mining of categorical data. By “categorical data,” we mean tables with fields that cannot be naturally ordered by a metric – e.g., the names of producers of automobiles, or the names of products offered by a manufacturer. Our approach is based on an iterative method for assigning and propagating weights on the categorical values in a table; this facilitates a type of similarity measure arising from the co-occurrence of values in the dataset. Our techniques can be studied analytically in terms of certain types of non-linear dynamical systems. Received February 15, 1999 / Accepted August 15, 1999     

Residual phosphate fertilizer compounds in soils

A variety of P compounds can accumulate in soils as residues of fertilizer and may influence soil test versus plant yield relationships. This work evaluates specific chemical extractants for their capacity to identify such Al, Fe and Ca phosphates in soils as a basis for increasing the precision of yield prediction. Aluminium phosphate, iron phosphate, calcium phosphate (apatite) and P sorbed onto gibbsite, goethite and calcite were added to four Western Australian lateritic soils. These soils were then subjected to sequential selective extraction using a modified Chang and Jackson procedure in order to evaluate the selectivity of these extractants for the different forms of P with the sequence of extraction: 1 M NH₄Cl, 0.5 M NH₄F, 0.1 M NaOH + 1 M NaCl, citrate-dithionite-bicarbonate (CDB), 1 M NaOH and 1 M HCl. The results show that the procedure is not sufficiently specific and thus might be of little value for estimating the forms and amounts of residues of phosphate rock fertilizers in soils.     

Principle Component Analysis in Conjuction with Data Driven Methods for Sediment Load Prediction

This study investigates sediment load prediction and generalization from laboratory scale to field scale using principle component analysis (PCA) in conjunction with data driven methods of artificial neural networks (ANNs) and genetic algorithms (GAs). Five main dimensionless parameters for total load are identified by using PCA. These parameters are used in the input vector of ANN for predicting total sediment loads. In addition, nonlinear equations are constructed, based upon the same identified dimensionless parameters. The optimal values of exponents and constants of the equations are obtained by the GA method. The performance of the so-developed ANN and GA based methods is evaluated using laboratory and field data. Results show that the expert methods (ANN and GA), calibrated with laboratory data, are capable of predicting total sediment load in field, thus showing their transferability. In addition, this study shows that the expert methods are not transferable for suspended load, perhaps due to insufficient laboratory data. Yet, these methods are able to predict suspended load in field, when trained with respective field data.     

A system for debugging via online tracing and dynamic slicing

Dynamic slicing is a promising trace based technique that helps programmers in the process of debugging. In order to debug a failed run, dynamic slicing requires the dynamic dependence graph (DDG) information for that particular run. The two major challenges involved in utilizing dynamic slicing as a debugging technique are the efficient computation of the DDG and the efficient computation of the dynamic slice, given the DDG. In this paper, we present an efficient debugger, which first computes the DDG efficiently while the program is executing; dynamic slicing is later performed efficiently on the computed DDG, on demand. To minimize program slowdown during the online computation of DDG, we make the design decision of not outputting the computed dependencies to a file, instead, storing them in memory in a specially allocated fixed size circular buffer. The size of the buffer limits the length of the execution history that can be stored. To maximize the execution history that can be maintained, we introduce optimizations to eliminate the storage of most of the generated dependencies, at the same time ensuring that those that are stored are sufficient to capture the bug. Experiments conducted on CPU‐intensive programs show that our optimizations are able to reduce the trace rate from 16 to 0.8 bytes per executed instruction. This enables us to store the dependence trace history for a window of 20 million executed instructions in a 16‐MB buffer. Our debugger is also very efficient, yielding slicing times of around a second, and only slowing down the execution of the program by a factor of 19 during the online tracing step. Using recently proposed architectural support for monitoring, we are also able to handle multithreaded programs running on multicore processors. Copyright © 2011 John Wiley & Sons, Ltd.