Sociomaterial bricolage: The creation of location-spanning work practices by global software developers

Context

Studies on global software development have documented severe coordination and communication problems among coworkers due to geographic dispersion and consequent dependency on technology. These problems are exacerbated by increase in the complexity of work undertaken by global teams. However, despite these problems, global software development is on the rise and firms are adopting global practices across the board, raising the question: What does successful global software development look like and what can we learn from its practitioners?

Objective

This study draws on practice-based studies of work to examine successful work practices of global software developers. The primary aim of this study was to understand how workers develop practices that allow them to function effectively across geographically dispersed locations.

Method

An ethnographically-informed field study was conducted with data collection at two international locations of a firm. Interview, observation and archival data were collected. A total of 42 interviews and 3 weeks of observations were conducted.

Results

Teams spread across different locations around the world developed work practices through sociomaterial bricolage. Two facets of technology use were necessary for the creation of these practices: multiplicity of media and relational personalization at dyadic and team levels. New practices were triggered by the need to achieve a work-life balance, which was disturbed by global development. Reflecting on my role as a researcher, I underscore the importance of understanding researchers’ own frames of reference and using research practices that mirror informants’ work practices.

Conclusion

Software developers on global teams face unique challenges which necessitate a shift in their work practices. Successful teams are able to create practices that span locations while still being tied to location based practices. Inventive use of material and social resources is central to the creation of these practices.     

A simulation framework for evolution on uneven terrains for synchronous drive robot

This paper presents a simulation framework for evolution on uneven terrains for a wheeled mobile robot (WMR) such as a synchronous drive robot. The framework lends itself as a tool capable of solving various problems, such as forward kinematic-based evolution, inverse kinematic-based evolution, path planning and trajectory tracking. This framework becomes particularly useful when we understand that the evolution problem (and hence, the various associated problems based on evolution) is particularly challenging on uneven terrain. Specifically, it is entailed to bring in the contact constraints posed by the interaction of the wheel and the ground as well as the holonomic constraints as the problem is formulated in a Differential Algebraic Equation setting. The problem becomes all the more crucial as vehicles moving on uneven terrain are becoming the order of the day. Nonetheless, there has not been much literature that deals in length the various aspects that go into the framework. This paper elaborates on the various aspects of the framework, presents simulation results on uneven terrain, where the vehicle evolves without slipping, and also presents substantial quantitative analysis in regard to wheel slippage. The main contributions of this paper are the motion planning using forward kinematic framework and a new formulation of inverse kinematics for wheeled robots on uneven terrains.     

Estimation of operating blast furnace reactor invisible interior surface using Differential Evolution

A blast furnace reactor that transforms processed minerals into liquid iron is the most important link in a steel making process chain. Estimating the condition of refractory shield in a running furnace is important for production campaign planning and hazardous leakage prevention. A method coupling Differential Evolution with heat transfer simulations is developed for estimating refractory inner surface within process real times. The fitness value that drives this evolutionary algorithm is calculated from the differences between temperatures measured from thermocouples embedded in the refractory, and those obtained from numerical solution of the heat transfer equations. A population of different refractory inner surfaces constitutes the candidate solution set. These evolving surfaces tend to become craggy which impact variably on accuracy of numerical solution with significant consequence on the final synthesized solution. These inter-candidate accuracy variations are neutralized by transforming each physical refractory grid configuration onto identical rectangular computational domains using a set of continuity-ensuring elliptic partial differential equations. The heat transfer equation is correspondingly transformed into the computational space and solved within a finite difference framework. A set of practical constraints are imposed on the Differential Evolution algorithm to guide evolution toward the optimal surface that best represents the measured temperatures. Rigorous verification of the various stages of development facilitating industrial acceptance of the method are presented. This simulation-embedded evolutionary inverse-design approach can be used generically for online estimation of unobservable critical parameters of infrastructure, equipment and processes in diverse domains.     

On-demand waypoints for live P2P video broadcasting

A peer-to-peer architecture has emerged as a promising approach to enabling the ubiquitous deployment of live video broadcasting on the Internet. However the performance in these architectures is unpredictable and fundamentally constrained by the characteristics of the members participating in the broadcast. By characteristics, we refer to user dynamics, out-going bandwidth connectivity, whether the member is behind NAT/firewall, and the network conditions among participating members. While several researchers have looked at hybrid P2P/CDN approaches to address these issues, such approaches require provisioning of centralized server resources prior to a broadcast, which complicates the goal of ubiquitous video broadcasting. In this paper, we explore an alternative architecture where users are willing to donate their bandwidth resources to a broadcast event, even though they are not a participant in the event. Such users constitute what we term a waypoint community. Any given broadcast event involves constructing overlays only based on participants to the extent possible, however waypoints may be dynamically invoked in an on-demand, performance-driven fashion to improve the performance of a broadcast. We present the design of a system built on this idea. Detailed results from trace-driven experiments over the PlanetLab distributed infrastructure and Emulab demonstrate the potential of the waypoint architecture to improve the performance of purely P2P-based overlays.     

A framework for business process modeling by QoS-based pruning

In this paper, we have proposed a methodology towards improved business process model redesign based on QoS. We have extended an existing framework that generates an exhaustive space of process models from a set of capability library. The solution space is pruned based on goal and constraints considered thereafter. An algebraic framework is deployed that permits integrated multi-dimensional assessments of QoS factors for choosing path from the reduced space towards derivation of an optimal business process model by comparing the QoS values on both quantitative and qualitative scales. The proposed methodology ensures that while deriving a solution, no possible superior business process model is left out. Further, the designs that do not satisfy the given constraints are eliminated. Eventually, the extended and improved framework provides a comprehensive, both syntactically and semantically correct, consistent and improved business process that adheres to the target business goals and constraints specific to a business house. A use case is used to describe our methodology.     

Effect of phosphorus content on Cu/Ni-P/Sn-3.5Ag solder joint strength after multiple reflows

Electroless Ni-P layers with three different P contents (6.1 wt.%, 8.8 wt.%, and 12.3wt.%) were deposited on copper (Cu) substrates. Multilayered samples of Sn-3.5Ag/Ni-P/Cu stack were prepared and subjected to multiple reflows at 250°C. A tensile test was performed to investigate the effect of P content on the solder joint strength. The low P samples exhibited the highest joint strength after multiple reflows, while the strength of medium and high P samples decreased more rapidly. From interfacial analysis, the Ni₃Sn₄ intermetallic compound (IMC) formed at the interface of low P sample was found to be more stable, while the one of medium and high P samples spalled into the molten solder. The IMC spallation sped up the consumption of electroless Ni-P, leading to the large formation of Cu-Sn IMCs. Fractographic and microstructural analyses showed that the degradation in solder joint strength was due to the formation of layers of voids and growth of Cu-Sn IMCs between the solder and the Cu substrate.     

Multi-label personality trait identification from text

Understanding the personality is beneficial for many purposes, e.g., it is natural to predict a user’s personality before offering him or her any services. The personality is intrinsic in the behavior of a person in all aspects, such as text writing. Some work has been proposed in recent times for correctly classifying a person’s personality from the text. However, it is still a significant challenge as the achieved accuracy is low; therefore, the proposed work addresses this issue. Effective feature selection techniques provide better classification accuracy in multi-label classification and personality traits identification as multi-label classification problem requires efficacy of feature selection methods. Therefore, to improve the accuracy using feature selection technique, this paper proposes a method for personality trait recognition from textual data called P ersonality T rait Classification based on L inguistic and F eature selection as M ulti-label classification (PTLFM). It combines analysis of variance’s F-statistic, Chi-square, and Mutual information with the sequential feature selection wrapper method to rank features. These three criteria apprehend different aspects of the dataset. The experimental results demonstrate that the proposed PTLFM method achieves higher accuracy across all the personality traits than the prevailing state-of-the-art machine learning and deep learning models. PTLFM provides an impressive absolute improvement of 2.23% and 3.84% of comparative improvement over the existing prevalent method, with more than 90% of features discarded. Furthemore, the proposed PTLFM achieves a percentage gain compared to the competitive methods across different personality traits Extraversion, Neuroticism, Agreeableness, Conscientiousness, and Openness in absolute terms 1.17, 1.94, 2.35, 1.64, and 0.35 respectively, and in comparative terms 2.01, 3.27, 4.14, 2.86, and 0.56 respectively. The results suggest that although deep learning is a popular paradigm, it does not always lead to a better predictive performance than machine learning models in all the problem domains.

     

Performance Study of Dual Unmanned Aerial Vehicles with Underlaid Device-to-Device Communications

Wireless Personal Communications - Unmanned aerial vehicle (UAV) as an aerial base station is a predominant cost-effective solution of coverage extension in wireless communication network. It has a...     

Mercury-mercurous propionate electrode: standard potentials at different temperatures and related thermodynamic quantities in dioxan-water media

The standard molal potentials (E°_m/V) of the Hg/Hg₂(OPr)₂, OPr^? electrode at 15, 20, 25, 30 and 35°C have been determined in dioxan-water media. The values of E°_m as a function of the Celsius temperature, t, in different solvent composition may be represented by the following equations:

The related thermodynamic quantities have been calculated. The dependence of the standard potentials at 25°C on the dielectric constant of the media (in the light of the Born equation), the volume fraction (Φ_w) and the mole fraction (N_w) of water (based on Feakins-French relationship) have been examined. The variation of the thermodynamic quantities ΔG°, ΔS° and ΔH° with various parameters associated with solvent media have also been examined. The observations are similar to those reported in our previous work on mercury-mercurous acetate electrode in the same media. ΔC°_p for the cell reaction has been calculated.     

Vocal emotion recognition in five native languages of Assam using new wavelet features

The present work investigates the following specific research questions concerning voice emotion recognition: whether vocal emotion expressions of discrete emotion (i) can be distinguished from no-emotion (i.e. neutral), (ii) can be distinguished from another, (iii) of surprise, which is actually a cognitive component that could be present with any emotion, can also be recognized as distinct emotion, (iv) can be recognized cross-lingually. This study will enable us to get more information regarding nature and function of emotion. Furthermore, this work will help in developing a generalized voice emotion recognition system, which will increase the efficiency of human-machine interaction systems. In this work an emotional utterance database is created with 140 acted utterances per speaker consisting of short sentences of six full-blown basic emotions and neutral of five native languages of Assam. This database is validated by a Listening Test. Four feature sets are extracted based on WPCC2 (Wavelet-Packet-Cepstral-Coefficients computed by method 2), MFCC (Mel-Frequency-Cepstral-Coefficients), tfWPCC2 (Teager-energy-operated-in-Transform-domain WPCC2) and tfMFCC. The Gaussian Mixture Model (GMM) is used as classifier. The performances of all these feature sets are compared in respect of accuracy of classification in two experiments: (i) text-and-speaker independent vocal emotion recognition in individual languages, and (ii) cross-lingual vocal emotion recognition. tfWPCC2 is a new wavelet feature set proposed by the same authors in one of their recent papers in a National Seminar in India as cited in References.