Making media work in space: An interdisciplinary perspective on media and communication requirements for current and future space communities

As humans expand into space communities will form. These have already begun to form in small ways, such as long-duration missions on the International Space Station and the space shuttle, and small-scale tourist excursions into space. Social, behavioural and communications data emerging from such existing communities in space suggest that the physically-bounded, work-oriented and traditionally male-dominated nature of these extremely remote groups present specific problems for the resident astronauts, groups of them viewed as ‘communities’, and their associated groups who remain on Earth, including mission controllers, management and astronauts’ families. Notionally feminine group attributes such as adaptive competence, social adaptation skills and social sensitivity will be crucial to the viability of space communities and in the absence of gender equity, ‘staying in touch’ by means of ‘news from home’ becomes more important than ever. A template of news and media forms and technologies is suggested to service those needs and enhance the social viability of future terraforming activities.

Usability of a mobile, group communication prototype while rendezvousing

Mobile phones are increasingly being used collaboratively by social networks of users in spite of the fact that they are primarily designed to support single users and one-to-one communication. It is not well understood how services such as group SMS, SMS-based discussion lists and mobile instant messaging (IM) will be used by mobile groups in natural settings. Studying specific instances of common styles of in situ, group interaction may provide a way to see behavior patterns and typical interaction problems. We conducted a study of a mobile, group communication probe used during a rendezvousing activity in an urban environment. Usability problems relating to group usage, phone interface design and context were identified. Several major issues included: multitasking during message composition and reading; speed of text entry; excessive demand on visual attention; and ambiguity of intended recipients. We suggest that existing mobile device designs are overly-focused on individual users to the detriment of usability for mobile groups of users. We provide recommendations for the design of future mobile, group interfaces, used in similar situations to those explored here

Analysis of computer communication systems by use of digital signal processing methods

Queueing theory is an effective tool in the analysis of canputer camrunication systems. Many results in queueing analysis have teen derived in the form of Laplace and z-transform expressions. Accurate inversion of these transforms is very important in the study of computer systems, but the inversion is very often difficult. In this thesis, methods for solving some of these queueing problems, by use of digital signal processing techniques, are presented. The z-transform of the queue length distribution for the Mj GY jl system is derived. Two numerical methods for the inversion of the transfom, together with the standard numerical technique for solving transforms with multiple queue-state dependence, are presented. Bilinear and Poisson transform sequences are presented as useful ways of representing continuous-time functions in numerical computations.

Privatization : problems of implementation in Egypt

This study aims to investigate to what extent the views of the managers of the enterprises to be privatized are a barrier to smooth implementation of privatization as opposed to other problems. Accordingly, the research tackles two main issues: Identification and analysis of the major problems encountered in the implementation of the Egyptian privatization programme and at which level these problems exist while proposing different approaches to tackle them; and views of public sector top and middle-level managers regarding the main issues of privatization. The study relies upon a literature survey, interviews with stakeholders, a survey of managers' attitudes and several illustrative case studies. A model of "good practice" for the smooth and effective implementation of privatization has been designed. Practice in Egypt has then been studied and compared with the "good practice" model. Lack of strictness and firmness in implementing the announced privatization programme has been found to be a characteristic of Egyptian practice. This is partly attributable to the inadequacy of the programme and partly to the different obstacles to implementation. The main obstacles are doubtful desirability of privatization on the part of the managers at different implementation levels, resistance of stakeholders, in adequately of the legal framework governing privatization, redundant labour, lack of an efficient monitoring system allowing for accountability, inefficient marketing of privatization, ineffective communication, insufficient information at different levels and problems related to valuation and selling procedures. A large part of the thesis is concerned with SOE (State Owned Enterprise) managers' attitudes on and understanding of the privatization (appraised through surveys). Although most managers have stated their acceptance of privatization, many of their responses show that they do not accept selling SOEs. They understand privatization to include enterprise reform and restructuring, changing procedures and giving more authority to company executives, but not necessarily as selling SOEs. The majority of managers still see many issues that have to be addressed for smooth implementation of privatization e.g. insufficiency of information, incompleteness of legal framework, restructuring and labour problems. The main contribution to knowledge of this thesis is the study of problems of implementing privatization in developing countries especially managers' resistance to privatization as a major change, partly because of the threat it poses and partly because of the lack of understanding of privatization and implications of operating private businesses. A programme of persuading managers and offsetting the unfavourable effects is recommended as an outcome of the study. Five different phrases and words for the national Index to theses are: Egypt, privatization, implementation of privatization, problems of implementing privatization and managers' attitudes towards privatization.

Organisational change and safety culture: the impact of communication

This research examines and explains the links between safety culture and communication. Safety culture is a concept that in recent years has gained prominence but there has been little applied research conducted to investigate the meaning of the concept in 'real life' settings. This research focused on a Train Operating Company undergoing change in a move towards privatisation. These changes were evident in the management of safety, the organisation of the industry and internally in their management. The Train Operating Company's management took steps to improve their safety culture and communications through the development of a cascade communication structure. The research framework employed a qualitative methodology in order to investigate the effect of the new system on safety culture. Findings of the research were that communications in the organisation failed to be effective for a number of reasons, including both cultural and logistical problems. The cultural problems related to a lack of trust in the organisation by the management and the workforce, the perception of communications as management propaganda, and asyntonic communications between those involved, whilst logistical problems related to the inherent difficulties of communicating over a geographically distributed network. An organisational learning framework was used to explain the results. It is postulated that one of the principal reasons why change, either to the safety culture or to communications, did not occur was because of the organisation's inability to learn. The research has also shown the crucial importance of trust between the members of the organisation, as this was one of the fundamental reasons why the safety culture did not change, and why safety management systems were not fully implemented. This is consistent with the notion of mutual trust in the HSC (1993) definition of safety culture. This research has highlighted its relevance to safety culture and its importance for organisational change.

Digital Creativity: Advantages, Problems, Responsibilities

The paper focuses on the rapid development of the digital culture and the challenges it imposes to human creativity. It analyses e-learning, digital entertainment, digital art and the issues of creativity and improvisation. It also presents a classification of the levels in the creative structure including hardware and software tools; product developers; creators and end users. Special attention is paid to the advantages of the new digital culture and the responsibilities of all people who create it or use it. We conclude that more attention should be paid to the threats and to ways of boosting positive creativity in the various fields of application of information and communication technologies.

The Attributes of Social Media as a Strategic Marketing Communication Tool

New digital trends are transforming the media industry landscape, modifying elemental characteristics and attitudes of companies as well as of consumers. Firms often claim that their presence in social media (SM) is a key element to success. SM helps companies rethink the traditional one-way flow of their marketing messages and to incorporate a new interactive pattern into their communications. Nevertheless, these tendencies involve problems of strategic myopia for firms that do not structurally integrate these tools. One main problem is that institutions can rarely differentiate between the various types of SM and the attributes thereof, while the literature equally reveals a number of contradictions in the subject. The present conceptual paper lays the foundations of a strategic approach to SM and discusses its theoretical implications. Following an overview on the concept of SM, through a content analysis of the specialized management literature (n = 14), we present various best practices and reflect on the apparent lack of strategic thinking in using SM as a marketing application. Then, we compare these practical examples with general marketing strategy theory. By merging theory and practice, we aim to provide an insight towards a well-founded application of SM as a genuinely strategic marketing tool.

Longitudinal effects of family factors on alcohol use and alcohol-related problems among males from pre-adolescence to adulthood

The goal of this study was to examine the longitudinal effects of five family factors on alcohol use among adolescent males. The family factors included familism (family pride, loyalty, and cohesion), parent derogation (being put down by parents), parent/child communication, family alcohol problems and family drug problems. The study focused on the effects of the family factors reported by a sample of 451 White-non-Hispanic and African American males during early and mid-adolescence on (1) the intensity of alcohol use in mid-adolescence, and (2) the number of problems associated with alcohol use during the transition to young adulthood. The study also explored racial differences in the effects of the family factors. The data for this study were derived from a two-phase longitudinal epidemiologic cohort study of male and female adolescents enrolled in middle schools in Miami, FL. Data were collected at four points between 1990 and 2001. Linear and logistical regressions were used to analyze the effects of the family variables on the dependent variables. ^ The results of the analyses indicated that all of the family variables except family drug problems were statistically significant predictors of the level of alcohol use and alcohol-related problems. Familism had a moderate influence on both of the dependent variables at all data points, while parent derogation, parent/child communication and family alcohol problems were weak predictors. While the family factors varied by race, their impact on the dependent variables did not vary substantially. ^ This study had methodological shortcomings related to measurement and design that may have contributed to the weak influence of the variables. Future studies should explore possible mediating effects of these variables, and should employ more sensitive measures that are culturally appropriate. The results suggest that, since early family factors have long-term effects on children's substance-using behaviors, the family environment should be addressed in prevention and intervention efforts. ^

Distributed Feature Selection in Large n and Large p Regression Problems

Fitting statistical models is computationally challenging when the sample size or the dimension of the dataset is huge. An attractive approach for down-scaling the problem size is to first partition the dataset into subsets and then fit using distributed algorithms. The dataset can be partitioned either horizontally (in the sample space) or vertically (in the feature space), and the challenge arise in defining an algorithm with low communication, theoretical guarantees and excellent practical performance in general settings. For sample space partitioning, I propose a MEdian Selection Subset AGgregation Estimator ({\em message}) algorithm for solving these issues. The algorithm applies feature selection in parallel for each subset using regularized regression or Bayesian variable selection method, calculates the `median' feature inclusion index, estimates coefficients for the selected features in parallel for each subset, and then averages these estimates. The algorithm is simple, involves very minimal communication, scales efficiently in sample size, and has theoretical guarantees. I provide extensive experiments to show excellent performance in feature selection, estimation, prediction, and computation time relative to usual competitors.

While sample space partitioning is useful in handling datasets with large sample size, feature space partitioning is more effective when the data dimension is high. Existing methods for partitioning features, however, are either vulnerable to high correlations or inefficient in reducing the model dimension. In the thesis, I propose a new embarrassingly parallel framework named {\em DECO} for distributed variable selection and parameter estimation. In {\em DECO}, variables are first partitioned and allocated to m distributed workers. The decorrelated subset data within each worker are then fitted via any algorithm designed for high-dimensional problems. We show that by incorporating the decorrelation step, DECO can achieve consistent variable selection and parameter estimation on each subset with (almost) no assumptions. In addition, the convergence rate is nearly minimax optimal for both sparse and weakly sparse models and does NOT depend on the partition number m. Extensive numerical experiments are provided to illustrate the performance of the new framework.

For datasets with both large sample sizes and high dimensionality, I propose a new "divided-and-conquer" framework {\em DEME} (DECO-message) by leveraging both the {\em DECO} and the {\em message} algorithm. The new framework first partitions the dataset in the sample space into row cubes using {\em message} and then partition the feature space of the cubes using {\em DECO}. This procedure is equivalent to partitioning the original data matrix into multiple small blocks, each with a feasible size that can be stored and fitted in a computer in parallel. The results are then synthezied via the {\em DECO} and {\em message} algorithm in a reverse order to produce the final output. The whole framework is extremely scalable.

Communication-efficient decentralized sequential detection

The problem of decentralized sequential detection is studied in this thesis, where local sensors are memoryless, receive independent observations, and no feedback from the fusion center. In addition to traditional criteria of detection delay and error probability, we introduce a new constraint: the number of communications between local sensors and the fusion center. This metric is able to reflect both the cost of establishing communication links as well as overall energy consumption over time. A new formulation for communication-efficient decentralized sequential detection is proposed where the overall detection delay is minimized with constraints on both error probabilities and the communication cost. Two types of problems are investigated based on the communication-efficient formulation: decentralized hypothesis testing and decentralized change detection. In the former case, an asymptotically person-by-person optimum detection framework is developed, where the fusion center performs a sequential probability ratio test based on dependent observations. The proposed algorithm utilizes not only reported statistics from local sensors, but also the reporting times. The asymptotically relative efficiency of proposed algorithm with respect to the centralized strategy is expressed in closed form. When the probabilities of false alarm and missed detection are close to one another, a reduced-complexity algorithm is proposed based on a Poisson arrival approximation. In addition, decentralized change detection with a communication cost constraint is also investigated. A person-by-person optimum change detection algorithm is proposed, where transmissions of sensing reports are modeled as a Poisson process. The optimum threshold value is obtained through dynamic programming. An alternative method with a simpler fusion rule is also proposed, where the threshold values in the algorithm are determined by a combination of sequential detection analysis and constrained optimization. In both decentralized hypothesis testing and change detection problems, tradeoffs in parameter choices are investigated through Monte Carlo simulations.

Legal Translation from English to Spanish in the Classroom: Problems when Translating Standard Formulas of Expression

The purpose of this paper is to identify problems when translating standard formulas of expression in English to Spanish legal translation. To achieve the goal, a total of 250 Spanish translations were analyzed of 10 sentences from legal texts in English. The degree of difficulty posed by the translation of these formulas is confirmed by the results obtained, which is related not so much to the intrinsic meaning of the words that compose them, but to their contextual meaning. An eclectic approach that combines discourse analysis with contrastive linguistics is proposed, and some specific didactic guidelines are indicated to facilitate the translation teaching of these standard formulas of expression. Lexical interpretation and contextual recreation allow the apprentice translator to make progress with the translation of these phrases and to improve his/her attitude when facing them to achieve a successful semantic and contextual interpretation, that is to say, getting the closest natural equivalent while respecting the genius of the language.

Methods, Models & Systems for Dealing with Some Business, Management & Engineering Problems

This keynote presentation will report some of our research work and experience on the development and applications of relevant methods, models, systems and simulation techniques in support of different types and various levels of decision making for business, management and engineering. In particular, the following topics will be covered. Modelling, multi-agent-based simulation and analysis of the allocation management of carbon dioxide emission permits in China (Nanfeng Liu & Shuliang Li Agent-based simulation of the dynamic evolution of enterprise carbon assets (Yin Zeng & Shuliang Li) A framework & system for extracting and representing project knowledge contexts using topic models and dynamic knowledge maps: a big data perspective (Jin Xu, Zheng Li, Shuliang Li & Yanyan Zhang) Open innovation: intelligent model, social media & complex adaptive system simulation (Shuliang Li & Jim Zheng Li) A framework, model and software prototype for modelling and simulation for deshopping behaviour and how companies respond (Shawkat Rahman & Shuliang Li) Integrating multiple agents, simulation, knowledge bases and fuzzy logic for international marketing decision making (Shuliang Li & Jim Zheng Li) A Web-based hybrid intelligent system for combined conventional, digital, mobile, social media and mobile marketing strategy formulation (Shuliang Li & Jim Zheng Li) A hybrid intelligent model for Web & social media dynamics, and evolutionary and adaptive branding (Shuliang Li) A hybrid paradigm for modelling, simulation and analysis of brand virality in social media (Shuliang Li & Jim Zheng Li) Network configuration management: attack paradigms and architectures for computer network survivability (Tero Karvinen & Shuliang Li)

Comparison of three algorithms for nonlinear metal cutting problems

This paper compares three alternative numerical algorithms applied to a nonlinear metal cutting problem. One algorithm is based on an explicit method and the other two are implicit. Domain decomposition (DD) is used to break the original domain into subdomains, each containing a properly connected, well-formulated and continuous subproblem. The serial version of the explicit algorithm is implemented in FORTRAN and its parallel version uses MPI (Message Passing Interface) calls. One implicit algorithm is implemented by coupling the state-of-the-art PETSc (Portable, Extensible Toolkit for Scientific Computation) software with in-house software in order to solve the subproblems. The second implicit algorithm is implemented completely within PETSc. PETSc uses MPI as the underlying communication library. Finally, a 2D example is used to test the algorithms and various comparisons are made.

Variational ensemble Kalman filtering applied to data assimilation problems in computational fluid dynamics

One challenge on data assimilation (DA) methods is how the error covariance for the model state is computed. Ensemble methods have been proposed for producing error covariance estimates, as error is propagated in time using the non-linear model. Variational methods, on the other hand, use the concepts of control theory, whereby the state estimate is optimized from both the background and the measurements. Numerical optimization schemes are applied which solve the problem of memory storage and huge matrix inversion needed by classical Kalman filter methods. Variational Ensemble Kalman filter (VEnKF), as a method inspired the Variational Kalman Filter (VKF), enjoys the benefits from both ensemble methods and variational methods. It avoids filter inbreeding problems which emerge when the ensemble spread underestimates the true error covariance. In VEnKF this is tackled by resampling the ensemble every time measurements are available. One advantage of VEnKF over VKF is that it needs neither tangent linear code nor adjoint code. In this thesis, VEnKF has been applied to a two-dimensional shallow water model simulating a dam-break experiment. The model is a public code with water height measurements recorded in seven stations along the 21:2 m long 1:4 m wide flume’s mid-line. Because the data were too sparse to assimilate the 30 171 model state vector, we chose to interpolate the data both in time and in space. The results of the assimilation were compared with that of a pure simulation. We have found that the results revealed by the VEnKF were more realistic, without numerical artifacts present in the pure simulation. Creating a wrapper code for a model and DA scheme might be challenging, especially when the two were designed independently or are poorly documented. In this thesis we have presented a non-intrusive approach of coupling the model and a DA scheme. An external program is used to send and receive information between the model and DA procedure using files. The advantage of this method is that the model code changes needed are minimal, only a few lines which facilitate input and output. Apart from being simple to coupling, the approach can be employed even if the two were written in different programming languages, because the communication is not through code. The non-intrusive approach is made to accommodate parallel computing by just telling the control program to wait until all the processes have ended before the DA procedure is invoked. It is worth mentioning the overhead increase caused by the approach, as at every assimilation cycle both the model and the DA procedure have to be initialized. Nonetheless, the method can be an ideal approach for a benchmark platform in testing DA methods. The non-intrusive VEnKF has been applied to a multi-purpose hydrodynamic model COHERENS to assimilate Total Suspended Matter (TSM) in lake Säkylän Pyhäjärvi. The lake has an area of 154 km2 with an average depth of 5:4 m. Turbidity and chlorophyll-a concentrations from MERIS satellite images for 7 days between May 16 and July 6 2009 were available. The effect of the organic matter has been computationally eliminated to obtain TSM data. Because of computational demands from both COHERENS and VEnKF, we have chosen to use 1 km grid resolution. The results of the VEnKF have been compared with the measurements recorded at an automatic station located at the North-Western part of the lake. However, due to TSM data sparsity in both time and space, it could not be well matched. The use of multiple automatic stations with real time data is important to elude the time sparsity problem. With DA, this will help in better understanding the environmental hazard variables for instance. We have found that using a very high ensemble size does not necessarily improve the results, because there is a limit whereby additional ensemble members add very little to the performance. Successful implementation of the non-intrusive VEnKF and the ensemble size limit for performance leads to an emerging area of Reduced Order Modeling (ROM). To save computational resources, running full-blown model in ROM is avoided. When the ROM is applied with the non-intrusive DA approach, it might result in a cheaper algorithm that will relax computation challenges existing in the field of modelling and DA.