950 resultados para communication problems


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Modern science, which was an indigenous product of Western culture, is now being practised in many non-Western countries. This paper discusses the peculiar social, cultural and intellectual problems which scientists of these non-Western countries face in adopting Western science in their situations, with special reference to India. It is pointed out that, in addition to money and communication, it is necessary to have a proper psychological gestalt to practise science satisfactorily. The author analyzes his experience as a physics student in India and in the United States to clarify the nature of this psychological gestalt, and to explain what makes it difficult for non-Western scientists to acquire it.

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A considerable amount of work has been dedicated on the development of analytical solutions for flow of chemical contaminants through soils. Most of the analytical solutions for complex transport problems are closed-form series solutions. The convergence of these solutions depends on the eigen values obtained from a corresponding transcendental equation. Thus, the difficulty in obtaining exact solutions from analytical models encourages the use of numerical solutions for the parameter estimation even though, the later models are computationally expensive. In this paper a combination of two swarm intelligence based algorithms are used for accurate estimation of design transport parameters from the closed-form analytical solutions. Estimation of eigen values from a transcendental equation is treated as a multimodal discontinuous function optimization problem. The eigen values are estimated using an algorithm derived based on glowworm swarm strategy. Parameter estimation of the inverse problem is handled using standard PSO algorithm. Integration of these two algorithms enables an accurate estimation of design parameters using closed-form analytical solutions. The present solver is applied to a real world inverse problem in environmental engineering. The inverse model based on swarm intelligence techniques is validated and the accuracy in parameter estimation is shown. The proposed solver quickly estimates the design parameters with a great precision.

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Despite an increased risk of mental health problems in adolescents with Autism Spectrum Disorder (ASD), there is limited research on effective prevention approaches for this population. Funded by the Cooperative Research Centre for Living with Autism, a theoretically and empirically supported school-based preventative model has been developed to alter the negative trajectory and promote wellbeing and positive mental health in adolescents with ASD. This conceptual paper provides the rationale, theoretical, empirical and methodological framework of a multilayered intervention targeting the school, parents, and adolescents on the spectrum. Two important interrelated protective factors have been identified in community adolescent samples, namely the sense of belonging (connectedness) to school, and the capacity for self and affect regulation in the face of stress (i.e., resilience). We describe how a confluence of theories from social psychology, developmental psychology and family systems theory, along with empirical evidence (including emerging neurobiological evidence) supports the interrelationships between these protective factors and many indices of wellbeing. However, the characteristics of ASD (including social and communication difficulties, and frequently difficulties with changes and transitions, and diminished optimism and self-esteem) impair access to these vital protective factors. The paper describes how evidenced-based interventions at the school level for promoting inclusive schools (using the Index for Inclusion), and interventions for adolescents and parents to promote resilience and belonging (using the Resourceful Adolescent Program (RAP)), are adapted and integrated for adolescents with ASD. This multisite proof of concept study will confirm whether this multilevel school-based intervention is promising, feasible and sustainable.

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The JoMeC Network project had three key objectives. These were to: 1. Benchmark the pedagogical elements of journalism, media and communication (JoMeC) programs at Australian universities in order to develop a set of minimum academic standards, to be known as Threshold Learning Outcomes (TLOs), which would applicable to the disciplines of Journalism, Communication and/or Media Studies, and Public Relations; 2. Build a learning and teaching network of scholars across the JoMeC disciplines to support collaboration, develop leadership potential among educators, and progress shared priorities; 3. Create an online resources hub to support learning and teaching excellence and foster leadership in learning and teaching in the JoMeC disciplines. In order to benchmark the pedagogical elements of the JoMeC disciplines, the project started with a comprehensive review of the disciplinary settings of journalism, media and communication-related programs within Higher Education in Australia plus an analysis of capstone units (or subjects) offered in JoMeC-related degrees. This audit revealed a diversity of degree titles, disciplinary foci, projected career outcomes and pedagogical styles in the 36 universities that offered JoMeC-related degrees in 2012, highlighting the difficulties of classifying the JoMeC disciplines collectively or singularly. Instead of attempting to map all disciplines related to journalism, media and communication, the project team opted to create generalised TLOs for these fields, coupled with detailed TLOs for bachelor-level qualifications in three selected JoMeC disciplines: Journalism, Communication and/or Media Studies, and Public Relations. The initial review’s outcomes shaped the methodology that was used to develop the TLOs. Given the complexity of the JoMeC disciplines and the diversity of degrees across the network, the project team deployed an issue-framing process to create TLO statements. This involved several phases, including discussions with an issue-framing team (an advisory group of representatives from different disciplinary areas); research into accreditation requirements and industry-produced materials about employment expectations; evaluation of learning outcomes from universities across Australia; reviews of scholarly literature; as well as input from disciplinary leaders in a variety of forms. Draft TLOs were refined after further consultation with industry stakeholders and the academic community via email, telephone interviews, and meetings and public forums at conferences. This process was used to create a set of common TLOs for JoMeC disciplines in general and extended TLO statements for the specific disciplines of Journalism and Public Relations. A TLO statement for Communication and/or Media Studies remains in draft form. The Australian and New Zealand Communication Association (ANZCA) and Journalism Education and Research Association of Australian (JERAA) have agreed to host meetings to review, revise and further develop the TLOs. The aim is to support the JoMeC Network’s sustainability and the TLOs’ future development and use.

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We consider the problem of determining if two finite groups are isomorphic. The groups are assumed to be represented by their multiplication tables. We present an O(n) algorithm that determines if two Abelian groups with n elements each are isomorphic. This improves upon the previous upper bound of O(n log n) [Narayan Vikas, An O(n) algorithm for Abelian p-group isomorphism and an O(n log n) algorithm for Abelian group isomorphism, J. Comput. System Sci. 53 (1996) 1-9] known for this problem. We solve a more general problem of computing the orders of all the elements of any group (not necessarily Abelian) of size n in O(n) time. Our algorithm for isomorphism testing of Abelian groups follows from this result. We use the property that our order finding algorithm works for any group to design a simple O(n) algorithm for testing whether a group of size n, described by its multiplication table, is nilpotent. We also give an O(n) algorithm for determining if a group of size n, described by its multiplication table, is Abelian. (C) 2007 Elsevier Inc. All rights reserved.

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We are concerned with maximizing the lifetime of a data-gathering wireless sensor network consisting of set of nodes directly communicating with a base-station. We model this scenario as the m-message interactive communication between multiple correlated informants (sensor nodes) and a recipient (base-station). With this framework, we show that m-message interactive communication can indeed enhance network lifetime. Both worst-case and average-case performances are considered.

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Solving large-scale all-to-all comparison problems using distributed computing is increasingly significant for various applications. Previous efforts to implement distributed all-to-all comparison frameworks have treated the two phases of data distribution and comparison task scheduling separately. This leads to high storage demands as well as poor data locality for the comparison tasks, thus creating a need to redistribute the data at runtime. Furthermore, most previous methods have been developed for homogeneous computing environments, so their overall performance is degraded even further when they are used in heterogeneous distributed systems. To tackle these challenges, this paper presents a data-aware task scheduling approach for solving all-to-all comparison problems in heterogeneous distributed systems. The approach formulates the requirements for data distribution and comparison task scheduling simultaneously as a constrained optimization problem. Then, metaheuristic data pre-scheduling and dynamic task scheduling strategies are developed along with an algorithmic implementation to solve the problem. The approach provides perfect data locality for all comparison tasks, avoiding rearrangement of data at runtime. It achieves load balancing among heterogeneous computing nodes, thus enhancing the overall computation time. It also reduces data storage requirements across the network. The effectiveness of the approach is demonstrated through experimental studies.

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Autonomous mission control, unlike automatic mission control which is generally pre-programmed to execute an intended mission, is guided by the philosophy of carrying out a complete mission on its own through online sensing, information processing, and control reconfiguration. A crucial cornerstone of this philosophy is the capability of intelligence and of information sharing between unmanned aerial vehicles (UAVs) or with a central controller through secured communication links. Though several mission control algorithms, for single and multiple UAVs, have been discussed in the literature, they lack a clear definition of the various autonomous mission control levels. In the conventional system, the ground pilot issues the flight and mission control command to a UAV through a command data link and the UAV transmits intelligence information, back to the ground pilot through a communication link. Thus, the success of the mission depends entirely on the information flow through a secured communication link between ground pilot and the UAV In the past, mission success depended on the continuous interaction of ground pilot with a single UAV, while present day applications are attempting to define mission success through efficient interaction of ground pilot with multiple UAVs. However, the current trend in UAV applications is expected to lead to a futuristic scenario where mission success would depend only on interaction among UAV groups with no interaction with any ground entity. However, to reach this capability level, it is necessary to first understand the various levels of autonomy and the crucial role that information and communication plays in making these autonomy levels possible. This article presents a detailed framework of UAV autonomous mission control levels in the context of information flow and communication between UAVs and UAV groups for each level of autonomy.

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We provide a new unified framework, called "multiple correlated informants - single recipient" communication, to address the variations of the traditional Distributed Source Coding (DSC) problem. Different combinations of the assumptions about the communication scenarios and the objectives of communication result in different variations of the DSC problem. For each of these variations, the complexities of communication and computation of the optimal solution is determined by the combination of the underlying assumptions. In the proposed framework, we address the asymmetric, interactive, and lossless variant of the DSC problem, with various objectives of communication and provide optimal solutions for those. Also, we consider both, the worst-case and average-case scenarios.

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The problem of sensor-network-based distributed intrusion detection in the presence of clutter is considered. It is argued that sensing is best regarded as a local phenomenon in that only sensors in the immediate vicinity of an intruder are triggered. In such a setting, lack of knowledge of intruder location gives rise to correlated sensor readings. A signal-space viewpoint is introduced in which the noise-free sensor readings associated to intruder and clutter appear as surfaces $\mathcal{S_I}$ and $\mathcal{S_C}$ and the problem reduces to one of determining in distributed fashion, whether the current noisy sensor reading is best classified as intruder or clutter. Two approaches to distributed detection are pursued. In the first, a decision surface separating $\mathcal{S_I}$ and $\mathcal{S_C}$ is identified using Neyman-Pearson criteria. Thereafter, the individual sensor nodes interactively exchange bits to determine whether the sensor readings are on one side or the other of the decision surface. Bounds on the number of bits needed to be exchanged are derived, based on communication complexity (CC) theory. A lower bound derived for the two-party average case CC of general functions is compared against the performance of a greedy algorithm. The average case CC of the relevant greater-than (GT) function is characterized within two bits. In the second approach, each sensor node broadcasts a single bit arising from appropriate two-level quantization of its own sensor reading, keeping in mind the fusion rule to be subsequently applied at a local fusion center. The optimality of a threshold test as a quantization rule is proved under simplifying assumptions. Finally, results from a QualNet simulation of the algorithms are presented that include intruder tracking using a naive polynomial-regression algorithm.

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Previous studies have shown a relationship between the use of communications technology and well-being, particularly mediated through its effect on personal relationships. However, there is some debate over whether this effect is positive or negative. The present study explored this issue further, examining whether the effect varies depending on the type of communications technology, and the nature of the personal relationship. An online survey was conducted with 3,421 participants in three countries (Australia, UK and US). It examined the use of ten communication methods, overall satisfaction with life and satisfaction with four different kinds of relationships (close and extended family, and close and distant friends). Results indicate that richer communication methods, which include non-verbal cues, were positively associated with both overall satisfaction with life and satisfaction with relationships. These methods included face-to-face communication, and phone and video calls. Conversely, more restricted methods, such as text messaging and instant messaging, were negatively associated with both variables. Social networking was negatively associated with overall satisfaction, but not with satisfaction with relationships. The strength of the association between a communications method and satisfaction with a relationship varied depending on the type of relationship, but whether it was positive or negative did not change.

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Communication and Political Crisis explores the role of the global media in a period of intensifying geopolitical conflict. Through case studies drawn from domestic and international political crises such as the conflicts in the Middle East and Ukraine, leading media scholar Brian McNair argues that the digitized, globalized public sphere now confronted by all political actors has produced new opportunities for social progress and democratic reform, as well as new channels for state propaganda and terrorist spectaculars such as those performed by the Islamic State and Al Qaeda. In this major work, McNair argues that the role of digital communication will be crucial in determining the outcome of pressing global issues such as the future of feminism and gay rights, freedom of speech and media, and democracy itself.

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Sequence design problems are considered in this paper. The problem of sum power minimization in a spread spectrum system can be reduced to the problem of sum capacity maximization, and vice versa. A solution to one of the problems yields a solution to the other. Subsequently, conceptually simple sequence design algorithms known to hold for the white-noise case are extended to the colored noise case. The algorithms yield an upper bound of 2N - L on the number of sequences where N is the processing gain and L the number of non-interfering subsets of users. If some users (at most N - 1) are allowed to signal along a limited number of multiple dimensions, then N orthogonal sequences suffice.

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This research explored the feasibility of using multidimensional scaling (MDS) analysis in novel combination with other techniques to study comprehension of epistemic adverbs expressing doubt and certainty (e.g., evidently, obviously, probably) as they relate to health communication in clinical settings. In Study 1, Australian English speakers performed a dissimilarity-rating task with sentence pairs containing the target stimuli, presented as "doctors' opinions". Ratings were analyzed using a combination of cultural consensus analysis (factor analysis across participants), weighted-data classical-MDS, and cluster analysis. Analyses revealed strong within-community consistency for a 3-dimensional semantic space solution that took into account individual differences, strong statistical acceptability of the MDS results in terms of stress and explained variance, and semantic configurations that were interpretable in terms of linguistic analyses of the target adverbs. The results confirmed the feasibility of using MDS in this context. Study 2 replicated the results with Canadian English speakers on the same task. Semantic analyses and stress decomposition analysis were performed on the Australian and Canadian data sets, revealing similarities and differences between the two groups. Overall, the results support using MDS to study comprehension of words critical for health communication, including in future studies, for example, second language speaking patients and/or practitioners. More broadly, the results indicate that the techniques described should be promising for comprehension studies in many communicative domains, in both clinical settings and beyond, and including those targeting other aspects of language and focusing on comparisons across different speech communities.