Communication and interactions in cloud platform subtitling

This article explores recent developments in freelance subtitling work within the audio-visual translation (AVT) industry. During the 2010s, many LSPs operating globally moved their provision of paid, professional subtitling services to cloud platforms, and I argue that such platforms, while capable of generating collaborative environments, enact information patterns which weaken the communicative and collaborative aspects of production processes, while running the risk of compromising the quality of the subtitlers’ position.

Analysis of Gaze Information Patterns of Nurses Gathering Patient Information Using Electronic Health Records

The objective of this study was to clarify gaze information patterns of nurses gathering patient information using electronic health records. We recorded the electronic health record screen on which nurses’ gazes were presented using an eye tracker and analyzed the recorded images. The analysis revealed two types of gaze information patterns of nurses engaged in patient information gathering. However, no regularity was observed in the gaze information patterns of the nurses viewing the electronic health record sections after selecting a patient.

Establishing Information Seeking Behavior on Access to Digital Resources by Students with Visual Impairment: A Case Study of Nairobi University Library Services, Kenya

Information is power, very important and valuable commodity in everyday human activity as evidenced with the current digital divide that equal access to information is essential to the development of information society which also applies to people with disability. The aim of the study was to establish the information seeking behavior of visually impaired (VI) students at University of Nairobi library services. The total population of the study comprised of two units of analysis which were 32 visually impaired students and 6 librarians in charge of the visually impaired students. The study carried out a survey by means of questionnaires. The study employed Wilson’s (1999) theory of information behavior model which provided a framework in mapping the student’s information patterns. Statistical Package for the Social Sciences (SPSS) and Microsoft excel 2016 were used to analyze the data. The response rate was 78.95% from all the units of analysis. The findings indicated that majority of the respondents 72% were female. The findings further revealed that most Visually impaired students were getting assistance from a sighted person or by use of computers, speech synthesizers, screen readers, brail prints, and audio books. A smaller number of the respondents (2.44%) used mobile app called tap tap. The study indicated that majority 68.3% of the Visually impaired students relied on aiding tools.

THE TRANSLATION OF INFORMATION PATTERN FOR I CARE A LOT MOVIE SUBTITLE FROM ENGLISH TO INDONESIAN

Movie subtitle translation is the transfer of meaning from source text into target text in the form of text under the screen with limited time and characters. One of the problems in translating movie subtitle is the information pattern. Information patterns are how the information is organized. This information arrangement includes information status and information urgency. This research uses descriptive and comparative methods. The results of the study indicate that (i) there are parallels in information pattern urgency, namely foreground position tends to be in the beginning of the speech; (ii) the misalignment of information status occurs in sentences translation with it subject and that impersonal and in interrogative and imperative sentences translation, as well as in sentences translation with the non-doer subject.

THE TRANSLATION OF INFORMATION PATTERN FOR I CARE A LOT MOVIE SUBTITLE FROM ENGLISH TO INDONESIAN

Movie subtitle translation is the transfer of meaning from source text into target text in the form of text under the screen with limited time and characters. One of the problems in translating movie subtitle is the information pattern. Information patterns are how the information is organized. This information arrangement includes information status and information urgency. This research uses descriptive and comparative methods. The results of the study indicate that (i) there are parallels in information pattern urgency, namely foreground position tends to be in the beginning of the speech; (ii) the misalignment of information status occurs in sentences translation with it subject and that impersonal and in interrogative and imperative sentences translation, as well as in sentences translation with the non-doer subject.

Plant-insect chemical communication in ecological communities: an information theory perspective

Cross-species communication, where signals are sent by one species and perceived by others, is one of the most intriguing types of communication that functionally links different species to form complex ecological networks. Yet, global changes and human activities can affect communication by increasing the fluctuations of species composition and phenology, altering signal profiles and intensity, and introducing noises. So far, most studies on cross-species communication have focused on a few specific species isolated from ecological communities. Scaling up investigations of cross-species communication to the community level is currently hampered by a lack of conceptual and practical methodologies. Here, we propose an interdisciplinary framework based on information theory to investigate mechanisms shaping cross-species communication at the community level. We use plants and insects, the cornerstones of most ecosystems, as a showcase; and focus on chemical communication as the key communication channel. We first introduce some basic concepts of information theory, then we illustrate information patterns in plant-insect chemical communication, followed by a further exploration of how to integrate information theory into ecological and evolutionary processes to form testable mechanistic hypotheses. We conclude by highlighting the importance of community-level information as a vehicle to better understand the maintenance of ecological systems, especially when facing rapid global changes.

An analysis of unconscious gender bias in academic texts by means of a decision algorithm

Inclusive language focuses on using the vocabulary to avoid exclusion or discrimination, specially referred to gender. The task of finding gender bias in written documents must be performed manually, and it is a time-consuming process. Consequently, studying the usage of non-inclusive language on a document, and the impact of different document properties (such as author gender, date of presentation, etc.) on how many non-inclusive instances are found, is quite difficult or even impossible for big datasets. This research analyzes the gender bias in academic texts by analyzing a study corpus of more than 12,000 million words obtained from more than one hundred thousand doctoral theses from Spanish universities. For this purpose, an automated algorithm was developed to evaluate the different characteristics of the document and look for interactions between age, year of publication, gender or the field of knowledge in which the doctoral thesis is framed. The algorithm identified information patterns using a CNN (convolutional neural network) by the creation of a vector representation of the sentences. The results showed evidence that there was a greater bias as the age of the authors increased, who were more likely to use non-inclusive terms; it was concluded that there is a greater awareness of inclusiveness in women than in men, and also that this awareness grows as the candidate is younger. The results showed evidence that the age of the authors increased discrimination, with men being more likely to use non-inclusive terms (up to an index of 23.12), showing that there is a greater awareness of inclusiveness in women than in men in all age ranges (with an average of 14.99), and also that this awareness grows as the candidate is younger (falling down to 13.07). In terms of field of knowledge, the humanities are the most biased (20.97), discarding the subgroup of Linguistics, which has the least bias at all levels (9.90), and the field of science and engineering, which also have the least influence (13.46). Those results support the assumption that the bias in academic texts (doctoral theses) is due to unconscious issues: otherwise, it would not depend on the field, age, gender, and would occur in any field in the same proportion. The innovation provided by this research lies mainly in the ability to detect, within a textual document in Spanish, whether the use of language can be considered non-inclusive, based on a CNN that has been trained in the context of the doctoral thesis. A significant number of documents have been used, using all accessible doctoral theses from Spanish universities of the last 40 years; this dataset is only manageable by data mining systems, so that the training allows identifying the terms within the context effectively and compiling them in a novel dictionary of non-inclusive terms.

Clock time: a foreign measure to brain dynamics

Human thought is highly flexible and dynamic, achieved by evolving patterns of brain activity across groups of cells. Neuroscience aims to understand cognition in the brain by analysing these intricate patterns. Here, we argue that this goal is impeded by the time format of our data – clock time. The brain is a system with its own dynamics and regime of time, with no intrinsic concern for the human-invented second. A more appropriate time format is cycles of brain oscillations, which coordinate neural firing and are widely implicated in cognition. These brain dynamics do not obey clock time – they start out of tune with clock time and drift apart even further as oscillations unpredictably slow down, speed up, and undergo abrupt changes. Since oscillations clock cognition, their dynamics should critically inform our analysis. We describe brain time warping as a new method to transform data in accordance with brain dynamics, which sets the time axis to cycles of clocking oscillations (a native unit) rather than milliseconds (a foreign unit). We also introduce the Brain Time Toolbox, a software library that implements brain time warping for electrophysiology data and tests whether it reveals information patterns in line with how the brain uses them.

Approximately Optimal Control of Nonlinear Dynamic Stochastic Problems with Learning: The OPTCON Algorithm

OPTCON is an algorithm for the optimal control of nonlinear stochastic systems which is particularly applicable to economic models. It delivers approximate numerical solutions to optimum control (dynamic optimization) problems with a quadratic objective function for nonlinear economic models with additive and multiplicative (parameter) uncertainties. The algorithm was first programmed in C# and then in MATLAB. It allows for deterministic and stochastic control, the latter with open loop (OPTCON1), passive learning (open-loop feedback, OPTCON2), and active learning (closed-loop, dual, or adaptive control, OPTCON3) information patterns. The mathematical aspects of the algorithm with open-loop feedback and closed-loop information patterns are presented in more detail in this paper.

Modeling Working Memory in a Spiking Neuron Network Accompanied by Astrocytes

We propose a novel biologically plausible computational model of working memory (WM) implemented by a spiking neuron network (SNN) interacting with a network of astrocytes. The SNN is modeled by synaptically coupled Izhikevich neurons with a non-specific architecture connection topology. Astrocytes generating calcium signals are connected by local gap junction diffusive couplings and interact with neurons via chemicals diffused in the extracellular space. Calcium elevations occur in response to the increased concentration of the neurotransmitter released by spiking neurons when a group of them fire coherently. In turn, gliotransmitters are released by activated astrocytes modulating the strength of the synaptic connections in the corresponding neuronal group. Input information is encoded as two-dimensional patterns of short applied current pulses stimulating neurons. The output is taken from frequencies of transient discharges of corresponding neurons. We show how a set of information patterns with quite significant overlapping areas can be uploaded into the neuron-astrocyte network and stored for several seconds. Information retrieval is organized by the application of a cue pattern representing one from the memory set distorted by noise. We found that successful retrieval with the level of the correlation between the recalled pattern and ideal pattern exceeding 90% is possible for the multi-item WM task. Having analyzed the dynamical mechanism of WM formation, we discovered that astrocytes operating at a time scale of a dozen of seconds can successfully store traces of neuronal activations corresponding to information patterns. In the retrieval stage, the astrocytic network selectively modulates synaptic connections in the SNN leading to successful recall. Information and dynamical characteristics of the proposed WM model agrees with classical concepts and other WM models.