Relevant bibliographies by topics / Mass communication|Artificial intelligence|Computer science

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Mass communication|Artificial intelligence|Computer science'

Author: Grafiati
Published: 4 June 2021
Last updated: 16 February 2022

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Journal articles on the topic "Mass communication|Artificial intelligence|Computer science"

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Kusumawati, Ririen. "KECERDASAN BUATAN MANUSIA (ARTIFICIAL INTELLIGENCE); TEKNOLOGI IMPIAN MASA DEPAN." ULUL ALBAB Jurnal Studi Islam 9, no. 2 (December 26, 2018): 257–74. http://dx.doi.org/10.18860/ua.v9i2.6218.

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The computer technology has incredibly increased. Computer software and hardware compete to meet the customer's needs. The research intends to spread the knowledge of information technology, specifically, on the artificial intelligence. The concept of artificial intelligence is adopting and imitating human form, character, and habit which to be implemented on the computer. Using natural approach, the research aims to investigate whether artificial intelligence (AI) will produce the duplication of God's creation. Another important reason of other reseaches on AI is to create a computer which is smart and able to understand human brain working system. Hence, AI has been designed into more practical with faster CPU, cheaper mass memory, and sophisticated software tool. The concept of integrating AI science or collaborative art among sub-fields of technology will stimulate and lead to further AI researches, and it will be an interesting topic for AI researchers for developing AI technology in the future.
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Stengler, Erik, and Jimena Escudero Pérez. "SiP 2017 panel: speculations and concerns on robots' status in society." Journal of Science Communication 16, no. 04 (September 20, 2017): C06. http://dx.doi.org/10.22323/2.16040306.

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Studying fictional depictions of robots and artificial intelligence in cinematographic science fiction narratives acquires a new level of relevance as legislators' approaches to the subject seem to be strongly influenced by popular culture. This panel of Science in Public 2017 presented various on-going investigations of this kind, showing that the critical mass in this area of research is growing
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Vladymyrov, Volodymyr. "Fourth Stage of the Information Revolution: Probable Drawings, Incredible Opportunities." Scientific notes of the Institute of Journalism, no. 1 (76) (2020): 11–24. http://dx.doi.org/10.17721/2522-1272.2020.76.1.

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The article discusses the prospects for the development of the mass communication science in the direction of including in its discourse the modern achievements in the field of the relation between quantum physics and consciousness as well as the artificial intelligence. It will give the media new opportunities to influence mass consciousness, and to impact social processes.It allows to forecast the rise of the next, the fourth stage of the information revolution and to recognize the ways for preparation to it. Quantum physics appears as classical physics develops in the study of the world. Scientists explain quantumness as the relations of everything with everything. Quantumism and consciousness are an already mastered topics of modern science. If we talk about mass consciousness, it should be recognized as a scholar problem and the existence of quantumness as an underlying phenomenon in mass communication. Perhaps this will be the content of the new, fourth stage of the information revolution – after its computer, Internet and mobile stages. Therefore, the urgency of the problem we are addressing is the need to “let in” quantum methods into the thinking, creation and dissemination of the mass-information product in the mass audience. Theorists of our scientific discipline are interested in precisely the new knowledge of quantum “confusion” in the depths of mass consciousness, which exists and manifests itself in the processes of mass communication. Then the quantum approach can be extremely fruitful here. Quantumism here appears both as a universal connection of everything with everything, and as the unpredictability of the nature of these connections from the point of view of ordinary and even dialectical logic. Here, the quantum logic of mass communication should be discovered. It should be noted that so far almost no one has noticed that media interference in the natural mental life of large human communities gives rise to a phenomenon similar to quantum “confusion”, when a change in the state of one “mass” thoughts occurs along with a change in the state of another. Quantum “confusion” is what permeates all the “matter” of human communication / existence. All participants in mass communication are “confused” with themselves, like photons in physics. And they’re not just confused, everybody is one and the part of whole in the external, “physical”, existing, and is the part of the ideal world, with its thoughts, hopes, emotions, “confused” in the Internet The introduction of quantumness as the leading principle of influence on mass consciousness is one of the three steps to a new stage in the information revolution. The second is the growing potential of artificial intelligence. The third is the gradual creation of quantum computers. All these together will make it possible to reach each recipient of information, to enter the inner, ideal world of an individual person, and even to see in this communication an intrapersonal discussion of a person with himself – and to control its course. Probably, the result will be the opportunity to learn to predict the unpredictable in behavior of “this” person in his behavior – in personal, group, intergroup, mass ones.
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Fernandes, Carlos M. "Pherographia: Drawing by Ants." Leonardo 43, no. 2 (April 2010): 107–12. http://dx.doi.org/10.1162/leon.2010.43.2.107.

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This paper addresses the hypothetical relationship of photography and so-called pheromone maps created by an artificial life system that simulates an ant colony and causes its activity to evolve based on the contours of images. Pheromone—used by ants to communicate via the environment—is also simulated, and from the communication and interaction of the swarm with the environment (an image) there results a kind of drawing made with the simulated pheromone. Since ants are able to detect the edges of the image, the outcome is a sketch that resembles the original image, as with old camera obscura drawings. This text explores the observable traits shared by the photographic process and the swarm's pheromone maps. The theme is discussed in the context of the emergent artificial art research field; recent theoretical advances that link swarm intelligence and cognitive sciences are also addressed.
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Iliin, V. P. "How to reorganize computer science and technologies?" Вестник Российской академии наук 89, no. 3 (March 24, 2019): 232–42. http://dx.doi.org/10.31857/s0869-5873893232-242.

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The fundamentals of modern progress are based on the infinite growth rates of the computational and informational capacities of a post-petaflop scale, which provide unthinkable opportunities for acquiring new knowledge and introducing innovation into production, environmental management, and the economic and social spheres. The key method here is based upon the predictive mathematical modeling of processes and phenomena, including theoretical and applied research, super-computations and large-scale computer experiments, operations with mega-data sets, and artificial intelligence. The solution to emerging supertasks requires huge amounts of new generation intelligent software, which is impossible without the formation of new concepts and paradigms of activity, architectural solutions, and constructive technologies. The world is embracing the creation of integrated computing and information environments, forming an instrumental context for automating the construction of models and algorithms, their mapping onto supercomputer platforms, and the creation of comfortable interfaces for users with different professional backgrounds. Such an ecosystem is designed for a long life cycle with continuous development and the coordinated participation of various groups of developers, as well as widespread demand. In fact, this is leading to the formation of a new industry with mass professions requiring high supercomputer literacy. The identified scientific and technological challenges require competent organizational and infrastructural solutions, including the interdepartmental coordination of academic, educational, and production teams
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Ruiz-Rosero, Juan, Gustavo Ramirez-Gonzalez, and Rahul Khanna. "Field Programmable Gate Array Applications—A Scientometric Review." Computation 7, no. 4 (November 11, 2019): 63. http://dx.doi.org/10.3390/computation7040063.

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Field Programmable Gate Array (FPGA) is a general purpose programmable logic device that can be configured by a customer after manufacturing to perform from a simple logic gate operations to complex systems on chip or even artificial intelligence systems. Scientific publications related to FPGA started in 1992 and, up to now, we found more than 70,000 documents in the two leading scientific databases (Scopus and Clarivative Web of Science). These publications show the vast range of applications based on FPGAs, from the new mechanism that enables the magnetic suspension system for the kilogram redefinition, to the Mars rovers’ navigation systems. This paper reviews the top FPGAs’ applications by a scientometric analysis in ScientoPy, covering publications related to FPGAs from 1992 to 2018. Here we found the top 150 applications that we divided into the following categories: digital control, communication interfaces, networking, computer security, cryptography techniques, machine learning, digital signal processing, image and video processing, big data, computer algorithms and other applications. Also, we present an evolution and trend analysis of the related applications.
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Filby, Evan E., and Richard A. Rankin. "Expert overseer for mass spectrometer system." Expert Systems with Applications 4, no. 1 (January 1992): VI. http://dx.doi.org/10.1016/0957-4174(92)90056-x.

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Gao, Xiaozhuan, and Yong Deng. "Quantum model of mass function." International Journal of Intelligent Systems 35, no. 2 (November 26, 2019): 267–82. http://dx.doi.org/10.1002/int.22208.

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Krzywanski, Jaroslaw. "A General Approach in Optimization of Heat Exchangers by Bio-Inspired Artificial Intelligence Methods." Energies 12, no. 23 (November 22, 2019): 4441. http://dx.doi.org/10.3390/en12234441.

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The paper introduces the artificial intelligence (AI) approach as a general method for the design and optimization study of heat exchangers. Genetic Algorithms (GA) and Artificial Neural Networks (ANN) are applied in the paper. An AGENN model, combining Genetic Algorithms with Artificial Neural Networks, was developed and validated against the desired data on a large falling film evaporator. A broad range of operating conditions and geometric configurations are considered in the study. Four kinds of tubes are deliberated, including plain and enhanced tubes. Different tube pass arrangements, i.e., top-to-bottom, bottom-to-top, and side-by-side, are discussed. Finally, the effects of liquid refrigerant mass flow rate, as well as the number of flooded tubes on the performance of the evaporator, are analyzed. The total heat transfer rate of the evaporator, predicted by the model, is in good agreement with the desired data; the maximum error is lower than ±3%. The highest heat transfer rate of the evaporator is 1140.01 kW and corresponds to Turbo EHP tubes, and bottom-to-top tubes pass arrangements, which guarantee the best thermal energy conversion. The presented approach can be referred to as a complementary technique in heat exchanger design procedures, besides the common rating and sizing tasks. It is an effective and alternative method for the existing approaches, considering the complexity of analytical and numerical techniques as well as the high costs of experiments.
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Baldwin, J. F., J. Lawry, and T. P. Martin. "A mass assignment method for prototype induction." International Journal of Intelligent Systems 14, no. 10 (October 1999): 1041–70. http://dx.doi.org/10.1002/(sici)1098-111x(199910)14:10<1041::aid-int6>3.0.co;2-9.

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Dissertations / Theses on the topic "Mass communication|Artificial intelligence|Computer science"

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Singh, Anurag. "Multi-Resolution Superpixels for Visual Saliency Detection in a Large Image Collection." Thesis, University of Louisiana at Lafayette, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3718565.

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Finding what attracts attention is an important task for visual processing. The visual saliency detection finds location of focus of visual attention on the most important or stand-out object in an image or a video sequence. These stand-out objects are composed of regions or superpixels. Moreover, the fixations occur in clusters, which are simulated using superpixels, where superpixels are clusters of pixels bound by the Gestalt principle for perceptual grouping. The visual saliency detection algorithms presented in the dissertation build on the premise that salient regions are high in color contrast, and when compared to other regions, they stand-out.

The most intuitive method to find the salient region is by comparing it to every other region. A region is ranked by its dissimilarities with respect to other regions and highlighting the statistically salient region proportional to their rank. Another way to compare regions is with respect to its local surrounding. Each region is represented with its Dominant Color Descriptor and the color difference between neighbors is found using the Earth Mover's Distance. The multi-resolution framework ensures robustness to the object size, location, and background type.

Image saliency detection using region contrast is often based on the premise that a salient region has a contrast with the background. But the natural biological method involves comparison to a large collection of similar regions. A novel method is presented to efficiently compare the image region to the regions derived from a large, stored collection of images. Intuitively finding video saliency is derived as a special case of a large collection with temporal reference. The various methods presented in the dissertation are tested on publicly available data sets and performs better than existing state-of-the-art methods.

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Gautam, Kumar. "Computer Vision-based Estimation of Body Mass Distribution, Center of Mass, and Body Types| Design and Comparative Study." Thesis, California State University, Long Beach, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10838305.

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Body mass distribution and center of mass (CoM) are important topics in the field of human biomechanics and the healthcare industry. Increasing global obesity has led researchers to measure body parameters. This project focuses on developing an automatic computer vision approach to calculate the body mass distribution and CoM, as well as identify body types with a minimum setup cost.

In this project, a 3-D calibrated experimental setup was devised to take images of four male subjects in three views: front view, left side view, and right side view. First, a method was devised to separate the human subject from the background. Second, a novel approach was developed to find the CoM, percentage body mass distribution, and body types using two models: Simulated Skeleton Model (SSM) and Simulated Skeleton Matrix (SSMA). The CoM using this method was 94.36% of the CoM calculated with a reaction board experiment. Total body mass using this method was 96.6% of the total body mass calculated with the weighing balance. This project has three components: (1) finding the body mass distribution and comparing the results with the weighing balance, (2) finding the CoM and comparing the results with the reaction board experiment, and (3) offering new ways to conceptualize the three body types that are ectomorph, endomorph, and mesomorph with ratings in the range of 0 to 5.

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Sim, Robert. "On visual maps and their automatic construction." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=84842.

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This thesis addresses the problem of automatically constructing a visual representation of an unknown environment that is useful for robotic navigation, localization and exploration. There are two main contributions. First, the concept of the visual map is developed, a representation of the visual structure of the environment, and a framework for learning this structure is provided. Second, methods for automatically constructing a visual map are presented for the case when limited information is available about the position of the camera during data collection.
The core concept of this thesis is that of the visual map, which models a set of image-domain features extracted from a scene. These are initially selected using a measure of visual saliency, and subsequently modelled and evaluated for their utility for robot pose estimation. Experiments are conducted demonstrating the feature learning process and the inferred models' reliability for pose inference.
The second part of this thesis addresses the problem of automatically collecting training images and constructing a visual map. First, it is shown that visual maps are self-organizing in nature, and the transformation between the image and pose domains is established with minimal prior pose information. Second, it is shown that visual maps can be constructed reliably in the face of uncertainty by selecting an appropriate exploration strategy. A variety of such strategies are presented and these approaches are validated experimentally in both simulated and real-world settings.
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Hartmann, William. "ASR-Driven Binary Mask Estimation for Robust Automatic Speech Recognition." The Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1338244649.

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Navaroli, Nicholas Martin. "Generative Probabilistic Models for Analysis of Communication Event Data with Applications to Email Behavior." Thesis, University of California, Irvine, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=3668831.

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Our daily lives increasingly involve interactions with others via different communication channels, such as email, text messaging, and social media. In this context, the ability to analyze and understand our communication patterns is becoming increasingly important. This dissertation focuses on generative probabilistic models for describing different characteristics of communication behavior, focusing primarily on email communication.

First, we present a two-parameter kernel density estimator for estimating the probability density over recipients of an email (or, more generally, items which appear in an itemset). A stochastic gradient method is proposed for efficiently inferring the kernel parameters given a continuous stream of data. Next, we apply the kernel model and the Bernoulli mixture model to two important prediction tasks: given a partially completed email recipient list, 1) predict which others will be included in the email, and 2) rank potential recipients based on their likelihood to be added to the email. Such predictions are useful in suggesting future actions to the user (i.e. which person to add to an email) based on their previous actions. We then investigate a piecewise-constant Poisson process model for describing the time-varying communication rate between an individual and several groups of their contacts, where changes in the Poisson rate are modeled as latent state changes within a hidden Markov model.

We next focus on the time it takes for an individual to respond to an event, such as receiving an email. We show that this response time depends heavily on the individual's typical daily and weekly patterns - patterns not adequately captured in standard models of response time (e.g. the Gamma distribution or Hawkes processes). A time-warping mechanism is introduced where the absolute response time is modeled as a transformation of effective response time, relative to the daily and weekly patterns of the individual. The usefulness of applying the time-warping mechanism to standard models of response time, both in terms of log-likelihood and accuracy in predicting which events will be quickly responded to, is illustrated over several individual email histories.

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Taylor, Julia Michelle. "Towards Informal Computer Human Communication: Detecting Humor in a Restricted Domain." Cincinnati, Ohio : University of Cincinnati, 2008. http://rave.ohiolink.edu/etdc/view.cgi?acc_num=ucin1226600183.

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Thesis (Ph.D.)--University of Cincinnati, 2008.
Advisor: Lawrence J. Mazlack. Title from electronic thesis title page (viewed Feb.16, 2009). Keywords: artificial intelligence; computational humor; natural language understanding. Includes abstract. Includes bibliographical references.
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Shi, Shaohuai. "Communication optimizations for distributed deep learning." HKBU Institutional Repository, 2020. https://repository.hkbu.edu.hk/etd_oa/813.

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With the increasing amount of data and the growing computing power, deep learning techniques using deep neural networks (DNNs) have been successfully applied in many practical artificial intelligence applications. The mini-batch stochastic gradient descent (SGD) algorithm and its variants are the most widely used algorithms in training deep models. The SGD algorithm is an iterative algorithm that needs to update the model parameters many times by traversing the training data, which is very time-consuming even using the single powerful GPU or TPU. Therefore, it becomes a common practice to exploit multiple processors (e.g., GPUs or TPUs) to accelerate the training process using distributed SGD. However, the iterative nature of distributed SGD requires multiple processors to iteratively communicate with each other to collaboratively update the model parameters. The intensive communication cost easily becomes the system bottleneck and limits the system scalability. In this thesis, we study the communication-efficient techniques for distributed SGD to improve the system scalability and thus accelerate the training process. We identify the performance issues in distributed SGD through benchmarking and modeling and then propose several communication optimization algorithms to address the communication issues. First, we build a performance model with a directed acyclic graph (DAG) to modeling the training process of distributed SGD and verify the model with extensive benchmarks on existing state-of-the-art deep learning frameworks including Caffe, MXNet, TensorFlow, and CNTK. Our benchmarking and modeling point out that existing optimizations for the communication problems are sub-optimal, which we need to address in this thesis. Second, to address the startup problem (due to the high latency of each communication) of layer-wise communications with wait-free backpropagation (WFBP), we propose an optimal gradient merging solution for WFBP, named MG-WFBP, that exploits the layer-wise property to well overlap the communication tasks with the computing tasks and can be adaptive to the training environments. Experiments are conducted on dense-GPU clusters with Ethernet and InfiniBand, and the results show that MG-WFBP can well address the startup problem in distributed training of layer-wise structured DNNs. Third, to make the high computing-intensive training tasks be possible in GPU clusters with low- bandwidth interconnect, we investigate the gradient compression techniques in distributed training. The top-{dollar}k{dollar} sparsification can well compress the communication traffic with little impact on the model convergence, but it suffers from a linear communication complexity to the number of workers so that top-{dollar}k{dollar} sparsification cannot scale well in large-scale clusters. To address the problem, we propose a global top-{dollar}k{dollar} (gTop-{dollar}k{dollar}) sparsification algorithm that reduces the communication complexity to be logarithmic to the number of workers. We also provide detailed theoretical analysis for the gTop-{dollar}k{dollar} SGD training algorithm, and the theoretical results show that our gTop-{dollar}k{dollar} SGD has the same order of convergence rate with SGD. Experiments are conducted on up to 64-GPU cluster to verify that gTop-{dollar}k{dollar} SGD significantly improves the system scalability with only a slight impact on the model convergence. Lastly, to enjoy the both benefits of the pipelining technique and the gradient sparsification algorithm, we propose a new distributed training algorithm, layer-wise adaptive gradient sparsification SGD (LAGS-SGD), which supports layer-wise sparsification and communication, and we theoretically and empirically prove that the LAGS-SGD preserves the convergence properties. To further alliterate the impact of the startup problem of layer-wise communications in LAGS-SGD, we also propose the optimal gradient merging solution for LAGS-SGD, named OMGS-SGD, and theoretical prove its optimality. The experimental results on a 16-node GPU cluster connected 1Gbps Ethernet show that OMGS-SGD can always improve the system scalability while the model convergence properties are not affected
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Shackelford, Philip Clayton. "On the Wings of the Wind: The United States Air Force Security Service and Its Impact on Signals Intelligence in the Cold War." Kent State University Honors College / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ksuhonors1399284818.

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Woodward, Mark P. "Framing Human-Robot Task Communication as a Partially Observable Markov Decision Process." Thesis, Harvard University, 2012. http://dissertations.umi.com/gsas.harvard:10188.

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As general purpose robots become more capable, pre-programming of all tasks at the factory will become less practical. We would like for non-technical human owners to be able to communicate, through interaction with their robot, the details of a new task; I call this interaction "task communication". During task communication the robot must infer the details of the task from unstructured human signals, and it must choose actions that facilitate this inference. In this dissertation I propose the use of a partially observable Markov decision process (POMDP) for representing the task communication problem; with the unobservable task details and unobservable intentions of the human teacher captured in the state, with all signals from the human represented as observations, and with the cost function chosen to penalize uncertainty. This dissertation presents the framework, works through an example of framing task communication as a POMDP, and presents results from a user experiment where subjects communicated a task to a POMDP-controlled virtual robot and to a human controlled virtual robot. The task communicated in the experiment consisted of a single object movement and the communication in the experiment was limited to binary approval signals from the teacher. This dissertation makes three contributions: 1) It frames human-robot task communication as a POMDP, a widely used framework. This enables the leveraging of techniques developed for other problems framed as a POMDP. 2) It provides an example of framing a task communication problem as a POMDP. 3) It validates the framework through results from a user experiment. The results suggest that the proposed POMDP framework produces robots that are robust to teacher error, that can accurately infer task details, and that are perceived to be intelligent.
Engineering and Applied Sciences
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Fiedler, Heather Starr. "Journalism and Mass Communication Education in The Age of Technology." NSUWorks, 2005. http://nsuworks.nova.edu/gscis_etd/516.

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The developmental research project was undertaken to determine the best way to structure the future of journalism and mass communication education so that it remains a viable discipline within the academy. New media technology is an emerging discipline within the journalism field. While many new jobs exist for graduates who are skilled in the field, only a small number of colleges and universities are offering undergraduate programs to train students in new media technology. The goal of the dissertation was to propose a new undergraduate major in new media technology that schools may implement. The literature review traces the origins and development of journalism and mass communication education through the 19th and 20th centuries and focuses on the emerging field of new media technology and online journalism. To help answer the research questions, a survey questionnaire was distributed to journalism and mass communications educators at 108 programs in the United States and to more than 300 media professionals. All the programs are accredited by the Accrediting Council on Education in Journalism and Mass Communications (ACEJMC), and the media professionals are all members of the Online News Association (ON A). The total number of participants was 102. In the surveys, participants shared their views on the current state of journalism and mass communication education as well as the new media industry through a combination of rank-order items, Likert-type scales, and open-ended questions. Results were used to correlate industry requirements with program offerings to prescribe the best possible undergraduate program in new media technology. The content, coverage and feasibility of the model program were validated by a panel of experts.
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Books on the topic "Mass communication|Artificial intelligence|Computer science"

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David, Hales, ed. Multi-agent-based simulation III: 4th international workshop, MABS 2003, Melbourne, Australia, July 14, 2003 : revised papers. Berlin: Springer, 2003.

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S, Sichman Jaime, Bousquet François 1963-, and Davidsson Paul 1964-, eds. Multi-agent-based simulation II: Third international workshop, MABS 2002, Bologna, Italy, July 2002 : revised papers. Berlin: Springer, 2003.

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Koichi, Kurumatani, Chen Shu-Heng 1959-, and Ohuchi Azuma, eds. Multi-agent for mass user support: International workshop, MAMUS 2003, Acapulco, Mexico, August 10, 2003 : revised and invited papers. Berlin: Springer, 2004.

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Portmann, Edy. The FORA Framework: A Fuzzy Grassroots Ontology for Online Reputation Management. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013.

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Ortony, Andrew. Communication from an Artificial Intelligence Perspective: Theoretical and Applied Issues. Berlin, Heidelberg: Springer Berlin Heidelberg, 1992.

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Delgado-Frias, José G., and Will R. Moore. VLSI for neural networks and artificial intelligence. New York: Springer Science+Business Media, 1994.

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IFIP International Conference on Intelligence in Communication Systems (2005 Montreal, Québec). Intelligence in communication systems: IFIP International Conference on Intelligence in Communication Systems, INTELLCOMM 2005, Montreal, Canada, October 17-19, 2005. New York: Springer Science+Business Media, 2005.

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Rasmussen, Leif Bloch. Computers and Networks in the Age of Globalization: IFIP TC9 Fifth World Conference on Human Choice and Computers August 25-28, 1998, Geneva, Switzerland. Boston, MA: Springer US, 2001.

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Ishida, Yoshiteru. Immunity-Based Systems: A Design Perspective. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004.

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Verhaegh, Wim F. J. Algorithms in Ambient Intelligence. Dordrecht: Springer Netherlands, 2004.

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Book chapters on the topic "Mass communication|Artificial intelligence|Computer science"

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Manoharan, N., and Arunkumar Thangavelu. "An Experimental Evaluation of Integrated Dematal and Fuzzy Cognitive Maps for Cotton Yield Prediction." In Cognitive Science and Artificial Intelligence, 31–43. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-6698-6_4.

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Frank, Andrew U. "Spatial Communication with Maps: Defining the Correctness of Maps Using a Multi-Agent Simulation." In Lecture Notes in Computer Science, 80–99. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/3-540-45460-8_7.

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Bora, Vibha Bafna, A. G. Kothari, and A. G. Keskar. "Mammogram Segmentation Using Rough k-Means and Mass Lesion Classification with Artificial Neural Network." In Communications in Computer and Information Science, 60–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-35326-0_7.

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Rüttgers, Mario, Seong-Ryong Koh, Jenia Jitsev, Wolfgang Schröder, and Andreas Lintermann. "Prediction of Acoustic Fields Using a Lattice-Boltzmann Method and Deep Learning." In Lecture Notes in Computer Science, 81–101. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-59851-8_6.

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Abstract Using traditional computational fluid dynamics and aeroacoustics methods, the accurate simulation of aeroacoustic sources requires high compute resources to resolve all necessary physical phenomena. In contrast, once trained, artificial neural networks such as deep encoder-decoder convolutional networks allow to predict aeroacoustics at lower cost and, depending on the quality of the employed network, also at high accuracy. The architecture for such a neural network is developed to predict the sound pressure level in a 2D square domain. It is trained by numerical results from up to 20,000 GPU-based lattice-Boltzmann simulations that include randomly distributed rectangular and circular objects, and monopole sources. Types of boundary conditions, the monopole locations, and cell distances for objects and monopoles serve as input to the network. Parameters are studied to tune the predictions and to increase their accuracy. The complexity of the setup is successively increased along three cases and the impact of the number of feature maps, the type of loss function, and the number of training data on the prediction accuracy is investigated. An optimal choice of the parameters leads to network-predicted results that are in good agreement with the simulated findings. This is corroborated by negligible differences of the sound pressure level between the simulated and the network-predicted results along characteristic lines and by small mean errors.
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Zhou, Wenjie, Xiaofeng Liu, Qing Guo, Xuemai Gu, and Rui E. "Comparative Analysis of Communication Links Between Earth-Moon and Earth-Mars." In Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, 155–65. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69066-3_15.

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Walrand, Jean. "Speech Recognition: A." In Probability in Electrical Engineering and Computer Science, 205–15. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-49995-2_11.

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AbstractSpeech recognition can be formulated as the problem of guessing a sequence of words that produces a sequence of sounds. The human brain is remarkably good at solving this problem, even though the same words correspond to many different sounds, because of accents or characteristics of the voice. Moreover, the environment is always noisy, to that the listeners hear a corrupted version of the speech.Computers are getting much better at speech recognition and voice command systems are now common for smartphones (Siri), automobiles (GPS, music, and climate control), call centers, and dictation systems. In this chapter, we explain the main ideas behind the algorithms for speech recognition and for related applications.The starting point is a model of the random sequence (e.g., words) to be recognized and of how this sequence is related to the observation (e.g., voice). The main model is called a hidden Markov chain. The idea is that the successive parts of speech form a Markov chain and that each word maps randomly to some sounds. The same model is used to decode strings of symbols in communication systems.Section 11.1 is a general discussion of learning. The hidden Markov chain model used in speech recognition and in error decoding is introduced in Sect. 11.2. That section explains the Viterbi algorithm. Section 11.3 discusses expectation maximization and clustering algorithms. Section 11.4 covers learning for hidden Markov chains.
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Miori, Virginia M., John Yi, Rashmi Malhotra, and Ronald K. Klimberg. "From Business Intelligence to Data Science." In Advances in Business Information Systems and Analytics, 218–37. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-7998-4799-1.ch008.

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The use of information technology and decision support concepts at the operational business level were slow to take hold in the 20th century. In 2010, the authors documented the evolution and current state of the field of business intelligence and analytics (BIA). In the last decade, however, through the resurgence and mainstream use of artificial intelligence, machine learning algorithms, the development of inexpensive cloud-based mass storage, and the internet-of-things, business intelligence has evolved into data science. In this chapter, the authors trace this evolution across the diverse areas of data science and identify extremely useful advancements and best practices in the field.
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Pal, Kamalendu. "Managing Green Supply Chain Transportation Operation Using Multi-Agent Framework." In Advances in Logistics, Operations, and Management Science, 305–24. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8040-0.ch014.

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The concept of software agent has become essential in both artificial intelligence (AI) and mainstream computer science. Multi-agent systems (MAS) provide the way to design and implement information system solutions that exhibit flexibility in a distributed environment. Simulation plays a crucial role in analyzing MAS solutions' behaviour during the automated software solution analysis and design phase. This chapter uses the idea of multi-agent computing and provides a software framework for green supply chain management, carbon footprint assessment planning for a multimodal transportation scenario. In this framework, the software agents' operational activities managed with the help of a hybrid knowledge-based system that uses rule-based reasoning (RBR) and case-based reasoning (CBR). The presented framework accepts a transport logistic service request and creates a transport plan that helps optimize environmental impact (i.e., CO2 footprint) by retrieving best practices (i.e., carbon footprint perspective) for each route from a repository of best-practiced cases.
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Yu, Y., W. Lin, G. Dai, and Q. Yuan. "Reliable design for Earth-Mars transfer trajectory." In Future Communication, Information and Computer Science, 225–29. CRC Press, 2015. http://dx.doi.org/10.1201/b18049-53.

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Grunwald, Armin, and Carsten Orwat. "Technology Assessment of Information and Communication Technologies." In Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction, 600–611. IGI Global, 2019. http://dx.doi.org/10.4018/978-1-5225-7368-5.ch045.

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Technology assessment (TA) has taken up the field of information science and technology (IST) as a subject of study from the 1970s on. Nowadays, this field is of central relevance to TA in a triple respect: (1) as research field per se (e.g., with regard to impact dimensions such as privacy, data protection, increasing use of autonomous agents, safety and security, sustainable development, intellectual property rights, regulation, societal vulnerability, etc.). It is (1) also of major and even increasing importance by entering and influencing other fields of technology (e.g., energy supply, military, robotics, logistics, nanotechnology, cognitive science, neuroscience, etc.). Finally, (2) several new services made available by IST developments are of high utility in TA practice of scientific projects and policy advice (e.g., in the fields of e-participation). This chapter provides an overview of TA with respect to its origin, its development, and its current situation in general, followed by a more specific consideration of TA themes and activities in the IST field.
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Conference papers on the topic "Mass communication|Artificial intelligence|Computer science"

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Khan, Muhammad Zeerak, Faizan Hassan, Muhammad Usman, Usman Ansari, and Shaheena Noor. "Virtual Reality in Multiplayer Carrom Game with Artificial Intelligence." In 2018 12th International Conference on Mathematics, Actuarial Science, Computer Science and Statistics (MACS). IEEE, 2018. http://dx.doi.org/10.1109/macs.2018.8628394.

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Rabenau, Erhard. "Planning Science Data Return of Mars Express with Support of Artificial Intelligence." In SpaceOps 2006 Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2006. http://dx.doi.org/10.2514/6.2006-5931.

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Nguyen, Tam V., and Luoqi Liu. "Salient Object Detection with Semantic Priors." In Twenty-Sixth International Joint Conference on Artificial Intelligence. California: International Joint Conferences on Artificial Intelligence Organization, 2017. http://dx.doi.org/10.24963/ijcai.2017/628.

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Salient object detection has increasingly become a popular topic in cognitive and computational sciences, including computer vision and artificial intelligence research. In this paper, we propose integrating semantic priors into the salient object detection process. Our algorithm consists of three basic steps. Firstly, the explicit saliency map is obtained based on the semantic segmentation refined by the explicit saliency priors learned from the data. Next, the implicit saliency map is computed based on a trained model which maps the implicit saliency priors embedded into regional features with the saliency values. Finally, the explicit semantic map and the implicit map are adaptively fused to form a pixel-accurate saliency map which uniformly covers the objects of interest. We further evaluate the proposed framework on two challenging datasets, namely, ECSSD and HKUIS. The extensive experimental results demonstrate that our method outperforms other state-of-the-art methods.
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Sarem, Roozbeh, Ahmad Jawaid Rahimi, and S. Varadharajan. "Estimation of Seismic response of Mass Irregular building frames using Artificial Intelligence." In 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence). IEEE, 2019. http://dx.doi.org/10.1109/confluence.2019.8776922.

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Yu, Ai-Rong, Jun Wang, Yan-Jie Niu, Guo-You Chen, and Yong Wang. "Research on Communication Anti Jamming System Based on Multitier Architecture." In International Conference on Computer Science and Artificial Intelligence (CSAI2016). WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813220294_0042.

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Zhang, Guo-Hui, Ang Gao, Jie Cao, and Yuan Wang. "Summarize of Communication Network MAC Layer Protocol Oriented Network Fire Control." In International Conference on Computer Science and Artificial Intelligence (CSAI2016). WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813220294_0004.

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Li, Jianyao, and Fang Liu. "Consumer Attitude Towards Computer Mediated Communication-A Cross-Cultural Study." In 2010 International Conference on Management and Service Science (MASS 2010). IEEE, 2010. http://dx.doi.org/10.1109/icmss.2010.5576830.

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Kang, Si-Min, Fu-Cai Qian, Wei-Bin Cheng, and Yue-Long Wang. "The Weak Signal Detection for Drill Pipe Acoustic Communication Based on Stochastic Resonance." In International Conference on Computer Science and Artificial Intelligence (CSAI2016). WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813220294_0095.

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Hussain, Safdar, Wasim Ahmed, Rana Muhammad Sohail Jafar, Ambar Rabnawaz, and Jian-Zhou Yang. "An Impact of Consumer’s Internet Information Adoption Through Electronic Word of Mouth Communication." In International Conference on Computer Science and Artificial Intelligence (CSAI2016). WORLD SCIENTIFIC, 2017. http://dx.doi.org/10.1142/9789813220294_0097.

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Wang, Haotian. "Residual Mask Based on MobileNet-V2 for Driver's Dangerous Behavior Recognition." In CSAI2019: 2019 3rd International Conference on Computer Science and Artificial Intelligence. New York, NY, USA: ACM, 2019. http://dx.doi.org/10.1145/3374587.3374621.

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Reports on the topic "Mass communication|Artificial intelligence|Computer science"

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Borrett, Veronica, Melissa Hanham, Gunnar Jeremias, Jonathan Forman, James Revill, John Borrie, Crister Åstot, et al. Science and Technology for WMD Compliance Monitoring and Investigations. The United Nations Institute for Disarmament Research, December 2020. http://dx.doi.org/10.37559/wmd/20/wmdce11.

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The integration of novel technologies for monitoring and investigating compliance can enhance the effectiveness of regimes related to weapons of mass destruction (WMD). This report looks at the potential role of four novel approaches based on recent technological advances – remote sensing tools; open-source satellite data; open-source trade data; and artificial intelligence (AI) – in monitoring and investigating compliance with WMD treaties. The report consists of short essays from leading experts that introduce particular technologies, discuss their applications in WMD regimes, and consider some of the wider economic and political requirements for their adoption. The growing number of space-based sensors is raising confidence in what open-source satellite systems can observe and record. These systems are being combined with local knowledge and technical expertise through social media platforms, resulting in dramatically improved coverage of the Earth’s surface. These open-source tools can complement and augment existing treaty verification and monitoring capabilities in the nuclear regime. Remote sensing tools, such as uncrewed vehicles, can assist investigators by enabling the remote collection of data and chemical samples. In turn, this data can provide valuable indicators, which, in combination with other data, can inform assessments of compliance with the chemical weapons regime. In addition, remote sensing tools can provide inspectors with real time two- or three-dimensional images of a site prior to entry or at the point of inspection. This can facilitate on-site investigations. In the past, trade data has proven valuable in informing assessments of non-compliance with the biological weapons regime. Today, it is possible to analyse trade data through online, public databases. In combination with other methods, open-source trade data could be used to detect anomalies in the biological weapons regime. AI and the digitization of data create new ways to enhance confidence in compliance with WMD regimes. In the context of the chemical weapons regime, the digitization of the chemical industry as part of a wider shift to Industry 4.0 presents possibilities for streamlining declarations under the Chemical Weapons Convention (CWC) and for facilitating CWC regulatory requirements.
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Chornodon, Myroslava. FEAUTURES OF GENDER IN MODERN MASS MEDIA. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11064.

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The article clarifies of gender identity stereotypes in modern media. The main gender stereotypes covered in modern mass media are analyzed and refuted. The model of gender relations in the media is reflected mainly in the stereotypical images of men and woman. The features of the use of gender concepts in modern periodicals for women and men were determined. The most frequently used derivatives of these macroconcepts were identified and analyzed in detail. It has been found that publications for women and men are full of various gender concepts that are used in different contexts. Ingeneral, theanalysisofthe concept-maximums and concept-minimum gender and their characteristics is carried out in the context of gender stereotypes that have been forme dand function in the society, system atizing the a ctual presentations. The study of the gender concept is relevant because it reveals new trends and features of modern gender images. Taking into account the special features of gender-labeled periodicals in general and the practical absence of comprehensive scientific studies of the gender concept in particular, there is a need to supplement Ukrainian science with this topic. Gender psychology, which is served by methods of various sciences, primarily sociological, pedagogical, linguistic, psychological, socio-psychological. Let us pay attention to linguistic and psycholinguistic methods in gender studies. Linguistic methods complement intelligence research tasks, associated with speech, word and text. Psycholinguistic methods used in gender psychology (semantic differential, semantic integral, semantic analysis of words and texts), aimed at studying speech messages, specific mechanisms of origin and perception, functions of speech activity in society, studying the relationship between speech messages and gender properties participants in the communication, to analyze the linguistic development in connection with the general development of the individual. Nowhere in gender practice there is the whole arsenal of psychological methods that allow you to explore psychological peculiarities of a person like observation, experiments, questionnaires, interviews, testing, modeling, etc. The methods of psychological self-diagnostics include: the gender aspect of the own socio-psychological portrait, a gender biography as a variant of the biographical method, aimed at the reconstruction of individual social experience. In the process of writing a gender autobiography, a person can understand the characteristics of his gender identity, as well as ways and means of their formation. Socio-psychological methods of studying gender include the study of socially constructed women’s and men’s roles, relationships and identities, sexual characteristics, psychological characteristics, etc. The use of gender indicators and gender approaches as a means of socio-psychological and sociological analysis broadens the subject boundaries of these disciplines and makes them the subject of study within these disciplines. And also, in the article a combination of concrete-historical, structural-typological, system-functional methods is implemented. Descriptive and comparative methods, method of typology, modeling are used. Also used is a method of content analysis for the study of gender content of modern gender-stamped journals. It was he who allowed quantitatively to identify and explore the features of the gender concept in the pages of periodicals for women and men. A combination of historical, structural-typological, system-functional methods is also implemented in the article. Descriptive and comparative methods, method of typology, modeling are used. A method of content analysis for the study of gender content of modern gender-labeled journals is also used. It allowed to identify and explore the features of the gender concept quantitatively in the periodicals for women and men. The conceptual perception and interpretation of the gender concept «woman», which is highlighted in the modern gender-labeled press in Ukraine, requires the elaboration of the polyfunctionality of gender interpretations, the comprehension of the metaphorical perception of this image and its role and purpose in society. A gendered approach to researching the gender content of contemporary periodicals for women and men. Conceptual analysis of contemporary gender-stamped publications within the gender conceptual sphere allows to identify and correlate the meta-gender and gender concepts that appear in society.
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Yatsymirska, Mariya. SOCIAL EXPRESSION IN MULTIMEDIA TEXTS. Ivan Franko National University of Lviv, February 2021. http://dx.doi.org/10.30970/vjo.2021.49.11072.

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The article investigates functional techniques of extralinguistic expression in multimedia texts; the effectiveness of figurative expressions as a reaction to modern events in Ukraine and their influence on the formation of public opinion is shown. Publications of journalists, broadcasts of media resonators, experts, public figures, politicians, readers are analyzed. The language of the media plays a key role in shaping the worldview of the young political elite in the first place. The essence of each statement is a focused thought that reacts to events in the world or in one’s own country. The most popular platform for mass information and social interaction is, first of all, network journalism, which is characterized by mobility and unlimited time and space. Authors have complete freedom to express their views in direct language, including their own word formation. Phonetic, lexical, phraseological and stylistic means of speech create expression of the text. A figurative word, a good aphorism or proverb, a paraphrased expression, etc. enhance the effectiveness of a multimedia text. This is especially important for headlines that simultaneously inform and influence the views of millions of readers. Given the wide range of issues raised by the Internet as a medium, research in this area is interdisciplinary. The science of information, combining language and social communication, is at the forefront of global interactions. The Internet is an effective source of knowledge and a forum for free thought. Nonlinear texts (hypertexts) – «branching texts or texts that perform actions on request», multimedia texts change the principles of information collection, storage and dissemination, involving billions of readers in the discussion of global issues. Mastering the word is not an easy task if the author of the publication is not well-read, is not deep in the topic, does not know the psychology of the audience for which he writes. Therefore, the study of media broadcasting is an important component of the professional training of future journalists. The functions of the language of the media require the authors to make the right statements and convincing arguments in the text. Journalism education is not only knowledge of imperative and dispositive norms, but also apodictic ones. In practice, this means that there are rules in media creativity that are based on logical necessity. Apodicticity is the first sign of impressive language on the platform of print or electronic media. Social expression is a combination of creative abilities and linguistic competencies that a journalist realizes in his activity. Creative self-expression is realized in a set of many important factors in the media: the choice of topic, convincing arguments, logical presentation of ideas and deep philological education. Linguistic art, in contrast to painting, music, sculpture, accumulates all visual, auditory, tactile and empathic sensations in a universal sign – the word. The choice of the word for the reproduction of sensory and semantic meanings, its competent use in the appropriate context distinguishes the journalist-intellectual from other participants in forums, round tables, analytical or entertainment programs. Expressive speech in the media is a product of the intellect (ability to think) of all those who write on socio-political or economic topics. In the same plane with him – intelligence (awareness, prudence), the first sign of which (according to Ivan Ogienko) is a good knowledge of the language. Intellectual language is an important means of organizing a journalistic text. It, on the one hand, logically conveys the author’s thoughts, and on the other – encourages the reader to reflect and comprehend what is read. The richness of language is accumulated through continuous self-education and interesting communication. Studies of social expression as an important factor influencing the formation of public consciousness should open up new facets of rational and emotional media broadcasting; to trace physical and psychological reactions to communicative mimicry in the media. Speech mimicry as one of the methods of disguise is increasingly becoming a dangerous factor in manipulating the media. Mimicry is an unprincipled adaptation to the surrounding social conditions; one of the most famous examples of an animal characterized by mimicry (change of protective color and shape) is a chameleon. In a figurative sense, chameleons are called adaptive journalists. Observations show that mimicry in politics is to some extent a kind of game that, like every game, is always conditional and artificial.
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