Information Communication Theory Research Articles

An informative dual ForkNet for video anomaly detection

An autoencoder for video anomaly detection task is a type of algorithm with the primary purpose of learning an “informative” representation of the normal data that can be used for identifying the abnormal data by learning to reconstruct a set of input observations. Based on the encoding-decoding structure, we explore a novel dual ForkNet architecture that can dissociate and process the spatio-temporal representation. It is well-known in the information theory community that most autoencoders coding processes are inevitably accompanied by a certain loss of information. In this dual ForkNet, we focus on mitigating the information loss problem and propose a novel architectural recalibration approach, which we term the “Informetrics Recalibration” (IR). It can adaptively recalibrate latent feature representation by explicitly modelling the similarity between the corresponding feature maps of encoder and decoder, and retain more useful semantic information to generate greater differentiation between normal and abnormal events. Additionally, because the structure of the autoencoder itself determines the difficulty to obtain deep semantic information, we introduce a Secondary Encoder (SE) in each ForkNet, so as to recalibrate target features responses of latent feature representation. Our model is easy to be trained and robust to be applied, because it basically consists of some ResNet blocks without using complicated modules. Extensive experiments on the five publicly available benchmarks show that our model outperforms the existing state-of-the-art architectures, demonstrating our framework’s effectiveness.

Information, Coding, and Biological Function: The Dynamics of Life.

In the mid-20th century, two new scientific disciplines emerged forcefully: molecular biology and information-communication theory. At the beginning, cross-fertilization was so deep that the term genetic code was universally accepted for describing the meaning of triplets of mRNA (codons) as amino acids. However, today, such synergy has not taken advantage of the vertiginous advances in the two disciplines and presents more challenges than answers. These challenges not only are of great theoretical relevance but also represent unavoidable milestones for next-generation biology: from personalized genetic therapy and diagnosis to Artificial Life to the production of biologically active proteins. Moreover, the matter is intimately connected to a paradigm shift needed in theoretical biology, pioneered a long time ago, that requires combined contributions from disciplines well beyond the biological realm. The use of information as a conceptual metaphor needs to be turned into quantitative and predictive models that can be tested empirically and integrated in a unified view. Successfully achieving these tasks requires a wide multidisciplinary approach, including Artificial Life researchers, to address such an endeavour.

Novel Generalized Entropy Measure's Characteristics Associated with Code-Word Length

In this article, we introduce a novel, all-purpose entropy measure and derive a new, all-purpose average codeword length in accordance with it. After that, we determined new average generalized codeword length constraints in terms of additional metrics of generalized entropy. In addition, we demonstrate that the metrics employed in this study are generalizations of other metrics typically employed in the coding and information theory communities.

Research on strategies to enhance the effectiveness of financial information dissemination under the background of rural revitalization

This paper aims to put forward optimization strategies for the shortcomings of rural financial information dissemination, so as to improve the effectiveness of financial information dissemination in rural areas，so as to form a win-win situation of two-way financial information interaction between rural commercial banks and farmers, stimulating rural development. Under the background of rural revitalization, financial information dissemination can help financial enterprises establish brand image and promote financial products and services, which plays a significant role in getting through the "last mile" of Inclusive finance. At present, facing the dual effects of policy environment and market environment, banks and other financial institutions are altering their focus and continuously increasing the dissemination of rural financial information. However, due to the influence of multiple factors such as regional environment and audience characteristics, related products, services and financial knowledge have not been fully, sufficiently and effectively disseminated. This paper takes the communication behavior of farmers and rural commercial banks in Jiangsu as the research object.In order to integrate into consumers' life and understand consumers' exposed or potential needs, we analyze the characteristics of information communication and audience in rural areas in the form of questionnaire and written interview, and put forward targeted optimization strategies according to the problems and difficulties existing in the current actual communication, so as to improve the effectiveness of financial information communication.The innovative feature of this paper is to carry out interdisciplinary research, cross integrate the theories of Journalism and communication and finance, and apply the information communication theory in journalism and communication to the field of finance.

The impact of contagion effects of media reports, investors’ sentiment and attention on the stock market based on HAR-RV model

In this paper, the Shanghai Securities Composite Index and 18 A-share listed companies are used to justify the impact of contagion effects of media reports, investors’ sentiment and attention on stock market. Five indicators are built: The news media optimistic tendency, investors’ attention, investors’ sentiment, investors’ sentiment disagreement and media sentiment disagreement. Furthermore, theoretical models are constructed based on HAR-RV model to analyze the contagion structure between media sentiment and investors’ sentiment and its impact on the performance of stock market. Additionally, the “reverse silence spiral” theory is proposed to analyze the regulatory role of sentiment disagreement in the contagion effects according to the information communication theory. The empirical results demonstrate the following conclusions. (1) The optimism degree of media reports positively affects investors’ subjective sentiment and increases their transaction volume. (2) Strengthening investors’ attention to corporate-related information is the main path by which media sentiment interferes with investors’ sentiment. (3) Media sentiment will indirectly affect the excess return and volatility of stocks through investors’ sentiment and their transactions. (4) Media sentiment disagreement has weakened the influence of media sentiment on investors’ attention and sentiment. Investors’ sentiment disagreement has alleviated its impact on the excess returns and volatility of stocks.

Identification Codes: A Topical Review With Design Guidelines for Practical Systems

A wide range of information technology applications require the identification of a particular message or label that represents the identity of an object at a distance, e.g., over a wireless channel. Conventionally, the underlying information that represents the identity is transmitted over the channel, following the information-theoretic concept of message transmission. If the purpose of the interaction over the channel is only to verify (match) an identity, then the concept of identification over channels—utilizing the identification codes that have been developed by the information theory community—can provide an exponential efficiency gain over message transmission. This topical review article conducts for the first time a comprehensive detailed evaluation of the existing identification codes for the practically relevant regime of finite parameters. We examine essentially all published identification codes, including codes based on inner constant weight codes that are concatenated with outer linear block codes, such as Reed-Solomon and Reed-Muller codes. Specifically, we conduct a holistic identification code comparison based on the logarithm of the number of representable identities (in shannon), the size (in bit) of the transmitted cue that represents an identity, and the corresponding type II error probability bound for essentially all existing identification codes. Based on the resulting insights, we formulate guidelines for the design of practical (finite-parameter) identification codes. For instance, we find that a linear block code (without concatenation with a sophisticated inner constant-weight code) is sufficient for most practical identification code usages.

The influence of AI word‐of‐mouth system on consumers' purchase behaviour: The mediating effect of risk perception

AbstractArtificial intelligence (AI) technology is playing an increasingly important role in achieving precision marketing. AI word‐of‐mouth system marketing focuses most on the entry point of consumers—the key information that leads consumers to buy. Based on consumer behaviour theory and information communication theory, this study constructs a research model of the influence of positive and negative online word of mouth on consumer purchase behaviour from the AI word‐of‐mouth system's four dimensions: professional degree, information quality, information quantity and information intensity. The results show that in the analysis of perceived risk, whether for positive or negative online word of mouth, consumers pay more attention to the number of information features than information quality and information intensity. In the purchase behaviour analysis, consumers are most concerned about information quality and information intensity. Perceived risk plays a mediating role in the influence of AI word of mouth on purchasing behaviour.

The moderating impact of product shadows on ad effectiveness perceptions for gestalt versus component product frames, product presentation color, and consumer visual processing modes

PurposeThis research aims to investigate the moderating impact of product shadows in gestalt versus component product frames on ad effectiveness perceptions. It offers insights on shadow-compatible and incompatible modes of product presentation color as well as consumer visual processing modes that offer optimal advertising effectiveness.Design/methodology/approachThis research begins with a content analysis of some popular print magazines and builds on qualitative findings from interviews conducted with two industry executives. It then undertakes four experiments to test the proposed hypotheses following a more deductive approach.FindingsResults reveal that incorporating product shadows increase ad effectiveness for gestalt products presented in black-and-white, but lower ad effectiveness for component products presented in color. Additionally, ad effectiveness for a gestalt (component) product presented in black-and-white (color) increases (decreases) in the presence of product shadow when consumers are currently processing in a compatible, gestalt (component) visual mode.Research limitations/implicationsIn addition to extending the limited marketing research on product shadows, this research contributes to the literature studying information communication theory (ICT) and advertising effectiveness, Construal-Level Theory (CLT), Heuristic–Systematic Model (HSM) of information processing and stylistic visual cues used in advertising.Practical implicationsThis research is focused on advertising effectiveness, providing a tangible outcome of interest to practitioners. An optimal use of this simple, inexpensive and stylistic ad element can help managers design effective communications without forgoing established brand equity.Originality/valueLimited marketing research on product shadows has only looked at their impact on product luxury implications (Sharma, 2016), experiential versus functional brand evaluations (Sharma, 2018) and product heaviness perceptions (Sharma and Romero, 2020). To the best of the authors’ knowledge, this work is the first to investigate specific gestalt versus component product contexts and the role of black-and-white and colored product presentations, along with specific consumer visual processing modes where shadows either increase or decrease the overall ad effectiveness.

Modulation of cortical oscillations by periodic electrical stimulation is frequency-dependent

The brain oscillations play a pivotal role in transmitting and processing the information. Periodic electrical stimulation has been proposed to shape the oscillations. However, how the periodic electrical stimulation modulates the oscillatory activities remains poorly understood. To address this question, a modified cortical network by adding the brain state information (eye–open and eye–closed states) and synaptic plasticity is employed. Constraining on eye–open state and without considering the synaptic plasticity, the numerical simulation results have shown that the network responses are strong frequency–dependent and the underlying mechanism of the network oscillations has been recognized as three typical neural phenomena, that is resonance, entrainment, and nonlinear oscillation, induced by periodic stimulation with different frequencies and amplitudes. We further prove the frequency dependency of network responses through theoretical analysis. Moreover, the impacts of the brain state have been explored. It is shown that the brain state has little impact on the network oscillatory response during stimulus and generates only a very short–lasting effect. However, the introduce of the plasticity in the cortical network makes the periodic stimulation generate obvious post—stimulus effects. Even though the stimulation is removed, the cortical network can still maintain the resonance, entrainment, and nonlinear oscillatory activities. The frequency–dependent network response mechanism provides a profound understanding of neural information communication theory induced by the periodic stimulus.

Neural Estimator of Information for Time-Series Data with Dependency.

Novel approaches to estimate information measures using neural networks are well-celebrated in recent years both in the information theory and machine learning communities. These neural-based estimators are shown to converge to the true values when estimating mutual information and conditional mutual information using independent samples. However, if the samples in the dataset are not independent, the consistency of these estimators requires further investigation. This is of particular interest for a more complex measure such as the directed information, which is pivotal in characterizing causality and is meaningful over time-dependent variables. The extension of the convergence proof for such cases is not trivial and demands further assumptions on the data. In this paper, we show that our neural estimator for conditional mutual information is consistent when the dataset is generated with samples of a stationary and ergodic source. In other words, we show that our information estimator using neural networks converges asymptotically to the true value with probability one. Besides universal functional approximation of neural networks, a core lemma to show the convergence is Birkhoff’s ergodic theorem. Additionally, we use the technique to estimate directed information and demonstrate the effectiveness of our approach in simulations.

Single-Server Private Information Retrieval Schemes are Equivalent to Locally Recoverable Coding Schemes

The Private Information Retrieval (PIR) problem has recently attracted a significant interest in the information-theory community. In this problem, a client wants to download one or more messages belonging to a database while protecting the identity of the downloaded message(s). In this article, we focus on the scenarios in which (i) the entire database is stored on a single server and (ii) the client has prior side information, namely a subset of messages unknown to the server. Such prior side information is necessary to enable efficient private information retrieval in the single server scenario. In the last decade, there has also been a significant interest in Locally Recoverable Codes (LRCs), a class of storage codes in which each symbol can be recovered from a limited number of other symbols. More recently, there is an interest in cooperative locally recoverable codes, i.e., codes in which multiple symbols can be recovered from a small set of other code symbols. The central problem in this context is given a set of code parameters to design an LRC scheme that includes a locally recoverable code along with encoding, decoding, and repair functions. The paper establishes an equivalence between the single-server PIR schemes and LRC schemes. In particular, we present explicit algorithms that transform a given PIR scheme into an LRC scheme and vice versa. We show that (i) PIR schemes for retrieving a single message are equivalent to classical LRC schemes; and (ii) PIR schemes for retrieving multiple messages are equivalent to cooperative LRC schemes. These equivalence results allow us to recover upper bounds on the download rate for PIR schemes, and to obtain a novel rate upper bound on cooperative LRC schemes. Our results cover schemes based on both linear and non-linear codes.

Construction of Marine Culture Communication and Inheritance System Based on Digital Images

Chen, Y., 2020. Construction of marine culture communication and inheritance system based on digital images. In: Liu, X. and Zhao, L. (eds.), Today's Modern Coastal Society: Technical and Sociological Aspects of Coastal Research. Journal of Coastal Research, Special Issue No. 111, pp. 258–262. Coconut Creek (Florida), ISSN 0749-0208.In order to solve the problems of the slow development of marine culture and waning inheritance, this article used digital imaging to build a marine culture communication and inheritance system that effectively improves the situation, which is characterized by narrow audience scope in traditional communication modes and ineffective cultural protection. On the basis of digital image technology, this paper discusses the composition of marine culture by using information communication theory and coding/decoding theory and describes the influence of digital media on marine culture by using communication and inheritance theory. The establishment of a database and interdisciplinary integration enhances public cultural awareness, to ensure that China's marine culture can be effectively protected and inherited.

Multivariate Extension of Matrix-Based Rényi's α-Order Entropy Functional.

The matrix-based Rényi's α-order entropy functional was recently introduced using the normalized eigenspectrum of a Hermitian matrix of the projected data in a reproducing kernel Hilbert space (RKHS). However, the current theory in the matrix-based Rényi's α-order entropy functional only defines the entropy of a single variable or mutual information between two random variables. In information theory and machine learning communities, one is also frequently interested in multivariate information quantities, such as the multivariate joint entropy and different interactive quantities among multiple variables. In this paper, we first define the matrix-based Rényi's α-order joint entropy among multiple variables. We then show how this definition can ease the estimation of various information quantities that measure the interactions among multiple variables, such as interactive information and total correlation. We finally present an application to feature selection to show how our definition provides a simple yet powerful way to estimate a widely-acknowledged intractable quantity from data. A real example on hyperspectral image (HSI) band selection is also provided.

Safety information cognition: A new methodology of safety science in urgent need to be established

In order to explain safety and environment protection from the aspects of information cognition, it is imperative to establish new safety theory by exploring accident and environmental pollution mechanism from the upstream level. In recent years, safety-related information or cognition studies have become new extension point in safety science. The researchers did not make any breakthroughs in the mechanism analysis of safety information science, because the essential process is not understood by researchers. Obviously, establishing safety information science is irreversible and critical. Therefore, it is theoretically and practically significant to establish and discuss the foundation of safety information science. Firstly, the safety systems should follow three levels: scale decomposition, dimension decomposition and research field. Then, from the perspective of spatial order, a systematic cognitive sequence of safety information and a Five Areas Four Belts spatial order model were established. Thirdly, the meaning and basic connotation of safety information are clarified. In addition, from the view of the combination between safety information dissemination and behavior cognition, the Safety Information Cognition model is constructed according to the general model of safety information cognition and Principle of system decomposition. Besides, the accident mechanism of 5-layers distortion and 4-times delay, as well as the general procedures of injury accidents were proposed. Finally, the worth of safety science model research for the future development was summarized. This paper contains a series of achievements, including system decomposition method, safety information cognition process and the cause mechanism and prevention strategies of accidents or pollution information. The conclusion shows that the information communication theory, the cognitive model and the safety information law can deepen the understanding of the safety and environment system and provide new ways for the further study of the safety and cleaner production. It can also further consolidate the essential principles of safety and environmental system and supply new preventions of accident and pollution, for example, the controls and elimination of harmful factors, Identification and analyze safety information science of dangerous and harmful factors, risk evaluation, prevention, monitoring and early warning measures et al.

Community detection with opinion leaders’ identification for promoting collaborative problem‐based learning performance

AbstractIn the 21st century when knowledge‐based economy is emphasized, the cultivation of autonomous learning and problem‐solving abilities presents the importance. With web‐based collaborative problem‐based learning (CPBL), learners could more conveniently cultivate their problem‐solving abilities through autonomous learning. Nevertheless, learners are often guided to solve a target problem by the information announced by teachers during the CPBL processes. Individual learners often could not effectively absorb such standard information, thus ignoring the important information from teachers. In the information communication theory, the two‐step flow of communication through opinion leaders has been proved that it can better change audiences’ attitudes than the one‐step flow of communication through mass media. This study thus employs the modularity Q function as the fitness function of genetic algorithm to optimally detect learning communities and uses PageRank measure to accurately find out community opinion leaders according to the social network interaction data of learners in the CPBL process. Based on quasi‐experimental design, this study examines whether learners in the experimental group using the two‐step flow of communication through opinion leaders to convey information for solving the target CPBL missions could more significantly enhance web‐based CPBL performance, social network interaction and group cohesion than learners in the control group using the one‐step flow of communication through teachers’ information. Analytical results show learners in the experimental group remarkably outperform those in the control group on learning performance and peer interaction under a CPBL environment. Particularly, female learners in the experimental group notably outperform female learners in the control group on learning performance, while there is no significant difference in male learners between both groups. More importantly, learners in the experimental group present significantly higher group cohesion than those in the control group. This study confirms that using the two‐step flow of communication instead of the one‐step flow of communication traditionally used in web‐based learning environments could significantly promote web‐based CPBL performance, social network interaction and group cohesion.

A View of Information-Estimation Relations in Gaussian Networks

Relations between estimation and information measures have received considerable attention from the information theory community. One of the most notable such relationships is the I-MMSE identity of Guo, Shamai and Verdú that connects the mutual information and the minimum mean square error (MMSE). This paper reviews several applications of the I-MMSE relationship to information theoretic problems arising in connection with multi-user channel coding. The goal of this paper is to review the different techniques used on such problems, as well as to emphasize the added-value obtained from the information-estimation point of view.

Equalizing the information amounts of protein and mRNA by information theory

Based on the Shannon’s information communication theory, information amount of the entire length of a polymeric macromolecule can be calculated in bits through adding the entropies of each building block. Proteins, DNA and RNA are such macromolecules. When only the building blocks’ variation is considered as the source of entropy, there is seemingly lower information in case of the protein if this approach is applied directly on a protein of specific size and the coding sequence size of the mRNA corresponding to the particular length of the protein. This decrease in the information amount seems contradictory but this apparent conflict is resolved by considering the conformational variations in proteins as a new variable in the calculation and balancing the approximated entropy of the coding part of the mRNA and the protein. Probabilities can change therefore we also assigned hypothetical probabilities to the conformational states, which represent the uneven distribution as the time spent in one conformation, providing the probability of the presence in either or one of the possible conformations. Results that are obtained by using hypothetical probabilities are in line with the experimental values of variations in the conformational-state of protein populations. This equalization approach has further biological relevance that it compensates for the degeneracy in the codon usage during protein translation and it leads to the conclusion that the alphabet size for the protein is rather optimal for the proper protein functioning within the thermodynamic milieu of the cell. The findings were also discussed in relation to the codon bias and have implications in relation to the codon evolution concept. Eventually, this work brings the fields of protein structural studies and molecular protein translation processes together with a novel approach.

New didactics as information communication theory of the learning process

The article presents an innovative approach to learning theory as the information communication process. The component structure of training communication and its model has been disclosed. The innovative interpretation of teaching method of learning as a form of content of motion has been given. The characteristics of such terms as method and way of learning, technique, methodology and technology training have been represented in the new information aspect.

Recent development of error control codes for future communication and storage systems

The outstanding performance of error control codes has attracted the interest of the information and communications theory community and industry partners for more than 20 years since Turbo codes were invented. In recent years, there are more and more scenarios in modern communication and digital storage systems, such as wireless communications, optical communications, flash memories, computer hard drives, sensor networks, and deep-space probing, each having drastically different performance requirements. Hence, more effi cient coding methods are highly desirable to be applied to multi-scenarios with low complexity, low latency and reliable transmission rate close to the Shannon capacity.

Research on Construction and Subdivision of WeChat Multi-stage Information Communication Mode

WeChat is a social tool with the highest acceptance in China, and its huge user social network and information communication mode become research hotspots in recent years. In the paper, different information communication abilities of many social functions of WeChat are integrated on the basis of referring to related information communication theory, WeChat multi-stage information communication mode is constructed, and its communication mode is systematically described and analyzed. In the paper, subjective selectivity communication of users and user own attributes on information is mainly emphasized in order to describe its information communication complexity and diversified selectivity more clearly, thereby further proving the availability and applicability of the WeChat multi-stage information communication mode. It is expected that it can play a larger role in research development of online social network information communication mode in the future.