ON INFORMATION THEORY METHOD FOR RELIABILITY ASSESSMENT OF SYSTEMS CONSISTING OF DIFFERENT SUCCESS FAILURE MODEL UNITS

Using the characteristic of addition of information quantity and the principle of equivalence of information quantity, this paper derives the general conversion formulae of the formation theory method conversion (synthesis) on the systems consisting of different success failure model units. According to the fundamental method of the unit reliability assessment, the general models of system reliability approximate lower limits are given. Finally, this paper analyses the application of the assessment method by examples, the assessment results are neither conservative nor radical and very satisfactory. The assessment method can be popularized to the systems which have fixed reliability structural models.

Agriculture Information Retrieval System Based on Comprehensive Information Theory

Through analyzing syntactic,semantic,pragmatic information,the retrieval system ACIS based on comprehensive information was established,which could achieve personalized information exaction to guide user s information retrieval.

Foundations and Applications of Information Systems Dynamics

Although numerous advances have been made in information technology in the past decades,there is still a lack of progress in information systems dynamics(ISD),owing to the lack of a mathematical foundation needed to describe information and the lack of an analytical framework to evaluate information systems.The value of ISD lies in its ability to guide the design,development,application,and evaluation of largescale information system-of-systems(So Ss),just as mechanical dynamics theories guide mechanical systems engineering.This paper reports on a breakthrough in these fundamental challenges by proposing a framework for information space,improving a mathematical theory for information measurement,and proposing a dynamic configuration model for information systems.In this way,it establishes a basic theoretical framework for ISD.The proposed theoretical methodologies have been successfully applied and verified in the Smart Court So Ss Engineering Project of China and have achieved significant improvements in the quality and efficiency of Chinese court informatization.The proposed ISD provides an innovative paradigm for the analysis,design,development,and evaluation of large-scale complex information systems,such as electronic government and smart cities.

Data Component:An Innovative Framework for Information Value Metrics in the Digital Economy

The increasing dependence on data highlights the need for a detailed understanding of its behavior,encompassing the challenges involved in processing and evaluating it.However,current research lacks a comprehensive structure for measuring the worth of data elements,hindering effective navigation of the changing digital environment.This paper aims to fill this research gap by introducing the innovative concept of“data components.”It proposes a graphtheoretic representation model that presents a clear mathematical definition and demonstrates the superiority of data components over traditional processing methods.Additionally,the paper introduces an information measurement model that provides a way to calculate the information entropy of data components and establish their increased informational value.The paper also assesses the value of information,suggesting a pricing mechanism based on its significance.In conclusion,this paper establishes a robust framework for understanding and quantifying the value of implicit information in data,laying the groundwork for future research and practical applications.

An Information Theory Approach to the Data Compression and Imaging System for Synthetic Aperture Radar （SAR）

Synthetic aperture radar (SAR) is portrayed as a multiple access channel. An information theory approach is applied to the SAR imaging system, and the information content about a target that can be extracted from its radar image is evaluated by the average mutual information measure. A conditional (transition) probability density function (PDF) of the SAR imaging system is derived by analyzing the system and a closed form of the information content is found. It is shown that the information content obtained by the SAR imaging system from an independent sample of echoes will decrease and the total information content obtained by the SAR imaging system will increase with an increase in the number of looks. Because the total average mutual information is also used to define a measure of radiometric resolution for radar images, it is shown that the radiometric resolution of a radar image of terrain will be improved by spatial averaging. In addition, the imaging process and the data compression process for SAR are each treated as an independent generalized communication channel. The effects of data compression upon radiometric resolution for SAR are studied and some conclusions are obtained.

Information Theory of Cartography:An Information-theoretic Framework for Cartographic Communication

Map is one of the communication means created by human being.Cartographers have been making efforts on the comparison of maps to natural languages so as to establish a"cartographic language"or"map language".One of such efforts is to adopt the Shannon’s Information Theory originated in digital communication into cartography so as to establish an entropy-based cartographic communication theory.However,success has been very limited although research work had started as early as the mid-1960 s.It is then found that the bottleneck problem was the lack of appropriate measures for the spatial(configurational)information of(graphic and image)maps,as the classic Shannon entropy is only capable of characterizing statistical information but fails to capture the configurational information of(graphic and image)maps.Fortunately,after over 40-year development,some bottleneck problems have been solved.More precisely,generalized Shannon entropies for metric and thematic information of(graphic)maps have been developed and the first feasible solution for computing the Boltzmann entropy of image maps has been invented,which is capable of measuring the spatial information of not only numerical images but also categorical maps.With such progress,it is now feasible to build the"Information Theory of Cartography".In this paper,a framework for such a theory is proposed and some key issues are identified.For these issues,some have already been tackled while others still need efforts.As a result,a research agenda is set for future action.After all these issues are tackled,the theory will become matured so as to become a theoretic basis of cartography.It is expected that the Information Theory of Cartography will play an increasingly important role in the discipline of cartography because more and more researchers have advocated that information is more fundamental than matter and energy.

Fault diagnosis method of hydraulic system based on fusion of neural network and D-S evidence theory

According to fault type diversity and fault information uncertainty problem of the hydraulic driven rocket launcher servo system（HDRLSS） , the fault diagnosis method based on the evidence theory and neural network ensemble is proposed. In order to overcome the shortcomings of the single neural network, two improved neural network models are set up at the com-mon nodes to simplify the network structure. The initial fault diagnosis is based on the iron spectrum data and the pressure, flow and temperature（PFT） characteristic parameters as the input vectors of the two improved neural network models, and the diagnosis result is taken as the basic probability distribution of the evidence theory. Then the objectivity of assignment is real-ized. The initial diagnosis results of two improved neural networks are fused by D-S evidence theory. The experimental results show that this method can avoid the misdiagnosis of neural network recognition and improve the accuracy of the fault diagnosis of HDRLSS.

An Exploration on the Theory of Information Economy

Since the 1970s, the application of information processing and information technology has gradually played a dominant role in Western economy, especially in American economy. Since the mid1980s, investment of the United States, Europe and Japan in information technology has increased drastically, making information

Rural Planning Based on Landscape Information Chain Theory: A Case Study of Jiabi Village in Maoba County, Lichuan City

As the most important part of the construction of beautiful countryside, village planning plays a crucial role in the construction of beautiful countryside. How to construct a beautiful village with prominent regional characteristics in line with rural natural resources and traditional culture turns out be a problem demanding prompt solution in current theoretical research and practical exploration. With the introduction of the landscape information chain theory, Jiabi Village in Maoba Town, Lichuan City was taken for example to create a complete landscape information chain where tea culture dominates and different cultures intermingle by excavating local landscape information elements, creating landscape information places, and constructing landscape information corridor, so as to create a distinctive beautiful vil age in western Hubei and accord with its positioning of "China's tea homestay culture village" and "China's couplet tea village".

Information Theory Model for Radiation

Information based models for radiation emitted by a Black Body which passes through a scattering medium are analyzed. In the limit, when there is no scattering this model reverts to the Black Body Radiation Law. The advantage of this mathematical model is that it includes the effect of the scattering of the radiation between source and detector. In the case when the exact form of the scattering mechanism is not known a model using a single scattering parameter is derived. A simple version of this model is derived which is useful for analyzing large data.

An Information Theory for the Geotechnical Engineering Inverse Problem

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Portfolio Diversification Using Information Theory Applied to Brazilian Stocks

Using the concepts from information theory, it is possible to improve the traditional methodologies of asset allocation. In this paper, it was studied and extended the two existent approaches： the first is based on the Shannon entropy concept and the second on the Kullback-Leibler distance. In modem portfolio theory, the investor has two basic procedures： the choice of a portfolio that maximizes its risk-adjusted excess return or the mixed allocation between the maximum Sharpe portfolio and the risk-free asset. The first procedure was already addressed in the related literature. One important contribution of this paper is the consideration of the second procedure in the information theory context. The performance of these approaches was compared with the three traditional asset allocation methodologies： the Markowitz＇s mean-variance, the resampled mean-variance and the equally weighted portfolio. It was used simulated and real data from Brazilian stocks. The information theory-based methodologies were verified to be more robust when dealing with the estimation errors.

Construction and Practice of Online Course Resources Based on Information Processing Theory:Taking“A Bite of Teochew Cuisine,”a Guangdong First-Class Course,as an Example

“Cantonese Cuisine Master”project is an important policy proposed by China to inherit Cantonese Cuisine culture,promote employment,and achieve targeted poverty reduction and rural revitalization.Confronted with the demands of more diverse education,it is an essential opportunity and task for the education system to consider how to construct high-quality online courses and pursue higher-quality“Cantonese Cuisine Master”projects in line with the new era.This paper,based on the theory of instructional media and information processing theory,will further clarify the demand,dilemma,and developing strategy of online course construction for culinary majors,and explore its construction and practice with the example of“A Bite of Teochew Cuisine,”a Guangdong first-class course.

Application of Information Processing Theory in Second Language Vocabulary Acquisition

Vocabulary acquisition is an intricate process,which has a close relationship with memory.In cognitive psychology,a large number of studies on memory system have been conducted based on the information processing theory,placing great value on second language learners’cognitive process.This study intends to probe into second language vocabulary acquisition from the perspective of information processing theory in hope to help learners acquire vocabulary more scientifically and efficiently.

From Black Holes to Information Erasure: Uniting Bekenstein’s Bound and Landauer’s Principle

This research aims to integrate Bekenstein’s bound and Landauer’s principle, providing a unified framework to understand the limits of information and energy in physical systems. By combining these principles, we explore the implications for black hole thermodynamics, astrophysics, astronomy, information theory, and the search for new laws of nature. The result includes an estimation of the number of bits stored in a black hole (less than 1.4 × 1030 bits/m3), enhancing our understanding of information storage in extreme gravitational environments. This integration offers valuable insights into the fundamental nature of information and energy, impacting scientific advancements in multiple disciplines.

Quantum Theory of Consciousness

Both consciousness and quantum phenomenon are subjective and indeterministic. In this paper, we propose consciousness is a quantum phenomenon. A quantum theory of consciousness (QTOC) is presented based on a new interpretation of quantum physics. We show that this QTOC can address the mind and body problem, the hard problem of consciousness. It also provides a physics foundation and mathematical formulation to study consciousness and neural network. We demonstrate how to apply it to develop and extend various models of consciousness. We show the predictions from this theory about the existence of a universal quantum vibrational field and the large-scale, nearly instantaneous synchrony of brainwaves among different parts of brain, body, people, and objects. The correlation between Schumann Resonances and some brainwaves is explained. Recent progress in quantum information theory, especially regarding quantum entanglement and quantum error correction code, is applied to study memory and shed new light in neuroscience.

Quantum Realities and Observer-Dependent Universes: An Advanced Observer Model

This paper presents a novel observer model that integrates quantum mechanics, relativity, idealism, and the simulation hypothesis to explain the quantum nature of the universe. The model posits a central server transmitting multi-media frames to create observer-dependent realities. Key aspects include deriving frame rates, defining quantum reality, and establishing hierarchical observer structures. The model’s impact on quantum information theory and philosophical interpretations of reality are examined, with detailed discussions on information loss and recursive frame transmission in the appendices.

Evaluating ChatGPT’s Consciousness and Its Capability to Pass the Turing Test: A Comprehensive Analysis

This study explores the capabilities of ChatGPT, specifically in relation to consciousness and its performance in the Turing Test. The article begins by examining the diverse perspectives among both the cognitive and AI researchers regarding ChatGPT’s ability to pass the Turing Test. It introduces a hierarchical categorization of the test versions, suggesting that ChatGPT approaches success in the test, albeit primarily with na?ve users. Expert users, conversely, can easily identify its limitations. The paper presents various theories of consciousness, with a particular focus on the Integrated Information Theory proposed by Tononi. This theory serves as the framework for assessing ChatGPT’s level of consciousness. Through an evaluation based on the five axioms and theorems of IIT, the study finds that ChatGPT surpasses previous AI systems in certain aspects;however, ChatGPT significantly falls short of achieving a level of consciousness, particularly when compared to biological sentient beings. The paper concludes by emphasizing the importance of recognizing ChatGPT and similar generative AI models as highly advanced and intelligent tools, yet distinctly lacking the consciousness attributes found in advanced living organisms.

Novel method of enhancing the key amount for FH systems

Based on the principle of information theory, a novel scheme of unequal-interval frequency-hopping (FH) systems was proposed. For cases of spectrum overlapping systems and non-overlapping systems, the implementation methods were presented and the security performances were discussed theoretically. Firstly, the definitions of absolute and relative key amounts of FH systems, equal-interval and unequal-interval FH systems were given. Then, the absolute key amount and relative key amount were analyzed for equal-interval and unequal-interval FH systems. The results indicated that the absolute key amount had become the key point in improving the security and secrecy of FH systems, especially in today's epoch of highly developed computer science and IC design technology. Theoretical analysis and practical examples showed that the absolute key amount of unequal-interval FH systems was generally over two orders larger than that of equal-interval ones when spectrum overlapping was allowable. Therefore, there was great superiority in enhancing the security and secrecy for the scheme mentioned.

MDL-based root-mean-squared delay spread estimation for MIMO OFDM systems

This paper studied the application of minimum description length (MDL) criterion for estimating root-mean-squared (RMS) delay spread (RDS) for MIMO OFDM systems. The analytic relationship between the powers and the correlation matrix of multipath components established the feasibility of the application of the MDL criterion to RDS estimation. The estimator presented both the estimate of instantaneous RDS and the estimates of noise variance, channel power and SNR of current channel with low computational complexity. Given the powers of the estimated multipath components, the MDL criterion was adopted to acquire the number of paths and the time delays of each path of current channel without making eigendecomposition of the correlation matrix normally required by MDL criterion, following which the noise variance and the power of each path can be estimated. The power delay profile (PDP) and RDS of the current channel were achieved. Simulation results showed that the proposed estimator was insensitive to variance of SNR and robust against frequency-selectivity.