A Practical Regular LDPC Coded Scheme for Physical-Layer Information Security

In this paper,we aim to design a practical low complexity low-density parity-check(LDPC)coded scheme to build a secure open channel and protect information from eavesdropping.To this end,we first propose a punctured LDPC coded scheme,where the information bits in a codeword are punctured and only the parity check bits are transmitted to the receiver.We further propose a notion of check node type distribution and derive multi-edge type extrinsic information transfer functions to estimate the security performance,instead of the well-known weak metric bit error rate.We optimize the check node type distribution in terms of the signal-to-noise ratio(SNR)gap and modify the progressive edge growth algorithm to design finite-length codes.Numerical results show that our proposed scheme can achieve a lower computational complexity and a smaller security gap,compared to the existing scrambling and puncturing schemes.

The Advertisement Translation Based on the Prototype Theory

Based on the Prototype Theory,the prototypical feature of advertisement is found to be the combination of three language functions:the informative function,the expressive function,and the vocative function.The advertisement translation means the adjustment of the informative function and the expressive function according to the differences between languages or cultures in order to maximize the vocative function.The faithful translation is the closest to the prototype of the source text but not necessarily the best translation.

A new measure for evaluating spatially related properties of traffic information credibility

With the wide applications of sensor network technology in traffic information acquisition systems,a new measure will be quite necessary to evaluate spatially related properties of traffic information credibility.The heterogeneity of spatial distribution of information credibility from sensor networks is analyzed and a new measure,information credibility function(ICF),is proposed to describe this heterogeneity.Three possible functional forms of sensor ICF and their corresponding expressions are presented.Then,two feasible operations of spatial superposition of sensor ICFs are discussed.Finally,a numerical example is introduced to show the calibration method of sensor ICF and obtain the spatially related properties of expressway in Beijing.The results show that the sensor ICF of expressway in Beijing possesses a negative exponent property.The traffic information is more abundant at or near the locations of sensor,while with the distance away from the sensor increasing,the traffic information credibility will be declined by an exponential trend.The new measure provides theoretical bases for the optimal locations of traffic sensor networks and the mechanism research of spatial distribution of traffic information credibility.

Study on information utility

Information has two aspects. One aspect is the objective one; another aspect is the subjective one. Shannon has discussed the objective aspect of information in information theory. But the subjective aspect of information has not been fully discussed. Someone use “Bayesian approaches” to evaluate the value of information. But in some cases it does not meet the information user＇s need. This paper is focus on the subjective aspect of objectively measurable information and gives formal definitions for information, information utility, and marginal information utility, normalized calculation of information utility. The information discussed in the paper has interdisciplinary nature. This work can be the foundation of many application areas.

Least squares weighted twin support vector machines with local information

A least squares version of the recently proposed weighted twin support vector machine with local information(WLTSVM) for binary classification is formulated. This formulation leads to an extremely simple and fast algorithm, called least squares weighted twin support vector machine with local information(LSWLTSVM), for generating binary classifiers based on two non-parallel hyperplanes. Two modified primal problems of WLTSVM are attempted to solve, instead of two dual problems usually solved. The solution of the two modified problems reduces to solving just two systems of linear equations as opposed to solving two quadratic programming problems along with two systems of linear equations in WLTSVM. Moreover, two extra modifications were proposed in LSWLTSVM to improve the generalization capability. One is that a hot kernel function, not the simple-minded definition in WLTSVM, is used to define the weight matrix of adjacency graph, which ensures that the underlying similarity information between any pair of data points in the same class can be fully reflected. The other is that the weight for each point in the contrary class is considered in constructing equality constraints, which makes LSWLTSVM less sensitive to noise points than WLTSVM. Experimental results indicate that LSWLTSVM has comparable classification accuracy to that of WLTSVM but with remarkably less computational time.

On information field of clinical diagnosis

“Field” is a universal phenomenon existing in both nature and society, and determines the existence and significance of all materials or information. The man being has always been generating and carrying a large quantity of life information in his whole life. Each piece of life information has an independent information field. The life information field includes such three subfields as bioinformation field, psychoinformation field and psycho-bioinformation field. The clinical diagnosis information field which is a specific information field within the information field of human activities consists of all information concerning man’s health. Only after we have cognized and ascertained the clinic diagnosis information field, can we accurately utilize its function to serve the human being.

The Social Functions of Gossip on Reality TV Show Big Brother

Gossip is a common phenomenon in human society though most people disdain it.Generally,gossip consists of four major social functions,namely information function,entertainment function,friendship function and influence function.This paper analyzes the gossip extracts from reality TV show Big Brother by using a detailed analytic approach to show how gossip functions.

Information-Body Relation and Information as a Solution of the Consciousness Problem in the Biological Structures

This paper approaches two main philosophical questions concerning the biological structures,from unicellular to multicellular organisms:one of them(i),referred to the information-body relation,as an extension of the mind-body relation at human,and another one(ii),to the consciousness problem,concerning the existence and nature of consciousness(if any),at the inferior organisms on the complexity scale,as this concept is known at humans.As philosophy benefits of the privilege to use data/concepts from other sciences to obtain philosophical conclusions,there were included detailed descriptions of some key biologic mechanisms,analyzed from informational perspective,necessary just to support/demonstrate/reinforce the informational nature/substrate of the mentioned relations.The analysis of the close relation between information and body,related to the structuration and functional properties of the biological organisms,from cells to multicellular structures,shows that all of them are able to“embody/disembody”information during/by structuration/destructuration processes of matter,in particular that of DNA/RNA/proteins,their functions appearing as a result of their informational capabilities to internally manage the inter-connection with environment,primarily due to their permanent dependence on the food resources and adaptation/survival needs.The experimental and theoretical studies,revealing/documenting on one hand the automatic management of maintenance metabolic processes,the reproduction,and growth/development,and on the other hand the adaptive decision-making/sentient processes as a responsive reaction to the environmental cues,show/support the consistency of the informational model of the human body and living structures on the entire biological scale,providing support to the informational solution of the stated problems(i)and(ii).A distinct attention is paid to plants,which are organisms without nervous system,but which show/manifest also informational capabilities to detect/react to information and to modulate their behavior accordingly.The question if the living organisms possess a pseudo/proto-consciousness level as a consequence of the informational activity of their body,distinct from human,but active in any biological structure under certain conditions is furthermore discussed,and a reliable definition of rudimentary pseudo/proto-consciousness level is given/described and compared with other empirical/theoretical concepts.

What Information Gap Activities can Teach Us in TESOL

Starting from presenting and analyzing some information gap activities during the previous teaching experience, this article has inferred the major roles of information gap activities. Some strategies to implement the information gap activities are also recommended together with the functions of the instructors via these activities. What information gap activities can teach us in TESOL （teaching English for speakers of other languages） is that information gap activities contribute to setting up a climate of a mutual autonomous learning style both for the learners and the instructors, and these activities activate a diversity in the learning atmosphere.

Customized anterior segment photoacoustic imaging for ophthalmic burn evaluation in vivo

Photoacoustic imaging has many advantages in ophthalmic application including high-resolution,requirement of no exogenous contrast agent,and noninvasive acquisition of both morphologic and functional information.However,due to the limited depth of focus of the imaging method and large curvature of the eye,it remains a challenge to obtain high quality vascular image of entire anterior segment.Here,we proposed a new method to achieve high quality imaging of anterior segment.The new method applied a curvature imaging strategy based on only one time scanning,and hence is time efficient and more suitable for ophthalmic imaging compared to previously reported methods using similar strategy.A custom-built photoacoustic imaging system was adapted for ophthalmic application and a customized image processing method was developed to quantitatively analyze both morphologic and functional information in vasculature of the anterior segment.The results showed that the new method improved the image quality of anterior segment significantly compared to that of conventional high resolution photoacoustic imaging.More importantly,we applied the new method to study ophthalmic disease in an in vivo mouse model for the first time.The results verified the suitability and advantages of the new method for imaging the entire anterior segment and the numerous potentials of applying it in ophthalmic imaging in future.

Clustering in the presence of side information: a non-linear approach

Purpose–Constrained clustering is an important recent development in clustering literature.The goal of an algorithm in constrained clustering research is to improve the quality of clustering by making use of background knowledge.The purpose of this paper is to suggest a new perspective for constrained clustering,by finding an effective transformation of data into target space on the reference of background knowledge given in the form of pairwise must-and cannot-link constraints.Design/methodology/approach–Most of existing methods in constrained clustering are limited to learn a distance metric or kernel matrix from the background knowledge while looking for transformation of data in target space.Unlike previous efforts,the author presents a non-linear method for constraint clustering,whose basic idea is to use different non-linear functions for each dimension in target space.Findings–The outcome of the paper is a novel non-linear method for constrained clustering which uses different non-linearfunctions for each dimension in target space.The proposed method for a particular case is formulated and explained for quadratic functions.To reduce the number of optimization parameters,the proposed method is modified to relax the quadratic function and approximate it by a factorized version that is easier to solve.Experimental results on synthetic and real-world data demonstrate the efficacy of the proposed method.Originality/value–This study proposes a new direction to the problem of constrained clustering by learning a non-linear transformation of data into target space without using kernel functions.This work will assist researchers to start development of new methods based on the proposed framework which will potentially provide them with new research topics.

Analytic design of information granulation-based fuzzy radial basis function neural networks with the aid of multiobjective particle swarm optimization

Purpose–The purpose of this paper is to consider the concept of Fuzzy Radial Basis Function Neural Networks with Information Granulation(IG-FRBFNN)and their optimization realized by means of the Multiobjective Particle Swarm Optimization(MOPSO).Design/methodology/approach–In fuzzy modeling,complexity,interpretability(or simplicity)as well as accuracy of the obtained model are essential design criteria.Since the performance of the IG-RBFNN model is directly affected by some parameters,such as the fuzzification coefficient used in the FCM,the number of rules and the orders of the polynomials in the consequent parts of the rules,the authors carry out both structural as well as parametric optimization of the network.A multi-objective Particle Swarm Optimization using Crowding Distance(MOPSO-CD)as well as O/WLS learning-based optimization are exploited to carry out the structural and parametric optimization of the model,respectively,while the optimization is of multiobjective character as it is aimed at the simultaneous minimization of complexity and maximization of accuracy.Findings–The performance of the proposed model is illustrated with the aid of three examples.The proposed optimization method leads to an accurate and highly interpretable fuzzy model.Originality/value–A MOPSO-CD as well as O/WLS learning-based optimization are exploited,respectively,to carry out the structural and parametric optimization of the model.As a result,the proposed methodology is interesting for designing an accurate and highly interpretable fuzzy model.