Asymptotic Optimality of Antidictionary Codes

An antidictionary code is a lossless compression algorithm using an antidictionary which is a set of minimal words that do not occur as substrings in an input string. The code was proposed by Crochemore et al. in 2000, and its asymptotic optimality has been proved with respect to only a specific information source, called balanced binary source that is a binary Markov source in which a state transition occurs with probability 1/2 or 1. In this paper, we prove the optimality of both static and dynamic antidictionary codes with respect to a stationary ergodic Markov source on finite alphabet such that a state transition occurs with probability $p (0 < p \leq 1)$.Comment: 5 pages, to appear in the proceedings of 2010 IEEE International Symposium on Information Theory (ISIT2010

Two-Dimensional Source Coding by Means of Subblock Enumeration

A technique of lossless compression via substring enumeration (CSE) attains compression ratios as well as popular lossless compressors for one-dimensional (1D) sources. The CSE utilizes a probabilistic model built from the circular string of an input source for encoding the source.The CSE is applicable to two-dimensional (2D) sources such as images by dealing with a line of pixels of 2D source as a symbol of an extended alphabet. At the initial step of the CSE encoding process, we need to output the number of occurrences of all symbols of the extended alphabet, so that the time complexity increase exponentially when the size of source becomes large. To reduce the time complexity, we propose a new CSE which can encode a 2D source in block-by-block instead of line-by-line. The proposed CSE utilizes the flat torus of an input 2D source as a probabilistic model for encoding the source instead of the circular string of the source. Moreover, we analyze the limit of the average codeword length of the proposed CSE for general sources.Comment: 5 pages, Submitted to ISIT201

A Universal Two-Dimensional Source Coding by Means of Subblock Enumeration

The technique of lossless compression via substring enumeration (CSE) is a kind of enumerative code and uses a probabilistic model built from the circular string of an input source for encoding a one-dimensional (1D) source. CSE is applicable to two-dimensional (2D) sources, such as images, by dealing with a line of pixels of a 2D source as a symbol of an extended alphabet. At the initial step of CSE encoding process, we need to output the number of occurrences of all symbols of the extended alphabet, so that the time complexity increases exponentially when the size of source becomes large. To reduce computational time, we can rearrange pixels of a 2D source into a 1D source string along a space-filling curve like a Hilbert curve. However, information on adjacent cells in a 2D source may be lost in the conversion. To reduce the time complexity and compress a 2D source without converting to a 1D source, we propose a new CSE which can encode a 2D source in a block-by-block fashion instead of in a line-by-line fashion. The proposed algorithm uses the flat torus of an input 2D source as a probabilistic model instead of the circular string of the source. Moreover, we prove the asymptotic optimality of the proposed algorithm for 2D general sources

Influence of cultural contexts on the appreciation of different cultural ecosystem services based on social network analysis

Since the Millennium Ecosystem Assessment, ecosystem science domain has made tremendous progress in the study of ecosystem services, but debates on neglected cultural ecosystem services (CES) have persisted. A recent approach established by the Intergovernmental Panel for Biodiversity and Ecosystem Services (IPBES) identifies and advocates incorporation of the CES through the role of local knowledge across other ecosystem services. However, approaches and tools that enable engagement of CES are limited. In this study, we examine how cultural contexts influence the appreciation of different CES, by identifying the behavioural aspects and the indigenous knowledge that has evolved on the basis of Social Network Analysis (SNA). SNA measures the network of relations between people and groups developed traditionally for a long time and their relational values with natural resources and ecosystem services. Through a comprehensive literature review of scholarly research published in Scopus data base, this study explicitly illustrates the interrelationship between SNA and CES. Keywords associated with SNA and cultural ecosystem services including forests, fisheries and agriculture (farming) were used. It was found that various aspects of social network uphold relational values of cultural importance and enhance resilience in groups amidst the social changes and times as societies progress. For instance, in the case of homophily, actors who are attracted to one another chose to interact in their defined network (e.g. fishing network) forming a strong social capital. Consequently, they shared similar beliefs and values that were eventually handed to the next generation of the network which shaped their heritage and identity. Social learning networks in various communities were also found to play a key role in information exchange and knowledge sharing among members compared to information from foreign technical experts. To fully integrate CES into sustainable decision making, this review suggests incorporation of the analysis of social networks formed in different cultural contexts globally

A snail-eating snake recognizes prey handedness

Specialized predator-prey interactions can be a driving force for their coevolution. Southeast Asian snail-eating snakes (Pareas) have more teeth on the right mandible and specialize in predation on the clockwise-coiled (dextral) majority in shelled snails by soft-body extraction. Snails have countered the snakes’ dextral-predation by recurrent coil reversal, which generates diverse counterclockwise-coiled (sinistral) prey where Pareas snakes live. However, whether the snake predator in turn evolves any response to prey reversal is unknown. We show that Pareas carinatus living with abundant sinistrals avoids approaching or striking at a sinistral that is more difficult and costly to handle than a dextral. Whenever it strikes, however, the snake succeeds in predation by handling dextral and sinistral prey in reverse. In contrast, P. iwasakii with little access to sinistrals on small peripheral islands attempts and frequently misses capturing a given sinistral. Prey-handedness recognition should be advantageous for right-handed snail-eating snakes where frequently encountering sinistrals. Under dextral-predation by Pareas snakes, adaptive fixation of a prey population for a reversal gene instantaneously generates a sinistral species because interchiral mating is rarely possible. The novel warning, instead of sheltering, effect of sinistrality benefitting both predators and prey could further accelerate single-gene ecological speciation by left-right reversal.ArticleScientific Reports.6:23832(2016)journal articl

Compression by Substring Enumeration Using Sorted Contingency Tables

This paper proposes two variants of improved Compression by Substring Enumeration (CSE) with a finite alphabet. In previous studies on CSE, an encoder utilizes inequalities which evaluate the number of occurrences of a substring or a minimal forbidden word (MFW) to be encoded. The inequalities are derived from a contingency table including the number of occurrences of a substring or an MFW. Moreover, codeword length of a substring and an MFW grows with the difference between the upper and lower bounds deduced from the inequalities, however the lower bound is not tight. Therefore, we derive a new tight lower bound based on the contingency table and consequently propose a new CSE algorithm using the new inequality. We also propose a new encoding order of substrings and MFWs based on a sorted contingency table such that both its row and column marginal total are sorted in descending order instead of a lexicographical order used in previous studies. We then propose a new CSE algorithm which is the first proposed CSE algorithm using the new encoding order. Experimental results show that compression ratios of all files of the Calgary corpus in the proposed algorithms are better than those of a previous study on CSE with a finite alphabet. Moreover, compression ratios under the second proposed CSE get better than or equal to that under a well-known compressor for 11 files amongst 14 files in the corpus

Explicitly Multi-Modal Benchmarks for Multi-Objective Optimization

In multi-objective optimization, designing good benchmark problems is an important issue for improving solvers. Although many benchmark problems have been proposed and some of them became de facto standards, designing multimodal problems that have a controllable landscape is still an open problem especially for high-dimensional cases. We thus propose the Benchmark with Explicit Multimodality (BEM), which lets the benchmark designer specify the basins of attraction using a graph structure known as the reachability graph. In this article, we focus on the mathematical formulation of the BEM. We will see that the BEM has preferable characteristics such as (i) realizing user-specified local Pareto set, (ii) allowing high-dimensional design spaces and (iii) possessing nonseparability