Compression by Substring Enumeration with a Finite Alphabet Using Sorting

An antidictionary is particularly useful for data compression, and on-line electrocardiogram (ECG) lossless compression algorithms using antidictionaries have been proposed. They work in real-time with constant memory and give better compression ratios than traditional lossless data compression algorithms, while they only deal with ECG data on a binary alphabet. This paper proposes on-line ECG lossless compression for a given data on a finite alphabet. The proposed algorithm gives not only better compression ratios than those algorithms but also uses less computational space than they do. Moreover, the proposed algorithm work in real-time. Its effectiveness is demonstrated by simulation results.

After K. Bostro/spl uml/m and T. Felbinger observed that lossless quantum data compression does not exist unless decoders know the lengths of codewords, they introduced a classical noiseless channel to inform the decoder of a quantum source about the lengths of codewords. In this paper we analyze their codes and present: 1) a sufficient and necessary condition for the existence of such codes for given lists of lengths of codes; 2) a characterization of the optimal compression rate for their codes. However our main contribution is a more efficient way to use the classical channel. We propose a more general coding scheme. It turned out that the optimal compression can always be achieved by a code obtained by this scheme. A von Neumann entropy lower bound to rates of our codes and a necessary and sufficient condition to achieve the bound are obtained. The gap between this lower bound and the compression rates is also well analyzed. For a special family of quantum sources we provide a sharper lower bound in terms of Shannon entropy. Finally, we propose some problems for further research.

By the problem, called a representation of the integers, is meant the encoding of the positive integers without a known upper bound, for which unique decoding can be provided. From the viewpoint of information theory, this problem has been discussed theoretically in its relation to the universality, asymptotic optimality, and computation theory. The result in those approaches has been applied to the data compression scheme for the type of data referring to the past as well as the URR and other floating-pointnumber representations with variable exponential length. This paper discusses representation of the integers problem from the viewpoint of the codeword-length function, which is the function to represent the length of the codeword. As a result, a general construction method is presented which has the desirable property and can uniquely encode all representations. Several methods are given from this approach, which can construct not only the traditional representations of the integers but also the first representations of the integers which has not been considered. It is noted first that two construction methods of codeword length, which are independent of the encoding, are considered. One is based on the combination of the codeword-length functions, and the other is based on the codeword-length distribution. More precisely, it is shown that not only are the traditional representations derived, but also the representations that have not been considered in the past. Using detailed examples, it is shown that the computational complexity of the encoding and decoding depends on the codeword-length function.

Consider a periodic sequence over a finite alphabet, say ..ababab.... This sequence can be specified by prohibiting the subwords aa and bb. In the paper, the maximum period of a word that can be defined by using k restrictions is determined. A sharp exponential bound is obtained: the period of a word determined by k restrictions cannot exceed the kth Fibonacci number. Thus, the period colength is estimated. The problem is studied in the context of Grobner bases, namely, the growth of a Grobner basis of an ideal (the cogrowth of an algebra). The proof uses the technique of Rauzy graphs.

In the unsupervised open set domain adaptation (UOSDA), the target domain contains unknown classes that are not observed in the source domain. Researchers in this area aim to train a classifier to accurately: 1) recognize unknown target data (data with unknown classes) and 2) classify other target data. To achieve this aim, a previous study has proven an upper bound of the target-domain risk, and the open set difference, as an important term in the upper bound, is used to measure the risk on unknown target data. By minimizing the upper bound, a shallow classifier can be trained to achieve the aim. However, if the classifier is very flexible [e.g., deep neural networks (DNNs)], the open set difference will converge to a negative value when minimizing the upper bound, which causes an issue where most target data are recognized as unknown data. To address this issue, we propose a new upper bound of target-domain risk for UOSDA, which includes four terms: source-domain risk, ϵ -open set difference ( ∆ϵ ), distributional discrepancy between domains, and a constant. Compared with the open set difference, ∆ϵ is more robust against the issue when it is being minimized, and thus we are able to use very flexible classifiers (i.e., DNNs). Then, we propose a new principle-guided deep UOSDA method that trains DNNs via minimizing the new upper bound. Specifically, source-domain risk and ∆ϵ are minimized by gradient descent, and the distributional discrepancy is minimized via a novel open set conditional adversarial training strategy. Finally, compared with the existing shallow and deep UOSDA methods, our method shows the state-of-the-art performance on several benchmark datasets, including digit recognition [modified National Institute of Standards and Technology database (MNIST), the Street View House Number (SVHN), U.S. Postal Service (USPS)], object recognition (Office-31, Office-Home), and face recognition [pose, illumination, and expression (PIE)].

Given an infinite word with values in a finite alphabet that admit frequencies for all its factors, the smallest frequency function associates with a given positive integer the smallest frequency for factors of this length, and the recurrence function measures the gaps between successive occurrences of factors. We develop in this paper the relations between the growth orders of the smallest frequency and of the recurrence functions. As proved by M. Boshernitzan, linearly recurrent words are characterized in terms of the smallest frequency function. In this paper, we see how to extend this result beyond the case of linearly recurrent words. We first establish a general relation between the smallest frequency and the recurrence functions. Given a lower bound for the smallest frequency function, this relation provides an upper bound for the recurrence function which involves the primitive of this lower bound. We then see how to improve this relation in the case of Sturmian words where the product of the smallest frequency and the recurrence function is bounded for most of the lengths of factors. We also indicate how to construct Sturmian words having a prescribed behaviour for the smallest frequency function, and for the product of the smallest frequency and the recurrence function.

Consider finite sequences $X_{[1,n]}=X_{1},\ldots,X_{n}$ and $Y_{[1,n]}=Y_{1},\ldots,Y_{n}$ of length $n$, consisting of i.i.d. samples of random letters from a finite alphabet, and let $S$ and $T$ be chosen i.i.d. randomly from the unit ball in the space of symmetric scoring functions over this alphabet augmented by a gap symbol. We prove a probabilistic upper bound of linear order in $(\ln(n))^{1/4}n^{3/4}$ for the deviation of the score relative to $T$ of optimal alignments with gaps of $X_{[1,n]}$ and $Y_{[1,n]}$ relative to $S$. It remains an open problem to prove a lower bound. Our result contributes to the understanding of the microstructure of optimal alignments relative to one given scoring function, extending a theory begun in (J. Stat. Phys. 153 (2013) 512–529).

A powerful abelian square-free substitution over 4 letters

Bell–CHSH is an inequality about unconditional expectations: under measurement independence, Bell locality, and bounded outcomes, the CHSH value satisfies S≤2. Experimental correlators, however, are often computed on an accepted subset of trials defined by detection logic, coincidence matching, quality cuts, and analysis windows. We model this by an acceptance probability γ(a,b,λ)∈[0,1] and the resulting accepted hidden-variable law νab obtained by weighting the measurement-independent prior ρ by γ and renormalizing. If νab depends on the setting pair then the four correlators entering CHSH are expectations under four different measures, and a Bell-local measurement-independent model can yield Sobs>2 by selection alone. We quantify the required setting dependence in total variation (TV) distance. For any reference law μ we prove the sharp bound Sobs≤2+2∑q∈QTV(νq,μ) for a CHSH quartet Q. Optimizing over μ yields the intrinsic dispersion bound Sobs≤2+2ΔQ, and, in particular, Sobs≤min{4,2+6DQ}, where DQ is the quartet TV diameter. The constants are optimal. Consequently, reproducing Tsirelson’s value 22 within Bell-local measurement-independent models via setting-dependent acceptance requires ΔQ≥2−1 (hence, DQ≥(2−1)/3). We then propose a two-lane experimental audit protocol: (i) prior-relative fair-sampling diagnostics using tags recorded on all trials, and (ii) prior-free dispersion diagnostics using accepted-tag distributions across settings, with ΔQ,X computable by linear programming on finite tag alphabets.

Letter graphs and well-quasi-order by induced subgraphs

A diesel spray overall SMD (Sauter mean diameter) in a spray chamber was simulated with CFD by varying the compression ratio in the spray chamber from 18:1 to 100:1. The gas densities of the spray chambers for the compression ratios of 18:1 and 100:1 were 17.97 and <TEX>$74.8kg/m^3$</TEX>, respectively. Standard KIVA-3V code was used for the CFD simulation. Various fuel injection patterns such as single injection, pilot injection and split injection were used for the CFD simulation. Fuel injection pressures for the simulated diesel sprays are 90 and 120 MPa. As the compression ratio increases, the CFD simulated SMD was decreased, which was generally in agreement with previous experimental studies.

Thermodynamic analysis of combustion and pollutants formation in a wood-gas spark-ignited heavy-duty engine

The thesis titled antecedents and enablers of green supply chain practices focuses on one of the most contemporary issues in supply chain management. The literature review explores the existing literature and research work on green supply chain practices and develops a framework for the research. The research is qualitative in nature and data was collected from the three automobile component-manufacturing companies in India. Semi structured interviews were conducted over a period of 18 months. There were three objectives for this thesis: 1. Describing the current state of green supply chain practices? 2. What are the antecedents and enablers for green supply chain practices? 3. What are the underlying mechanisms, if any? The research work concludes by answering all the above three questions and also gives the future direction for research. The research work started by finding a gap for the empirical research in the context of green supply chain practices. The objective of the research was to focus on antecedents and enablers of green supply chain practices. Some contextual factors, inhibitors and consequences are also emerged during the pilot case study. The research work is rigor and to ensure the rigor of the research design, five-stage process was used to structure the methodology. As a final check author assessed his research against the four basic tests commonly used in empirical research; construct validity, internal validity, external validity and reliability. The research study has contributed both to the development and testing of theory relating to the antecedents and enablers of green supply chain practices. The review of literature provided a synthesis of the underpinning bodies of literature that has not previously been conducted in this way. This resulted in the identification of ten core green supply chain practices for the development of antecedents and enablers that created the foundation for author’s empirical investigation. It was found that previous studies have been largely theoretical. The empirical studies that do exist have focused on one particular dyadic relationship with in green supply chain practices. A double contribution has been made to testing the theory of green supply chain practices from a process and output perspective. As process perspective, a contribution has been made to methodology by developing a robust approach for conducting supply chain research beyond the dyad. From output perspective, the author has the empirical results from the three individual case studies and their cross-case comparison for dissemination to an academic audience. Specific contribution of this research to theory development include: 1. Development of macro model of green supply chain practices with the inputs from literature. 2. The synthesis of ten core green supply chain practices with antecedents and enablers from existing body of literature enriched through empirical testing 3. Empirical derivation of three contextual factors. Although the research work is new and contribute to the theory and practices, there are still some limitations of this research. Two minor limitations have been identified: 1. Generalizability of result to practice to practice: Due to the limited size of the case study approach, the results can only be generalized to theory and not to practice. 2. Variation in quality of information: The scope of data collection for all three case studies was same still the quality of information gathered was different. As good quality cross-case analysis was still possible but the relative strengths of the three cases varied. Overall the research work is original, rigor, and contributes to the existing theory and also paves the path for future research work in the area of green supply chain practices.

Novel maximal encoding, encoding, and maximal prefix encoding different from Huffman encoding are introduced. It is proven that for finite source alphabets all Huffman codes are optimal maximal codes, codes, and maximal prefix codes. Conversely, the above three types optimal codes need not to be the Huffman codes. Completely similar to Huffman codes, we prove that for every random variable with a countably infinite set of outcomes and with finite entropy there exists an optimal maximal code (code, maximal prefix code) which can be constructed from optimal maximal codes (codes, maximal prefix codes) for truncated versions of the random variable, and furthermore, that the average code word lengths of any sequence of optimal maximal codes (codes, maximal prefix codes) for the truncated versions converge to that of the optimal maximal code (cone, maximal prefix code).

Hearing aids provide nonlinear amplification to improve speech audibility and loudness perception. While more audibility typically increases speech intelligibility at low levels, the same is not true for above-conversational levels, where decreases in intelligibility ("rollover") can occur. In a previous study, we found rollover in speech intelligibility measurements made in quiet for 35 out of 74 test ears with a hearing loss. Furthermore, we found rollover occurrence in quiet to be associated with poorer speech intelligibility in noise as measured with linear amplification. Here, we retested 16 participants with rollover with three amplitude-compression settings. Two were designed to prevent rollover by applying slow- or fast-acting compression with a 5:1 compression ratio around the "sweet spot," that is, the area in an individual performance-intensity function with high intelligibility and listening comfort. The third, reference setting used gains and compression ratios prescribed by the "National Acoustic Laboratories Non-Linear 1" rule. Speech intelligibility was assessed in quiet and in noise. Pairwise preference judgments were also collected. For speech levels of 70 dB SPL and above, slow-acting sweet-spot compression gave better intelligibility in quiet and noise than the reference setting. Additionally, the participants clearly preferred slow-acting sweet-spot compression over the other settings. At lower levels, the three settings gave comparable speech intelligibility, and the participants preferred the reference setting over both sweet-spot settings. Overall, these results suggest that, for listeners with rollover, slow-acting sweet-spot compression is beneficial at 70 dB SPL and above, while at lower levels clinically established gain targets are more suited.