On Lossless Quantum Data Compression With a Classical Helper

The first description of modern cardiopulmonary resuscitation (CPR) included the instruction to compress the chest “about 60 times per minute”1; however, the optimal compression rate was unknown. Franz Koenig is credited with describing the original technique for external cardiac massage, which included a compression rate of 30 to 40 per minute.2 But in the first published description of external cardiac massage in 1892, Friedrich Maass documented a better clinical response with a rate of 120 per minute.2 To this day, the optimal compression rate is the subject of controversy. Animal data indicate that cardiac output increases with compression rates up to as high as 150 per minute.3 In a canine model of prolonged cardiac arrest, compression rates of 120 per minute compared with 60 per minute increased mean aortic (systolic and diastolic) and coronary perfusion pressures, and 24-hour survival (61% versus 15%, P =0.03).4 In a study of 9 patients undergoing CPR, a compression rate of 120 per minute generated higher aortic peak pressures and coronary perfusion pressures compared with a compression rate of 60 per minute (the rate recommended by the 1980 American Heart Association [AHA] guidelines). This evidence is supported by another study of 23 patients in cardiac arrest in which compressions at 120 per minute resulted in significantly higher end-tidal carbon dioxide values compared with compressions at 80 per minute.5 Article see p 3004 The first large, prospective, observational study of the influence of chest compression rate on patient survival was published in this journal in 2005.6 The number of delivered chest compressions was recorded by trained observers during in-hospital resuscitation attempts. A higher chest compression rate was associated with a higher rate of return of spontaneous circulation (ROSC). The mean chest compression rate for initial survivors was 90 …

On the basis of introducing protocol testing and conformance testing, this paper mainly focuses on introducing the testing generation methods based on Finite State Machine model (FSM), Extended Finite State Machine model (EFSM), Deterministic Finite State Machine model (DFSM) and Non-Deterministic Finite State Machine model (NDFSM) and so on. In conclusion, this paper points out some problems for further research and the development trend in this field.

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.

This paper analyzes the distribution of the code- word lengths of the optimal lossless compression code without prefix constraints both in the non-asymptotic regime and in the asymptotic regime. The technique we use is based on upper and lower bounding the cumulant generating function of the optimum codeword lengths. In the context of prefix codes, the normalized version of this quantity was proposed by Campbell in 1965 as a generalized average length. We then use the one- shot bounds to analyze the large deviations (reliability function) and small deviations (normal approximation) of the asymptotic fundamental limit in the case of memoryless sources. In contrast to other approaches based on the method of types or the Berry- Essinequality, we are able to deal with sources with infinite alphabets. PX(x) is the information in x (with respect to PX ). The mean and variance of {X(X) are the entropy H(X) and varentropy V (X), respectively. Customar- ily, H1(X) = H(X) (which coincides with lim !1H (X), provided H 0(X) < 1 for some 0 < 1). Furthermore, H1(X) = minx2X {X(x). For a discrete random variable X PX and 2 (0; 1), the -scaled version of X, denoted X , is defined by the relation

Perfect codes in vertex-transitive graphs

We develop a systematic approach, based on convex programming and real analysis for obtaining upper bounds on the capacity of the binary deletion channel and, more generally, channels with i.i.d. insertions and deletions. Other than the classical deletion channel, we give special attention to the Poisson-repeat channel introduced by Mitzenmacher and Drinea (IEEE Transactions on Information Theory, 2006). Our framework can be applied to obtain capacity upper bounds for any repetition distribution (the deletion and Poisson-repeat channels corresponding to the special cases of Bernoulli and Poisson distributions). Our techniques essentially reduce the task of proving capacity upper bounds to maximizing a univariate, real-valued, and often concave function over a bounded interval. The corresponding univariate function is carefully designed according to the underlying distribution of repetitions, and the choices vary depending on the desired strength of the upper bounds as well as the desired simplicity of the function (e.g., being only efficiently computable versus having an explicit closed-form expression in terms of elementary, or common special, functions). Among our results, we show the following: (1) The capacity of the binary deletion channel with deletion probability d is at most (1 − d ) φ for d ≥ 1/2 and, assuming that the capacity function is convex, is at most 1 − d log(4/φ) for d &lt; 1/2, where φ = (1 + √5)/2 is the golden ratio. This is the first nontrivial capacity upper bound for any value of d outside the limiting case d → 0 that is fully explicit and proved without computer assistance. (2) We derive the first set of capacity upper bounds for the Poisson-repeat channel. Our results uncover further striking connections between this channel and the deletion channel and suggest, somewhat counter-intuitively, that the Poisson-repeat channel is actually analytically simpler than the deletion channel and may be of key importance to a complete understanding of the deletion channel. (3) We derive several novel upper bounds on the capacity of the deletion channel. All upper bounds are maximums of efficiently computable, and concave, univariate real functions over a bounded domain. In turn, we upper bound these functions in terms of explicit elementary and standard special functions, whose maximums can be found even more efficiently (and sometimes analytically, for example, for d = 1/2).

This paper tackles the problem of zero-error instantaneous coding with decoder side information in light of the Kraft inequality. Specifically, a bounded Kraft sum over all cliques in the characteristic graph of the source/side-information pair is envisioned to be a sufficient condition for the existence of a valid code with given codeword lengths. It is shown that (i) if such a sufficient condition exists for a class of graphs, it is possible to universally bound the rate redundancy in the class, (ii) there exist graph classes of interest for which such sufficient conditions can indeed be found, and finally (iii) no such condition can be found for the class of all graphs.

A supplement to Fu [1] is presented. Three areas are briefly reviewed: 1) control systems with human controller, 2) control systems with man-machine controller, and 3) autonomous robot systems. Problems for further research are discussed.

The increasing popularity of metaheuristic algorithms has attracted a great deal of attention in algorithm analysis and performance evaluations. No-free-lunch theorems are of both theoretical and practical importance, while many important studies on convergence analysis of various metaheuristic algorithms have proven to be fruitful. This paper discusses the recent results on no-free-lunch theorems and algorithm convergence, as well as their important implications for algorithm development in practice. Free lunches may exist for certain types of problem. In addition, we will highlight some open problems for further research.

Vibratory conveying of a material point by harmonic longitudinal and polyharmonic normal vibrations of an inclined conveying surface is considered. The dependence of dimensionless conveying velocity—a ratio of velocity to the product of frequency and amplitude of longitudinal vibration—on several dimensionless parameters is investigated in the moving modes without hopping. Maximal conveying velocity is achieved at the certain values of normal vibration amplitudes and phase difference angle between the longitudinal and normal vibrations, which are called optimal. Their values are dependent on two dimensionless parameters: the inclination angle parameter—a ratio of an inclination angle tangent to a frictional coefficient, the intensive vibration coefficient—a ratio of the longitudinal amplitude of vibration to the amplitude of the first harmonic of normal vibration and frictional coefficient. In a condition of the intensive longitudinal vibration, when its amplitude significantly greater than amplitudes of normal vibration, dimensionless velocity is almost independent of the intensive vibration parameter and it depends only on inclination angle parameter, i.e., on inclination angle and frictional coefficient. The optimal values of harmonics’ amplitudes of polyharmonic normal vibration are determined in dependence of inclination angle parameter with the number of harmonics from 2 to 7. The graphs of considered dependencies are presented and the most important values of parameters are presented in the table. Conclusions are made to determine the optimal vibration parameters and the problems of further research are indicated. The considered vibrations can be used in different vibratory conveying devices with electromagnetic drives.

This paper poses a new problem of detecting an unknown class present in a text corpus which has huge amount of unlabeled samples but a very small quantity of labeled samples. A simple yet efficient solution has also been proposed by modifying conventional clustering technique to demonstrate the scope of the problem for further research. A novel way to estimate cluster diameter is proposed which in turn has been used as a measure to estimate the degree of dissimilarity between two clusters. The main idea of the model is to arrive at a cluster of unlabeled text samples which is far away from any of the labeled clusters guided by few rules such as diameter of the cluster and dissimilarity between pair of clusters. This work is first of its kind in the literature and has tremendous applications in text mining tasks. In fact the model proposed is a general framework which can be applied onto any application which necessarily involves identification of unseen classes in a semi-supervised learning environment. The model has been studied with extensive empirical analysis on different text datasets created from the benchmarking 20Newsgroups dataset. The results of the experimentation have revealed the capabilities of the proposed approach and the possibilities for future research.

On a problem of Erdős, Herzog and Schönheim

Partitions of natural numbers with the same weighted representation functions

Multilevel Processor‐Sharing (MLPS) disciplines refer to a family of age‐based scheduling disciplines introduced decades ago. A time‐discretized version of an MLPS discipline is applied in the scheduler of the traditional UNIX operating system. In recent years, MLPS disciplines have been used to study the way that packet level scheduling mechanisms impact the performance perceived at the flow level in the Internet. Inspired by this latter application, many new sojourn time results have been discovered for these disciplines in the context of the M/G/1 queue. The aim of this paper was to give a consistent overview of these new results. In addition, it points out some intriguing open problems for further research.

With the rapid growth of the global economy, the global car ownership is also increasing year by year, which has caused a series of problems, the most prominent of which is traffic congestion and traffic accidents. In order to solve the traffic problem, all countries are actively studying the intelligent transportation system, and one of the important research contents of the intelligent transportation system is vehicle detection. Vehicle detection based on vision is to capture vehicle images in the driving environment through a camera, and then use computer vision recognition technology for vehicle detection and recognition. Although computer vision recognition technology has made great progress, how to improve the detection accuracy of the image to be detected is still an important content of visual recognition technology research. Intelligent vehicle visual robust detection and identification of methods of research to reduce the growing incidence of traffic accidents, improve the existing road traffic safety and transportation efficiency, alleviate the degree of driver fatigue problem are of great significance. This paper considers the intelligent vehicle environmental awareness of the key technology to the goal of robust detection and recognition based on machine vision problems for further research. The particle filter is used to extract the local energy of the image to realize the fast segmentation of the region of interest (ROI). In order to further verify the ROI, a measure learning method based on multi-core embedding is proposed, and the semantic classification of ROI is realized by integrating the color, shape and geometric features of ROI. Experimental results show that the algorithm can effectively eliminate false sexy ROI interest, and the algorithm is robust to complex background, illumination changes, perspective changes and other conditions.