How to best sample a periodic probability distribution, or on the accuracy of Hamiltonian finding strategies

Projective measurements of a single two-level quantum mechanical system (a qubit) evolving under a time-independent Hamiltonian produce a probability distribution that is periodic in the evolution time. The period of this distribution is an important parameter in the Hamiltonian. Here, we explore how to design experiments so as to minimize error in the estimation of this parameter. While it has been shown that useful results may be obtained by minimizing the risk incurred by each experiment, such an approach is computationally intractable in general. Here, we motivate and derive heuristic strategies for experiment design that enjoy the same exponential scaling as fully optimized strategies. We then discuss generalizations to the case of finite relaxation times, T ₂ < ∞.     

PiSHi: click the images and I tell if you are a human

This paper introduces pictorial intelligent system for human identification (PiSHi), an image-based captcha which uses three human cognitive abilities to distinguish humans from machines. The first is the human ability to easily recognise the image’s upright orientation. The second is the human brain’s ability in recognising a picture’s content when it is only partially visible. And the third is the human ability in unconscious decision making when encountering pictorial challenges. This work models such complicated human patterns in problem solving for the first time. In order to extract these behavioural patterns and save them in a pattern database, we have implemented our own captcha and performed a series of experiments. PiSHi’s interface presents the user with a set of distorted pictures and asks her to click on the upright orientation of all the pictures in any preferred order. Next, it captures the user’s interaction patterns, compares them with the ones saved in the pattern database, and grants her a corresponding credit. Based on this credit, the user either passes or fails the test, and participates in updating the picture database. Our experiments indicate that human users can solve our proposed captcha effectively—with an accuracy of 99.44 %. Besides, our proposed system is secure against several types of attacks including random guessing and reverse image search engines. The results offer the possibility of utilising the identified human behavioural models in practical captchas.     

Inference for grouped data with a truncated skew-Laplace distribution

The skew-Laplace distribution has been used for modelling particle size with point observations. In reality, the observations are truncated and grouped (rounded). This must be formally taken into account for accurate modelling, and it is shown how this leads to convenient closed-form expressions for the likelihood in this model. In a Bayesian framework, “noninformative” benchmark priors, which only require the choice of a single scalar prior hyperparameter, are specified. Conditions for the existence of the posterior distribution are derived when rounding and various forms of truncation are considered. The main application focus is on modelling microbiological data obtained with flow cytometry. However, the model is also applied to data often used to illustrate other skewed distributions, and it is shown that our modelling compares favourably with the popular skew-Student models. Further examples with simulated data illustrate the wide applicability of the model.     

How to re-use a one-time pad safely and almost optimally even if P = NP

Assuming an insecure quantum channel, a quantum computer, and an authenticated classical channel, we propose an unconditionally secure scheme for encrypting classical messages under a shared key, where attempts to eavesdrop the ciphertext can be detected. If no eavesdropping is detected, we can securely re-use the entire key for encrypting new messages. If eavesdropping is detected, we must discard a number of key bits corresponding to the length of the message, but can re-use almost all of the rest. We show this is essentially optimal. Thus, provided the adversary does not interfere (too much) with the quantum channel, we can securely send an arbitrary number of message bits, independently of the length of the initial key. Moreover, the key-recycling mechanism only requires one-bit feedback. While ordinary quantum key distribution with a classical one time pad could be used instead to obtain a similar functionality, this would need more rounds of interaction and more communication.     

“Damned if you do,damned if you don’t”: Media frames of responsibility and accountability in handling a wildfire

Previous research on media framing of wildfire has chiefly been concerned with the nature of wildfire in the context of climate change and with framing effects on policy and public opinion. Empirical studies on media content, hence what is mediated to crisis managers and the public concerning authorities’ and the public's response, seem to be largely missing. This is remarkable, given that the media represent main sources of information that may influence crisis management and shape public opinion. Thus, the aim of this study was to identify key media frames relating to portrayals of public and authority responses during and after a wildfire crisis. The study is based on media articles from two time periods: immediately after the fire and 1 year later. We used a thematic method of analysis (TA), thus an inductive, “bottom‐up” approach. A core frame, Responsibility/accountability is identified, underpinned by two sub‐themes. One sub‐theme relates to the causes of the fire and its escalation, revealing a number of different interrelated blame frames. The second sub‐theme refers to management of the crisis, reflecting both authorities’ and citizens’ responses. The deficiencies of the former are implicitly suggested to have forced citizens to act to compensate for their inadequacy. The main theoretical contribution is the identification of an interrelationship between frames in relation to different groups of individuals responding to a crisis, pointing to a more complex view of framing effects. In addition, results show how media tend to assess crisis management based on idealistic criteria, inevitably making the evaluation negative. This contributes to an understanding of how media blame frames, thus “blame games,” may unfold. Practical implications of these results are discussed.     

How anonymous are you online? Examining online social behaviors from a cross-cultural perspective

Communication on the Internet is often described as “anonymous”, yet the usage of the term is often confusing, even in academia. Three levels of anonymity, visual anonymity, dissociation of real and online identities, and lack of identifiability, are thought to have different effects on various components of interpersonal motivation. Specifically, we propose that cross-cultural differences in interpersonal motivation (autonomy vs. affiliation) are illustrated by choices individuals make when deciding whether or not to remain anonymous while communicating online. Autonomy is often valued in Western societies, whereas Eastern societies tend to emphasize affiliation, suggesting that individuals in Western societies will gravitate toward online communities that allow lower levels of anonymity, while individuals in Eastern societies will be more likely to seek out online communities that promote higher levels of anonymity. The research presented in this article supports this notion, suggesting that we need to consider cultural differences when designing online communication systems and other communications technologies.     

How Would You Know if You Synthesized a Thinking Thing?

We confront the following popular views: that mind or life are algorithms; that thinking, or more generally any process other than computation, is computation; that anything other than a working brain can have thoughts; that anything other than a biological organism can be alive; that form and function are independent of matter; that sufficiently accurate simulations are just as genuine as the real things they imitate; and that the Turing test is either a necessary or sufficient or scientific procedure for evaluating whether or not an entity is intelligent. Drawing on the distinction between activities and tasks, and the fundamental scientific principles of ontological lawfulness, epistemological realism, and methodological skepticism, we argue for traditional scientific materialism of the emergentist kind in opposition to the functionalism, behaviourism, tacit idealism, and merely decorative materialism of the artificial intelligence and artificial life communities.     

Quantum Cryptography II: How to re-use a one-time pad safely even if P=NP

When elementary quantum systems, such as polarized photons, are used to transmit digital information, the uncertainty principle gives rise to novel cryptographic phenomena unachievable with traditional transmission media, e.g. a communications channel on which it is impossible in principle to eavesdrop without a high probability of being detected. With such a channel, a one-time pad can safely be reused many times as long as no eavesdrop is detected, and, planning ahead, part of the capacity of these uncompromised transmissions can be used to send fresh random bits with which to replace the one-time pad when an eavesdrop finally is detected. Unlike other schemes for stretching a one-time pad, this scheme does not depend on complexity-theoretic assumptions such as the difficulty of factoring.     

How to meet when you forget: log-space rendezvous in arbitrary graphs

Two identical (anonymous) mobile agents start from arbitrary nodes in an a priori unknown graph and move synchronously from node to node with the goal of meeting. This rendezvous problem has been thoroughly studied, both for anonymous and for labeled agents, along with another basic task, that of exploring graphs by mobile agents. The rendezvous problem is known to be not easier than graph exploration. A well-known recent result on exploration, due to Reingold, states that deterministic exploration of arbitrary graphs can be performed in log-space, i.e., using an agent equipped with O(log n) bits of memory, where n is the size of the graph. In this paper we study the size of memory of mobile agents that permits us to solve the rendezvous problem deterministically. Our main result establishes the minimum size of the memory of anonymous agents that guarantees deterministic rendezvous when it is feasible. We show that this minimum size is Θ(log n), where n is the size of the graph, regardless of the delay between the starting times of the agents. More precisely, we construct identical agents equipped with Θ(log n) memory bits that solve the rendezvous problem in all graphs with at most n nodes, if they start with any delay τ, and we prove a matching lower bound Ω(log n) on the number of memory bits needed to accomplish rendezvous, even for simultaneous start. In fact, this lower bound is achieved already on the class of rings. This shows a significant contrast between rendezvous and exploration: e.g., while exploration of rings (without stopping) can be done using constant memory, rendezvous, even with simultaneous start, requires logarithmic memory. As a by-product of our techniques introduced to obtain log-space rendezvous we get the first algorithm to find a quotient graph of a given unlabeled graph in polynomial time, by means of a mobile agent moving around the graph.     

如何从电视迷变成摇滚迷

您可能永远没有机会真正坐在科克船长的旁边,陪伴他进行遥远的太空探险．但您完全可以在虚拟世界中体验这些。坐上它．您可以觉得像是～个真正的宇航员。来自魁北克的D—Box技术公司设计和生产的D—Box Quest运动模拟座椅可以为你提供魅力无穷的虚拟实景旅行。     

Case management a must to survive managed care

Fast, efficient access to patient information is now an essential management tool. Not only does it facilitate a streamlined approach to the continuum of care, but it also helps ensure the kind of quality that consumers are clamoring for.     

“You will only see it,if you understand it” or occupational risk prevention from a management perspective

Evidence of a managerial influence on occupational risk prevention is largely lacking. The incidence of major accidents in high‐hazard sectors of industry does not show a downward trend. Also, the decline of fatal occupational accidents in industrialized Western countries may well be attributed to the growing employment in the relatively safe service sectors and to a phenomenon known as export of hazards. Looking more closely at accidents and disasters, we now believe they are not only caused by direct physical events, nor by human errors alone. They have their roots in organizational settings and in the sociotechnical system companies are active in. Whatever their cause, we know that (major) accidents almost always take us by surprise. Despite all our efforts and systems, we seem unable to foresee or predict these events. It seems our management systems are looking at the wrong items. Critics from small‐ and medium‐sized enterprises also point in that direction; management systems are too bureaucratic and lack a focus on hazard and risk identification. Apparently, we fail to incorporate the main ingredients of accident causation in our management systems. This article will discuss current models and presentations. In reference to the title of this article, the possibility to integrate these presentations into management systems will be discussed. This article is based on the presentation given at the 4th International Conference on Occupational Risk Prevention, Sevilla, Spain, May 10–12, 2006. © 2008 Wiley Periodicals, Inc.     

How to produce all sentences from a two-level grammar

Two-level grammars are very readable formalisms for generating Chomsky Type 0 languages. Teaching and understanding them is greatly aided by the presence of a sentence generator. This paper shows how a usable sentence generator can be constructed. A working program is available from the author.     

How do you visit: Identifying addicts from large-scale transit records via scenario deep embedding

Identification of individuals based on transit modes is of great importance in user tracking systems. However, identifying users in real-life studies is not trivial owing to the following challenges: 1) activity data containing both temporal and spatial context are high-order and sparse; 2) traditional two-step classifiers depend on trajectory patterns as input features, which limits accuracy especially in the case of scattered and diverse data; 3) in some cases, there are few positive instances and they are difficult to detect. Therefore, approaches involving statistics-based or trajectory-based features do not work effectively. Deep learning methods also suffer from the problem of how to represent trajectory vectors for user classification. Here, we propose a novel end-to-end scenario-based deep learning method to address these challenges, based on the observation that individuals may visit the same place for different reasons. We first define a scenario using critical places and related trajectories. Next, we embed scenarios via path-based or graph-based approaches using extended embedding techniques. Finally, a two-level convolution neural network is constructed for the classification. Our model is applied to the problem of detection of addicts using transit records directly without feature engineering, based on real-life data collected from mobile devices. Based on constructed scenario with dense trajectories, our model outperforms classical classification approaches, anomaly detection methods, state-of-the-art sequential deep learning models, and graph neural networks. Moreover, we provide statistical analyses and intuitiveexplanations to interpret the characteristics of resident and addict mobility. Our method could be generalized to other trajectory-related tasks involving scattered and diverse data.