Optimal stabilization for differential systems with delays - Malkin’s approach

The paper considers a process controlled by a system of delayed differential equations. Under certain assumptions, a control function is determined such that the zero solution of the system is asymptotically stable and, for an arbitrary solution, the integral quality criterion with infinite upper limit exists and attains its minimum value in a given sense. To solve this problem, Malkin’s approach to ordinary differential systems is extended to delayed functional differential equations, and Lyapunov’s second method is applied. The results are illustrated by examples, and applied to some classes of delayed linear differential equations.     

What makes a review a reliable rating in recommender systems?

The way that users provide feedback on items regarding their satisfaction varies among systems: in some systems, only explicit ratings can be entered; in other systems textual reviews are accepted; and in some systems, both feedback types are accommodated. Recommender systems can readily exploit explicit ratings in the rating prediction and recommendation formulation process, however textual reviews -which in the context of many social networks are in abundance and significantly outnumber numeric ratings- need to be converted to numeric ratings. While numerous approaches exist that calculate a user's rating based on the respective textual review, all such approaches may introduce errors, in the sense that the process of rating calculation based on textual reviews involves an uncertainty level, due to the characteristics of the human language, and therefore the calculated ratings may not accurately reflect the actual ratings that the corresponding user would enter. In this work (1) we examine the features of textual reviews, which affect the reliability of the review-to-rating conversion procedure, (2) we compute a confidence level for each rating, which reflects the uncertainty level for each conversion process, (3) we exploit this metric both in the users’ similarity computation and in the prediction formulation phases in recommender systems, by presenting a novel rating prediction algorithm and (4) we validate the accuracy of the presented algorithm in terms of (i) rating prediction accuracy, using widely-used recommender systems datasets and (ii) recommendations generated for social network user satisfaction and precision, where textual reviews are abundant.     

Energy conversion in biological systems—part II. heat production in brown adipose tissue

This study involves the application of bond graphs to the generation of heat by cells in brown adipose tissue. In the first portion of this paper, data are presented to show the types of signals that can be measured at several sites in the system controlling thermogenesis—signals travelling from the brain to the tissue as well as signals over a feedback pathway from spinal cord temperature receptors back to the brain. Bond graphs are developed for several components of the system with an emphasis being placed on graphs describing the alternative mechanisms proposed for cellular energy conversion. The power flow is calculated using ENPORT for one mechanism for different values of plasma membrane resistance.     

A unified superatomic-molecule theory for local aromaticity in π-conjugated systems

Aromaticity is one of the most important concepts in chemistry.However,there is still no unified chemical insight for various systems with conjugated sp² carbon.Herein,we proposed a superatomic-molecule theory to build a generalized electron rule for polycyclic conjugated hydrocarbons,fullerenes and 2D periodic materials.Taking benzenoid units as 2D superatoms,polycyclic conjugated hydrocarbons and C₆₀can be seen as superatomic molecules consisting of bonded superatoms,resu...     

Smart cities: Advances in research—An information systems perspective

Smart cities employ information and communication technologies to improve: the quality of life for its citizens, the local economy, transport, traffic management, environment, and interaction with government. Due to the relevance of smart cities (also referred using other related terms such as Digital City, Information City, Intelligent City, Knowledge-based City, Ubiquitous City, Wired City) to various stakeholders and the benefits and challenges associated with its implementation, the concept of smart cities has attracted significant attention from researchers within multiple fields, including information systems. This study provides a valuable synthesis of the relevant literature by analysing and discussing the key findings from existing research on issues related to smart cities from an Information Systems perspective. The research analysed and discussed in this study focuses on number of aspects of smart cities: smart mobility, smart living, smart environment, smart citizens, smart government, and smart architecture as well as related technologies and concepts. The discussion also focusses on the alignment of smart cities with the UN sustainable development goals. This comprehensive review offers critical insight to the key underlying research themes within smart cities, highlighting the limitations of current developments and potential future directions.     

New insights in stability analysis of delayed Lotka–Volterra systems

Most of the reported Lotka–Volterra examples have at most one stability interval for the delay parameters. Furthermore, the existing methods fall short in treating more general case studies. Inspired by some recent results for analyzing the stability of time-delay systems, this paper focuses on a deeper characterization of the stability of Lotka–Volterra systems w.r.t. the delay parameters. More precisely, we will introduce the recently-proposed frequency-sweeping approach to study the complete stability problem for a broad class of linearized Lotka–Volterra systems. As a result, the whole stability delay-set can be analytically determined. Moreover, as a significant byproduct of the proposed approach, some Lotka–Volterra examples are found to have multiple stability delay-intervals. To the best of the authors’ knowledge, such a characterization represents a novelty for having some insights in the population dynamics: in some situations, a longer maturation period of species is helpful for the stability of a population system.     

商品期货市场运用Optimal F研究

资金管理主要用于具有杠杆的金融工具交易中头寸的管理,是影响商品期货交易成败的重要因素.本文针对我国商品期货市场运用Optimal F资金管理方法;并对于理论的应用过程中以及实际交易中可能遇到的一些问题进行分析,努力给出可行的解决办法;而对于那些目前不易解决的问题,也指出其结症所在和对未来解决方法预期.文章重点研究保证金限制的F和收益和亏损的F.     

How do innovation systems interact? Schumpeterian innovation in seven Australian sectors

This paper analyses how and why different types of innovation systems interact through analysing seven Australian sectors. We find that there are sets of mechanisms or systems that ‘articulate’; i.e. structure and shape the interaction among sectoral innovation systems and other types of innovation systems. Drawing on the Schumpeterian and evolutionary legacy, we contribute a theoretical explanation of how interaction among innovation systems influences innovation. First, this interaction enables and enhances variety creation by expanding the new combinations of knowledge and resources a firm can achieve. Second, it allows for more efficient and effective scaling up of useful knowledge recombination to achieve increasing returns. Empirically, this is supported in that the more successful sectors have active articulation systems with alignment with other systems, while weaker sectors have unplanned and patchy linkages. No simple model seems to explain successful articulation. However, important factors are active receptor firms with the motivation and capabilities to absorb and use resources from external systems, high quality and responsive education systems, and international linkages. Public research, labour markets, and intermediaries varied in importance.     

Energy conversion in biological systems—part I. chemical reactions and ion transport

Constitutive equations for nonisothermal chemical reactions are derived with attention to temperature dependent parameters. Equations are also developed for the coupling of chemical reactions to ion transport. The equations are shown to be consistent with the laws of thermodynamics.     

Stability in mean of partial variables for stochastic reaction–diffusion systems with Markovian switching

This paper is denoted to investigating stability in mean of partial variables for stochastic reaction–diffusion equations with Markovian switching (SRDEMS). By transforming the integral of the trajectory with respect to spatial variables as the solution of the stochastic ordinary differential equations with Markovian switching (SODEMS) and using Itô formula, sufficient criteria on uniform stability in mean, asymptotic stability in mean, uniformly asymptotic stability in mean, exponential stability in mean of partial variables for SRDEMS are first derived. An example is presented to illustrate the effectiveness and efficiency of the obtained results.     

SecureCPS: Cognitive inspired framework for detection of cyber attacks in cyber–physical systems

In the era of autonomous systems, the security is indispensable module for flexible computing environment. Due to increased computer power and network speed, a new computing paradigm, such as cognitive inspired computing, will emerge. Such a paradigm provides human-centered services that are convenient and enjoyable at any time, anywhere, and on any device. On the foundation of smart city environment, human computer interaction, intelligent services, and universal device connectivity, Cyber Physical Computing for Cyber Physical systems has recently been investigated. However, in this proposal, a cognitive inspired framework for securing CPS is scrutinized. The cognitive ability is conceded to the search engines by updating the PageRank ranking methodology. The proposed framework, named SecureCPS is trained with real time collective dataset for marking the relevancy of web page with the support the facial expressions. The eye regions are marked using Focal Point Detector algorithm. The framework is validated with machine learning models and resulted in achieving 98.51% accuracy and its outperforms the existing frameworks.     

Knowledge flows and bases in emerging economy innovation systems: Brazilian research 2005–2009

This article considers the role of domestic knowledge capabilities for developing countries and emerging economies, and in particular in the build-up of their national systems of innovation. Using bibliometric methods, we describe the geographic sources of knowledge and the users of Brazilian research in 2005–2009, and analyze the roles of domestic and foreign knowledge bases in it. Our results suggest that increasing reliance on domestic sources of knowledge is a feature of Brazil's improved science and technology capabilities. The ascendancy of Brazil's research informs us about the unfolding re-organization of global research, too, underlining nascent South-South knowledge flows, the prevailing relevance of EU research, and the relative decline of US research for Brazilian knowledge creation.     

Optimal parameter estimation of ε-filter employing distribution distance

As the filter which can effectively remove the small amplitude noises on digital images, the $\epsilon \mathrm{-}\mathrm{filter}$ has been proposed. In order to effectively use this filter, a smoothing parameter $\epsilon \mathrm{-}\mathrm{filter}$ should be appropriately estimated before applying it. To address this problem, the authors proposed the parameter estimation method based on Hellinger distance (HD). In the method, HD between a residual signal and assumed noise distribution was evaluated, and a parameter $\epsilon$ of the $\epsilon \mathrm{-}\mathrm{filter}$ was estimated by finding the value giving minimum distance. However, the enough discussion on use of HD has not been made.In this paper, it is attempted to utilize not only the HD, but also various distribution distances in the parameter estimation, and their performances and characteristics are compared and analyzed experimentally. Furthermore, the parameter estimation method is extended to be applicable for the vector $\epsilon \mathrm{-}\mathrm{filter}$ for the color images. Consequently, through the experiments, it is shown that L1-norm or maximum norm is appropriate as the distribution distance used in the parameter estimation methods from the view points of the simplicity of the calculation and MSE performance in the filtering.     

Only one way to skin a cat? Heterogeneity and equifinality in European national innovation systems

One of the most significant results of the qualitative literature on national systems of innovation (NSIs) is that different systemic arrangements (i.e. configurations of actors and institutions) can deliver similar levels of innovative performance. Using factor analysis on a novel dataset of 29 quantitative indicators of innovative activities we provide an empirical characterization of the structure of European NSIs over the last ten years. Our results cast doubt on the empirical significance of the “equifinality” of heterogeneous systemic arrangements in the context of NSI. Innovation systems show inherent complexity, which leads to a high level of complementarity among their constituent components and configuration. This result implies that successful innovation policies should be systemic, leaving little flexibility in policy design and scope.     

Event-based weighted residual generator design via non-PDC scheme for fault diagnosis in T–S fuzzy systems

This paper is concerned with the event-based weighted residual generator design via non-parallel distribution compensation (PDC) scheme for fault diagnosis in discrete-time T–S fuzzy systems, under consideration of the imperfect premise matching membership functions. An event-triggered mechanism is firstly introduced to save communication resources, which leads to the premise variables of the system and observer to be asynchronous. Then, a fuzzy diagnostic observer with mismatched premise variables is designed to estimate the unmeasurable states of the system. Moreover, by using non-PDC method, a diagnostic observer-based weighted residual generator is established to improve the fault detection (FD) performance by using the information provided by each local system, in which the membership functions structure of the diagnostic observer and residual generator need not to be the same as the systems, and the L_∞/L₂ and L_∞ FD scheme is used to optimize the FD performance. Finally, two simulation results are provided to show the efficiency of the proposed non-PDC method.     

LWT–DSR based new robust framework for watermark extraction under intentional attack conditions

This paper proposes a new watermarking approach using dynamic stochastic resonance (DSR) based tuning operation to extract the watermark logo from the watermarked image that has undergone different intentional and signal processing attacks. This method is intended to provide remedies from the shortcomings of the technique proposed by Lin et al. (2008), and invalidates the effect of intentional attacks recently designed by Meerwald et al. (2009). The algorithm incorporates three level image decomposition using lifting wavelet transform (LWT) and low-pass subband is utilized for data hiding purpose. Watermark bits are embedded into the blocks of non-overlapped wavelet coefficients of the cover image by quantizing the two maximum coefficients of the corresponding block. In watermark extraction process, the DSR is applied by performing the tuning operation on coefficient blocks of attacked watermarked image. It is a parameter dependent approach that enhances the performance of watermark extraction, where the parameters of DSR inherently depend on the image properties such as standard deviation or variance. As far as security is concerned, the randomization of wavelet coefficients, blocks, and watermark bits helps the framework to be more secure. The proposed technique is also examined against multiple watermarking attack and successfully proves its authenticity and ownership. Comparison of the proposed technique with recent techniques shows remarkable improvement in terms of robustness and security against various intentional, signal processing, and geometrical attacks.     

Do systems pass university entrance exams?

Reading Comprehension tests are commonly used to assess the degree to which people comprehend what they read. This is why we work with the hypothesis that it is reasonable to use these tests to assess the degree to which a machine “comprehends” what it is reading. In this work, we evaluate Question Answering systems using Reading Comprehension tests from exams to enter University. This article analyses the datasets generated, the kind of inferences required, the methodology followed in three evaluation campaigns, the approaches presented by participants and current results. Besides, we study the evolution of systems and the main lessons learned in this evaluation process. We also show how current technologies are unable to pass university-entrance exams. This is because these tests require a deep understanding of texts, as well as detecting the similar meaning of phrases with different words. Future directions focused on these ideas seem more promising than including a massive amount of data for training systems, what has allowed systems to obtain outstanding results in Reading Comprehension tests with more straightforward questions. We think this study helps to increase the knowledge about how to develop better Question Answering systems.     

Safety in unpredictable complex systems – a framework for the analysis of safety derived from the nuclear power industry

The increasing complexity and power of our technologies compels us to find new ways in which to conceptualise, understand and maintain their safety in the long term. Some complex technological industries have performed better than others in terms of applying sustained and systematic approaches to the maintenance of safety. The United States nuclear power industry can be seen as an ideal test-bed for the development of safety initiatives, being responsible for the control of potentially unpredictable technology that involves extraordinary forces and costs. This paper describes and formalises a framework for better understanding the safety of complex socio-technological systems, based on key events in the development of safety in the United States nuclear power industry. The framework comprises two components: (1) a state-space approach for better conceptualising system failures, the benefits of incident reporting and remedial safety initiatives; and (2) a set of milestones that can be used to assess the development of safety in socio-technological industries. Healthcare and the United States nuclear power industry both represent complex socio-technological systems with similar technical characteristics. However, safety strategies in healthcare have not kept pace with the increasing complexity of clinical practice, and there have been international calls for improvements in patient safety. The framework is applied to the analysis of safety in healthcare, demonstrating its utility as an alternative safety analogy in healthcare. Use of the framework indicates substantial scope for improvements in healthcare safety through major evidence-based system redesign. By lowering the threshold for the reporting of incident data to include accident precursors, it is possible to identify problem areas before patient harm occurs.     

News recommender systems – Survey and roads ahead

More and more people read the news online, e.g., by visiting the websites of their favorite newspapers or by navigating the sites of news aggregators. However, the abundance of news information that is published online every day through different channels can make it challenging for readers to locate the content they are interested in. The goal of News Recommender Systems (NRS) is to make reading suggestions to users in a personalized way. Due to their practical relevance, a variety of technical approaches to build such systems have been proposed over the last two decades. In this work, we review the state-of-the-art of designing and evaluating news recommender systems over the last ten years. One main goal of the work is to analyze which particular challenges of news recommendation (e.g., short item life times and recency aspects) have been well explored and which areas still require more work. Furthermore, in contrast to previous surveys, the paper specifically discusses methodological questions and today’s academic practice of evaluating and comparing different algorithmic news recommendation approaches based on accuracy measures.     

Targeting DNA-repair systems brings hopes to cancer patients

CAS researchers have recently raised a hypothesis to circumvent tumor resistance to radio-and chemo-therapy