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As the scale of distributed generations connecting to the power system increases continuously, communication system considering the requirements of real-time control is becoming much more important in active distribution system. Therefore, in order to improve the responsiveness of the distribution network during the communication interruption, an offline backup strategy is proposed considering the combined output of distributed generations and energy storage systems involving the characteristics of the active distribution system. Based on a typical set of clusters which describe the features of wind turbines and photovoltaics, the strategy analyses operational vulnerability combining structural characteristics of the active distribution system and solves the output level of each distributed generation according to the improved algorithm. A numerical case study is presented to demonstrate the effectiveness of this model.

Modern scientific approaches to building a comprehensive assessment of the quality of automated control are not possible without the use of systematic analysis methodology. System analysis provides the completeness and comprehensiveness of the study of a complex system, allows you to combine into a whole set of processes that occur in different fields, such as economic, social, environmental, military. Today, all the links between complex military systems are poorly formalized and generally investigated. At the same time, the complex system itself is poorly structured and interconnected. On this basis, the authors propose the use of system-cognitive analysis to describe and study such systems. The Geospatial Intelligence system is an integral part of the military intelligence system and the overall monitoring system of Ukraine's allies, coalitions and blocs, and there are pro-functions that are detailed into a typical set of tasks performed through the composition of internal functions and basic information-technological algorithms of system functioning. In turn, the automation of the Geospatial Intelligence is aimed at improving the efficiency of the system as a whole. In the development of an automated control system for the Geospatial Intelligence, the priority is to build a correct mathematical model of the control object. It is shown that the Geospatial Intelligence system is a multi-purpose weakly structured system in which the deterministic and bifurcation stages are distinguished. Managing such a system is a multi-criteria task that is complicated by the need to take into account group preferences of decision-makers. The quality of the decision support problem in the management process cannot be evaluated by one function or even by several scales. In such cases, the rational choice mechanism requires additional indirect information, which allows at least to compare alternatives to the choice of management strategies. Therefore, it is necessary to formulate and solve the problem of steady control of the system of Geospatial Intelligence in different conditions and states of its functioning on the basis of system-cognitive analysis. Theoretical studies of computational methods of decision theory prove the importance of determining the requirements for the procedure for forming a vector criterion. These requirements include the completeness of the set of criteria, the redundancy, the ability to decompose, the minimum, the ability to measure. The procedure for constructing such a vector criterion is quite complex, ambiguous and sometimes unformalized. The purpose of the article. The purpose of the article is to improve the scientific and methodological apparatus based on the use of system-cognitive analysis to determine the vector criterion in solving the problem of steady control, determine the value and influence of input parameters on the functioning and choice of strategy management of the Geospatial Intelligence system.

Data Analytics is rapidly expanding within the healthcare domain to help develop strategies for improving the quality of care and curbing costs as well. Natural Language Processing (NLP) solutions have received particular attention whereas a large part of clinical data is stockpiled into unstructured physician or nursing notes. In this respect, we attempt to employ NLP to provide an early prediction of the medical specialties at hospital admission. The study uses a large-scale dataset including more than 260K ED records provided by the Amiens-Picardy University Hospital in France. Our approach aims to integrate structured data with unstructured textual notes recorded at the triage stage. On one hand, a standard MLP model is used against the typical set of features. On the other hand, a Convolutional Neural Network is used to operate over the textual data. While both learning components are conducted independently in parallel. The empirical results demonstrated a promising accuracy in general. It is conceived that the study could be an additional contribution to the mounting efforts of applying NLP methods in the healthcare domain.

Class-modelling methods aim to predict the conformity of new unknown samples with a single target class, using statistical decision rules built exclusively with objects of that class. This article introduces a novel class-modelling method for spectral data. The method uses the concept of β%-prediction band for functional data to classify spectra. The band is defined by an upper and a lower limiting spectra which delimit critical trajectories for β% of future spectra of the target class. It is constructed in three main steps: firstly, a naive bootstrap sample of calibration spectra is projected onto a parsimonious principal component (PC) basis and their scores are estimated. The posterior predictive distribution of the scores on each PC is estimated using a Bayesian zero-mean normal model. This procedure is repeated on naive bootstrap estimations of the PCs to obtain the predictive distribution of the scores. These enable to account for all modelling uncertainties including the random deviation of scores from their zero-mean on each PC, uncertainty in the variance of scores (eigenvalue) on each PC, and uncertainty in the PC estimations. Secondly, the predicted scores are back-transformed to the original signal scale to obtain the predictive distribution of future spectra. Thirdly, the predicted spectra are ranked to select the β% most central ones as typical set, whose ranges of variation are used to construct the simultaneous limits of the band. Once the band is constructed, reconstructions of future unknown test spectra by bootstrap PC models are projected onto it, and the extent to which they overlap with it is used to decide their acceptance or rejection. The statistical properties and classification performances of the proposed prediction band are evaluated on real near-infrared datasets and compared to the well-known soft-independent modelling of class analogy (SIMCA) model. The results of the evaluation provide evidence that the proposed prediction band possesses satisfactory predictive performances. It even outperforms the SIMCA while offering attractive advantages like risk-management and straightforward physical interpretability of outlyingness patterns of tested spectra.

Subject: The article contains investigation of the questions related to semantic and syntactic analysis of the texts, decomposition of sentences into component processes, the construction of the syntactic structure of sentences; semantic interpretation of the fragments of a natural language sentence into fragments of an M-language; the composition of the fragments of the M-language in the structure of the abstract, describing the problem environment. Purpose: development of a method for analyzing and processing information on the DSS ACS. Objective: To analyze the research of recent years related to the solution of analyzing the content of the language structure problem from the point of view of creating dialogue systems software, to make a conclusion about the appropriateness of research directions. Perform a detailed description of the stages of performing semantic and parsing with a description of the input, intermediate and output data. Determine the recommendations for the input data variability depending on the structure of the sentences of the subject area (the text described in natural language). Suggest rules for the formation of predicates for different parts of the Ukrainian language. Determine the typical set of service awards for filling the reference dictionary. Justify the implementation of each of the above operations for combining into a single computing structure, which is performed at certain stages. Develop procedures for passing each of the stages. Suggest rules for the formation of syntactic groups for certain pairs of tokens. Conclusions: The application of the developed method based on certain rules in predicates will allow to sample informatively significant information from a set of textual information and present it as an annotation (abstract).

Andrey Kolmogorov put forward in 1933 the five fundamental axioms of classical probability theory. The original idea in my complex probability paradigm is to add new imaginary dimensions to the experiment real dimensions which will make the work in the complex probability set totally predictable and with a probability permanently equal to one. Therefore, adding to the real set of probabilities $ {\sc{R}} $ the contributions of the imaginary set of probabilities $ \sc{M} $ will make the event in $ \sc{C}= \sc{R} + \sc{M} $ absolutely deterministic. It is of great importance that stochastic systems become totally predictable since we will be perfectly knowledgeable to foretell the outcome of all random events that occur in nature. Hence, my purpose here is to link my complex probability paradigm to Claude Shannon’s information theory that was originally proposed in 1948. Consequently, by calculating the parameters of the new prognostic model, we will be able to determine the magnitude of the chaotic factor, the degree of our knowledge, the complex probability, the self-information functions, the message entropies, and the channel capacities in the probability sets $ \sc{R} $ and $ \sc{{M}} $ and $ \sc{C} $ and which are all functions of the message real probability subject to chaos and random effects.

We introduce a method for measuring the number and durations of processing stages from the electroencephalographic signal and apply it to the study of associative recognition. Using an extension of past research that combines multivariate pattern analysis with hidden semi-Markov models, the approach identifies on a trial-by-trial basis where brief sinusoidal peaks (called bumps) are added to the ongoing electroencephalographic signal. We propose that these bumps mark the onset of critical cognitive stages in processing. The results of the analysis can be used to guide the development of detailed process models. Applied to the associative recognition task, the hidden semi-Markov models multivariate pattern analysis method indicates that the effects of associative strength and probe type are localized to a memory retrieval stage and a decision stage. This is in line with a previously developed the adaptive control of thought-rational process model, called ACT-R, of the task. As a test of the generalization of our method we also apply it to a data set on the Sternberg working memory task collected by Jacobs, Hwang, Curran, and Kahana (2006). The analysis generalizes robustly, and localizes the typical set size effect in a late comparison/decision stage. In addition to providing information about the number and durations of stages in associative recognition, our analysis sheds light on the event-related potential components implicated in the study of recognition memory. (PsycINFO Database Record

This paper presents a new methodology for hyperspectral image classification based on the definition of typical sets from the Asymptotic Equipartition Property, an important tool in the field of information theory. The Endmembers (EM) are decomposed in orthogonal functions by a discrete wavelet transform and are modeled as a HMM (Hidden Markov Model). Based on this model, for each EM, a Typical Sequence set is established. One spectrum is classified as a member of a specific EM if belongs to its typical set. It is considered the case in which a class in the hyperspectral image can be represented by several subclasses and also the original spectra can be decimated and be used with less bands in the classification processes. The proposed method is tested with a set of AVIRIS data and is compared with the classification performed by Euclidian Distance, Spectral Angle Mapper (SAM) and Spectral Information Divergence (SID). It is shown that the proposed classification can be used with a reduced number of bands and achieves results comparable with other methods using all bands.

The main aim of this paper is to present results of a full-scale pushover test of a 40 meter telecommunication tower under breaking load. A detailed description of the studied tower has been presented with emphasis on the geometrical imperfections of the selected members of the structure. The results of the experiment consisting of the axial forces in the tower's members, as well as the displacements of the observed nodes as a function of external load have been presented. A comparison of a wind load based on the current standards with the load based on the experimental breaking force has been discussed for a typical set of telecommunication equipment. The main conclusion was that the structure's overall carrying capacity depended on the buckling resistance of the legs. Additionally, theoretical buckling resistances (based on standards) of the tower's legs made with round solid bars were smaller than the experimental axial forces in compression.

In this paper, a new and efficient hybrid AC/DC solar powered Homegrid model is proposed based on the load characteristics of a typical set of home appliances working on a 220 V, 50 Hz system. The load characteristics of home appliances are represented by a static ZIP (constant impedance (Z), constant current (I) and constant power (P)) coefficient model, a useful load model in power flow studies. A Homegrid system is formed by analysing the distortion produced by modern household equipment, and a K-factor with a significant role in the overheating of residential/distribution transformers is determined. Further, the ZIP load model is validated by a simulation and the results are compared with experimental data. To improve the efficiency and quality of the traditional Homegrid system, a solar powered hybrid AC/DC supply network model is proposed. This system eliminates redundant power conversion stages and mitigates the loss due to the harmonics by a shift of harmonic intensive loads to the Direct Current (DC) network side. Its effectiveness has been investigated with a simulation in MATLAB as well as with hardware implementation. This proposed energy efficient Homegrid model could be quite helpful in fulfilling the idea of net zero or surplus energy buildings.

Each solar powered device that is based on solar cells requires energy system, which contains typical set of subsystems which should be implemented in software and hardware to achieve efficient power management. This paper will structure general design of solar power system that could be modular and applied to many different types of devices and applications.

Redox-based resistive random access memories (ReRAM) are promising candidates for the use in ‘beyond-von Neumann’ architectures. One key issue for utilizing ReRAM for e.g. neuromorphic applications is a gradual SET and RESET behavior, allowing to write various resistance states emulating synaptic weights. However, a typical SET event for filamentary-like valence change mechanism devices is happening abrupt due to its physical principle. In this work we demonstrate a gradual SET behavior for $\text{HfO}_{2}/\text{TiO}_{\mathrm{x}}$ ReRAM cells in pulse mode. The results are discussed in view of the inherent properties of the particular bilayer structure.

Purpose – Value-at-risk (VaR) is a risk measure of potential loss on a specific portfolio. The main uses of VaR are in risk management and financial reporting. Researchers are continuously looking for new and efficient ways to evaluate VaR, and the 2008 financial crisis has given further impetus to finding new and reliable ways of evaluating and using VaR. In this study, the authors use genetic algorithm (GA) to evaluate VaR and compare the results with conventional VaR techniques. Design/methodology/approach – In essence, the authors propose two modifications to the standard GA: normalized population selection and strict population selection. For a typical set of simulation, eight chromosomes were used each with eight stored values, and the authors get eight values for VaR. Findings – The experiments using data from four different market indices show that by adjusting the volatility, the VaR computed using GA is more conservative as compared to those computed using Monte Carlo simulation. Research limitations/implications – The proposed methodology is designed for VaR computation only. This could be generalized for other applications. Practical implications – This is achieved with much less cost of computation, and hence, the proposed methodology could be a viable practical approach for computing VaR. Originality/value – The proposed methodology is simple and, at the same time, novel that could have far-reaching impact on practitioners.

Machining using industrial robots is currently limited to applications with low geometrical accuracies and soft materials. This paper analyzes the sources of errors in robotic machining and characterizes them in amplitude and frequency. Experiments under different conditions represent a typical set of industrial applications and allow a qualified evaluation. Based on this analysis, a modular approach is proposed to overcome these obstacles, applied both during program generation (offline) and execution (online). Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high-dynamic compensation mechanism on piezo-actuator basis.

Safety factors proposed in codes CEB, B.A.E.L 91 and EUROCODE 1 cover a great number of uncertainties; making them inadequate for the assessment of existing structures. Suitable safety factors are established using a probabilistic assessment, once real dimensions, materials strength and existing structures deterioration mechanisms are taken into account. This paper presents a calibration method for safety factors using a typical set of RC bridges in France. It considers the principal stages of corrosion provoked by CO2 and Cl− penetration and threshold indexes (B0) for existing structures. Reliability indexes are determined by the FORM method in the calibration method.

Efficiency maps have long been used by engineers to understand the topographical behavior of their machinery. Most commonly, efficiency maps have been generated for internal combustion engines, where the torque–speed curve for the engine shows the wide-open-throttle line with constant efficiency lines drawn beneath this maximum operating limit. From such maps, engineers have been able to determine the most efficiency operating point for the engine, given a desired output power (torque and speed). There currently exists a great interest in using hydrostatic transmissions for improving the operating efficiency of an internal combustion engine. However, efficiency maps for hydrostatic transmissions, similar to efficiency maps for internal combustion engines, do not exist in the literature and therefore it is difficult to assess the overall efficiency gains that are achieved when using a hydrostatic transmission in these applications. This paper proposes a method for generating efficiency maps for hydrostatic transmissions, and presents a typical set of maps that may be used as a first approximation for assessing transmission efficiency. The results of this paper are nondimensional and are generalized for a transmission of any size. As shown in this research, there are regimes of transmission operation in which the efficiency is nearly independent of either the output torque, or the output speed. Furthermore, it is shown that maximum operating efficiencies typically exist at high output speeds, and mid-to-high output torques.

Site response analysis, widely performed in practice to estimate seismic site effects, requires multiple inputs regarding the dynamic soil properties. While comprehensive site-specific field and laboratory tests need to be performed for the proper characterization of a site, engineers are often given only limited information and are forced to work with uncertainties. A round-robin test on site response analysis was performed in Korea to evaluate the dispersion of the calculated responses originating from the uncertainties in soil characterization and from the method of analysis. The participants were intentionally given limited information, which represented a typical set of inputs given in practice. The participants were asked to predict the dynamic properties based on the given data, and to perform a series of site response analyses. This paper documents the variations in the predicted dynamic properties and the computed responses. The results showed that the prediction of the shear wave velocity was most important for the evaluation of the ground-motion propagation, while the type of analysis had only a secondary influence. Important guidelines for the prediction of dynamic properties are also given.

Emotional cellular (EC), proposed in our previous works, is a kind of semantic cell that contains kernel and shell and the kernel is formalized by a triple-L = , wherePdenotes a typical set of positive examples relative to word-L,dis a pseudodistance measure on emotional two-dimensional space: valence-arousal, andδis a probability density function on positive real number field. The basic idea of EC model is to assume that the neighborhood radius of each semantic concept is uncertain, and this uncertainty will be measured by one-dimensional density functionδ. In this paper, product form features were evaluated by using ECs and to establish the product style database, fuzzy case based reasoning (FCBR) model under a defined similarity measurement based on fuzzy nearest neighbors (FNN) incorporating EC was applied to extract product styles. A mathematical formalized inference system for product style was also proposed, and it also includes uncertainty measurement tool emotional cellular. A case study of style acquisition of mobile phones illustrated the effectiveness of the proposed methodology.

In cognitive radio (CR) cooperative sensing schemes, wireless sensor nodes deployed in the network sense the licensed spectrum and send their local sensing decisions to a fusion center (FC) that makes a global decision on whether to allow the unlicensed user transmit on the licensed spectrum, based on a decision (fusion) rule. k-out-of-N is widely used in the literature owing to its practical simplicity. Regrettably, it exhibits a tradeoff between the achievable probabilities of false alarm and miss detection, which could have consequent effects on the performance of CR. In this paper, based on the notion of typical sequences, we propose a novel fusion rule in which the false alarm and miss detection probabilities can be simultaneously made as small as desired (asymptotically zero as the number of sensors goes to infinity).

Tensegrity structures have been intensively studied since they appeared in the 1950s. Their applications have been extended from architecture to other areas including aerospace structures, cell mechanics, and robotics. In this paper, an interesting characteristic, the so-called multistability, is reported. A detailed investigation on a multistable tensegrity structure whose basic stable configuration corresponds to the expanded octahedron tensegrity is presented. Using an evolutionary form-finding scheme, together with the dynamic relaxation method, two other self-equilibrated configurations with higher strain energies are found. The stabilities of these configurations are verified by a matrix analysis process. Then, an investigation on the actuations and the corresponding threshold energies triggering the transformations between the different configurations is carried out. A typical set of actuation loads and the corresponding threshold energies for the state transformations are identified. The existence...

A multivariate particle classification approach is proposed and applied to the analysis of the data from H.E.S.S. (High Energy Stereoscopic System). The combination of results from the three shower reconstruction methods: Hillas, model and 3D-model, leads to a substantial gain in the discrimination power between photons and hadrons. The construction and use of a combined effective estimator improves by several factors the signal-to-background ratio which is extremely important in case of studies of the faint and extended sources. The results of this approach are presented for a typical set of sources. The consequent gain in the sensitivity is shown through a comparison to the H.E.S.S. published results.

Many DSP applications such as FIR filtering and DCT (discrete cosine transformation) require multiplication with constants. Therefore, optimizing the performance of constant multiplication improves the overall performance of these applications. It is well-known that shifting can replace a constant multiplication if the constant is a power of two. In this paper, we extend this idea in such a way that by employing more than two barrel shifters, we can design highly efficient constant multipliers. We have found that by using two or three shifters, we can generate a large set of constants. Using these constants, we can execute a typical set of FIR or DCT applications with few errors. Furthermore, with variable precision support, we can carry out a fairly large class of DSP applications with high computational efficiency. Compared to conventional multipliers, we can achieve power savings of up to 56% with negligible computational errors.

Most of the fatal injuries and the loss of lives occur due to lack of timely and quick action to be taken by the vehicular drivers. The difficulty in determining the incidence of fatigue-related accidents is due to the difficulty in identifying fatigue as a causal or causative factor in accidents. In most instances, one or more indirect or circumstantial pieces of evidence are used to make the case that fatigue was a factor in the accidents. In this paper we propose an unconventional approach for fatigue detection in vehicular drivers using Oximetry Pulse (OP) signal to detect cognitive fatigue of the driver thereby reducing the loss of the lives and vehicular accidents. This method includes implementation of basic K-means and modified K-means for detection of fatigue state of drivers. Oximetry Pulse signal has been recorded from vehicular drivers for Pre and Post driving states and were processed using various wavelet functions to extract typical set of features. The K-means classifiers were trained and tested for these datasets. Each of the features extracted was treated as single decision making parameter. From the test results it could be found that some of the wavelet features could fetch 100 % classification accuracy with modified K-means while few others with basic K-means classifier.

A unique opportunity exists when an experimental NMR spectrum is obtained for which a specific chemical structure is anticipated. A process of Verification—the confirmation of a postulated structure—is now possible, as opposed to Elucidation—the de novo determination of a structure. A method for automated structure verification is suggested, which compares the chemical shifts, intensities and multiplicities of signals in an experimental 1H NMR spectrum with those from a predicted spectrum for the proposed structure. A match factor (MF) is produced and used to classify the spectrum-structure match into one of three categories, correct, ambiguous, or incorrect. The verification result is also augmented by the spectrum assignment obtained as part of the verification process. This method was tested on a set of synthetic spectra and several sets of experimental spectra, all of which were automatically prepared from raw data. Taking into account even the most problematic structures, with many labile protons present and poor prediction accuracy, 50% of all spectra can still be automatically verified without any false positives or negatives. In a blind test on a typical set of data, it is shown that fewer than 31% of the structures would need manual evaluation. This means that a system is possible whereby 69% of the spectra are prepared and evaluated automatically, and never need to be seen or evaluated by a human. Copyright © 2006 John Wiley & Sons, Ltd.

A performance assessment of corroded reinforced concrete (RC) structures requires an acute understanding of both material deterioration and its impact on structural behaviour, in order to evaluate its durability, safety, serviceability and remaining service life. The corrosion phenomenon is usually due to carbon dioxide and chloride ions. More generally, the environmental conditions may determine what kind of deterioration mechanism can produce structural degradation depending on relative humidity, temperature, severity of the surrounding environment, materials properties, etc. Consequently, the performance cycle prediction of reinforced concrete structures involves many factors, which introduce uncertainties. A probabilistic approach as opposed to a deterministic one is therefore more appropriate to generate reliable cycle predictions. This paper focuses on the application of the principles of such a probabilistic approach to calculate for a typical set of RC bridges in France, the critical times corresp...

In this paper the main performances of communication services based on low earth orbit satellites (LEOs) have been analyzed in order to evaluate their suitability for a typical set of power system monitoring functionalities. As an experimental test bed, an intelligent electronic device (IED) for remote monitoring and protection of power components equipped with a bi-directional communication system based on the LEO satellites of the Globalstar® consortium has been prototyped. Thanks to the adoption of this facility the main parameters characterizing the performance of the satellite TCP/IP services have been evaluated. They comprise in particular the connection time, the degradation of service and data latency for both packet and asynchronous data services. The experimental results obtained show that the application of LEO satellites based communication technologies exhibits a set of intrinsic advantages that could be particularly useful in several fields of power system communication.

Modern Science is finding new methods of looking at biological, physical or social phenomena. Traditional methods of quantification are no longer sufficient and new approaches are emerging. These approaches make it apparent that the phenomena the observer is looking at are not classifiable by conventional methods. These phenomena are complex. A complex system, as Chua's oscillator, is a nonlinear configuration whose dynamical behavior is chaotic. Chua's oscillator equations allow to define the basic behavior of a dynamical system and to detect the changes in the qualitative behavior of a system when bifurcation occurs, as parameters are varied. The typical set of behavior of a dynamical system can be detailed as equilibrium points, limit cycles, strange attractors. The concepts, methods and paradigms of Dynamical Systems Theory can be applied to understand human behavior. Human behavior is emergent and behavior patterns emerge thanks to the way the parts or the processes are coordinated among themselves. In fact, the listening process in humans is complex and it develops over time as well. Sound and music can be both inside and outside humans. This tutorial concerns the translation of Chua's oscillators into music, in order to find a new way of understanding complexity by using music. By building up many computational models which allow the translation of some quantitative features of Chua's oscillator into sound and music, we have created many acoustical and musical compositions, which in turn present the characteristics of dynamical systems from a perceptual point of view. We have found interesting relationships between dynamical systems behavior and their musical translation since, in the process of listening, human subjects perceive many of the structures as possible to perceive in the behavior of Chua's oscillator. In other words, human cognitive abilities can analyze the large and complicated patterns produced by Chua's systems translated into music, achieving the cognitive economy and the coordination and synthesis of countless data at our disposal that occur in the perception of dynamic events in the real world. Music can be considered the semantics of dynamical systems, which gives us a powerful method for interpreting complexity.

SYNOPSIS The thermo-economic function, defined as the total cost of the engine system per unit power output of an irreversible Carnot heat engine cycle, is studied in detail. The objective function is optimised with respect to the temperature ratio of the working substance in the two isothermal processes and the optimum operation parameters are calculated for a typical set of operating conditions. It is found that there are the optimal values of the temperature ratio of the working substance in the two isothermal processes and the thermal efficiency of the cycle at which the objective function has a minimum. The maximum power output associated with thermo-economic performance and the corresponding parameters are also derived for a typical set of operating parameters. The influence of different parameters on the performance of the system is discussed in detail. It is important that some significant results obtained by earlier workers can be directly derived as special cases of the present paper.

Consider the situation where a word is chosen probabilistically from a finite list. If an attacker knows the list and can inquire about each word in turn, then selecting the word via the uniform distribution maximizes the attacker's difficulty, its Guesswork, in identifying the chosen word. It is tempting to use this property in cryptanalysis of computationally secure ciphers by assuming coded words are drawn from a source's typical set and so, for all intents and purposes, uniformly distributed within it. By applying recent results on Guesswork, for i.i.d. sources it is this equipartition ansatz that we investigate here. In particular, we demonstrate that the expected Guesswork for a source conditioned to create words in the typical set grows, with word length, at a lower exponential rate than that of the uniform approximation, suggesting use of the approximation is ill-advised., Comment: ISIT 2013, with extended proof

Higher education institutions (HEI) and students are highly dependent of information systems, implemented as web applications. Students must be able to access this applications, thought accessible web interfaces, in order to perform their academic activities. This paper presents an overview of a typical set of web applications used by students and the main concerns regarding accessibility compliance. The analysis was conducted using the systems at the University of Tras-os-Montes e Alto Douro.

Metabolism has been identified as a defining factor in drug development success or failure because of its impact on many aspects of drug pharmacology, including bioavailability, half-life and toxicity. In this article, we provide an outline and descriptions of the resources for metabolism-related property predictions that are currently either freely or commercially available to the public. These resources include databases with data on, and software for prediction of, several end points: metabolite formation, sites of metabolic transformation, binding to metabolizing enzymes and metabolic stability. We attempt to place each tool in historical context and describe, wherever possible, the data it was based on. For predictions of interactions with metabolizing enzymes, we show a typical set of results for a small test set of compounds. Our aim is to give a clear overview of the areas and aspects of metabolism prediction in which the currently available resources are useful and accurate, and the areas in which they are inadequate or missing entirely.

Since the radius of curvature of a mirror cannot be zero, the apodization that is created by a phase-induced amplitude apodizer (PIAA) formed by a pair of mirrors cannot be zero at the edge of the pupil. If contrasts lower than 10 -10 must be obtained, then an additional apodizer must be used with the PIAA mirrors. This has a consequence on the throughput of the system, as well as on its inner working angle (IWA). The intensity distribution in the final pupil plane computed in the ray-optics approximation is misleading, and diffraction must be taken into account to evaluate the true performance of the system. We compute the propagated electric field using two different tools: the semi-analytical model developed by Pueyo and a purely numerical model based on the Huygens integral. It is shown that for higher Fresnel numbers, the agreement between the beams computed using both propagators is stronger, and that for too low Fresnel numbers, the contrast computed using the semi-analytical model can be 2 orders of magnitude higher than the one computed by a numerical evaluation of the Huygens integral. We then study the impact of surface aberrations introduced on the mirrors of the PIAA. The surface quality of the mirrors limits the performance of the system, and the IWA increases linearly with the root-mean-square (RMS) of the aberrations. For a typical set of mirrors, errors of 10nm RMS can increase the IWA by 0.5 to 1λ/D for a contrast of 10 -10 , and, in the case of a contrast of 10 -8 , the IWA is maintained to 2 λ/D as long as the errors are smaller than 20nm RMS.

Set size and crowding affect search efficiency by limiting attention for recognition and attention against competition; however, these factors can be difficult to quantify in complex search tasks. The current experiments use a quantitative measure of the amount and variability of visual information (i.e., clutter) in highly complex stimuli (i.e., digital aeronautical charts) to examine limits of attention in visual search. Undergraduates at a large southern university searched for a target among 4, 8, or 16 distractors in charts with high, medium, or low global clutter. The target was in a high or low local-clutter region of the chart. In Experiment 1, reaction time increased as global clutter increased, particularly when the target was in a high local-clutter region. However, there was no effect of distractor set size, supporting the notion that global clutter is a better measure of attention against competition in complex visual search tasks. As a control, Experiment 2 demonstrated that increasing the number of distractors leads to a typical set size effect when there is no additional clutter (i.e., no chart). In Experiment 3, the effects of global and local clutter were minimized when the target was highly salient. When the target was nonsalient, more fixations were observed in high global clutter charts, indicating that the number of elements competing with the target for attention was also high. The results suggest design techniques that could improve pilots' search performance in aeronautical charts. (PsycINFO Database Record (c) 2010 APA, all rights reserved). Language: en

In Dempster-Shafer Theory (DST) of evidenceeand transferable belief model (TBM), the probability transformation is necessary and crucial fordecision-making. The evaluation of the quality of the probability transformation is usually based on the entropyor the probabilistic information content (PIC) measures, which are questioned in this paper. Anotheralternative of probability transformation approach is proposed based on the uncertainty minimization to verifythe rationality of the entropy or PIC as the evaluationcriteria for the probability transformation. Accordingto the experimental results based on the comparisonsamong different probability transformation approaches,the rationality of using entropy or Probabilistic InformationContent (PIC) measures to evaluate probabilitytransformation approaches is analyzed and discussed.&nbsp

Marechal’s treatment of tolerance theory shows that in designing high quality systems one should aim at minimizing the variance E of the wave aberration. Since the value of E is essentially positive, a useful criterion for the whole field is the sum of the suitably weighted values of E for a typical set of image points. It is shown here that the variance E (for both the axial and extraaxial images) may be calculated very simply by means of a set of universal coefficients [P(i,j), Q(i,j), and R(i,j)] once the wave aberrations of selected rays are known. The values of these coefficients are uniquely determined by the form of polynomial assumed for the wave aberration and by the pattern of rays traced. Tables of P(i,j), Q(i,j), and R(i,j) are presented for the different cases that can arise in practice.

Hopkins' treatment of tolerance theory shows that, in designing quality optical systems, we should aim at minimizing the variance K of the wave-aberration difference function. Since the value of K is essentially positive, a useful criterion for the whole field is the sum of the suitably weighted values of K for a typical set of image points, corresponding to a range of selected values of spatial frequencies s and azimuths psi. In this paper we show that the variance K (for both the axial and the extraaxial images) may be calculated by means of a set of universal coefficients P(i,j;s), Q(i,j;spsi) and R(i,j;spsi) once the wave-aberrations of certain rays are known. The values of these coefficients are uniquely determined by the function of the wave-aberration polynomial assumed and by the-pattern of rays traced. Examples of the coefficients are presented.

The cornerstone of a Smart Grid is the ability for multiple entities to interact via communication networks. A scalable and pervasive communication infrastructure represents a crucial issue in both structuring and operating smart networks. In addressing this problem this paper figures out the potential role of cooperative Wireless Sensor Networks (WSNs). In detail, it analyses the performance of IEEE 802.15.4 based WSNs in order to establish their suitability for a typical set of monitoring and supervision functionalities required by urban-scale Smart Grids applications. The results obtained show that the application of this technology may be very promising in several Smart Grids applications as far as automation, remote monitoring and supervision are concerned.

A scalable and pervasive communication infrastructure represents a crucial issue in both structuring and operating modern power systems. In addressing this problem, this paper evaluates the potential role of cooperative wireless sensor networks. In order to establish their suitability for a typical set of monitoring and supervision functionalities required by Wide Area Monitoring Systems, the performance of IEEE 802.15.4 Standard based sensor networks are analysed in detail. The results obtained show that the application of this technology may be very promising in several power systems applications as far as distribution automation, remote monitoring, supervision, protection and control are concerned. (5 pages)

Low cost, miniaturized, commercial-off-the-shelf (COTS) motion sensors, collectively with processors, an energy source and other electronic circuitry can be packaged into very small volumes for autonomous operation. If such a system operates over short periods of time, or data acquisitions occur at a very low frequency, processor resources should be sufficient to manage offsets and errors. The paper analyzes a typical set of COTS accelerometers and gyroscopes, to indicate how best these can be used in hydraulic environments. Application examples such as river bed sediment monitoring, milk vat monitoring etc. are briefly discussed, with application oriented design approaches. Minimizing the power consumption to introduce a novel, rechargeable power supply design is briefly outlined.

Some certain chanciness existed in the coal accidents can result in the gas explosion. In this paper, brittle theory and entropy theory are suggested, and the brittle risk entropy function is deduced through the probability of the accident occurrence, grave consequence of system collapse, and uncontrollable degree of factors; meanwhile, characters of risk entropy function are discussed. According to the property of entropy, we have the control strategy. And we define the module of factors, according to the module magnitude of factor, we choose the factor to eliminate. Finally, the probability entropy function is taken as example, and the entropy value of accident system is controlled successfully according to the controlled strategy.

In recent studies, a new class of planar and spatial linkage mechanisms was presented in which for a continuous full rotation or continuous rocking motion of the input link, the output link undergoes two continuous rocking motions. Such linkage mechanisms were referred to as the “motion-doubling” linkage mechanisms. This class of mechanisms was also shown to generally have dynamics advantage over regular mechanisms designed to achieve similar gross output motions. In a recent study, the application of such motion-doubling linkage mechanisms to vehicle suspension system was investigated. In the present study, the performance of a vehicle using such a suspension system is compared to a suspension system regularly used in vehicles. For a typical set of vehicle and tire parameters, the parameters of both suspension systems are optimally determined with a commonly used objective function. The performance of the two systems in the presence of various input disturbances is then determined using computer simulation. It is shown that suspension systems constructed with motion-doubling linkage mechanisms can provide a significantly superior performance as compared to a commonly used suspension system.Copyright © 2007 by ASME

Shape from shading (SFS) is a classic problem in computer vision, which aims to infer the shape of an object from its shading information in a single image. Since this problem is ill-posed, a number of assumptions have been used extensively in the computer vision community for the SFS problem, such as orthographic projection, Lambertian reflectance model, single light source, and constant surface albedo. In this paper, starting with this typical set of assumptions, we derive new image intrinsic values based on image shading information. We validated the obtained intrinsic values on hundreds of real and synthetic images. Furthermore, we study the effect of intensity and geometric non-linearities (e.g., gamma correction and lens distortion) on the derived image intrinsics. One important application of this study is the possibility of using the image intrinsics to undo some effects of these non-linearities or to correct input images in order to obtain better SFS results.

The author applies pattern matching results to three problems in information theory. The characterisation of a probability law is also discussed. >

The author suggests that in any product area there will be a continuum of potential architectures ranging from ones which are highly random and interdependent to those characterized by distinct functional modules, joined together in noncomplex ways. A typical set of architectures common in the electronic industries is posited. Each of these architectures is discussed from the point of view of appropriability by competitors, cost, speed to market, and the ability to evolve in response to various types of technological change. The impact of typical contractual restraints associated with acquired technologies is then examined in relation to these architectures. It is suggested that architectural choices should be based on an assessment of all the foregoing factors, including the ability of the chosen architecture to accommodate acquired technologies and the disabilities associated with them. >

A self-tuning control algorithm incorporating a variable forgetting factor has been utilized to control a rolling mill DC drive. The performance index of the control algorithm incorporates system input, output, and set-point variations. Four-quadrant operation of the drive is required for the operation of the rolling mill drive. An inner current loop is required for the operation of the rolling mill drive. The inner current loop is equipped with a PI controller, and the outer speed loop has the proposed self-tuning controller. Digital simulation results reveal that the proposed adaptive control algorithm is able to follow the typical set-point variations required for a rolling mill in conjunction with torque variations on the shaft of the drive. >

This paper describes a new approach to modelling robot systems by a large number of cooperating agents solving a robot task. On the one hand the agent model submits to use results of the distributed artificial intelligence (DAI), on the other hand, typical aspects of robot systems must be integrated. Therefore, an agent model will be presented serving the special requirements of robot systems and offering many advantages like robustness, high efficiency, and the chance of integrating reactive and deliberative behavior. The agent model also enables the use of different programming paradigms, ranging from complex over hierarchical to object-oriented agents. Finally, a typical set of agents is presented, forming a multi-layered, distributed and reactive (MDR) robot task-level transformer.

This paper investigates the identification of mechanisms of disc brake squeal by the application of a recently developed Empirical Mode Decomposition method (EMD). A known strength of the EMD is its adaptive nature in analyzing nonstationary data, with success in its original application to ocean mechanics. The EMD decomposes an original signal into a number of intrinsic mode functions (IMFs), with each IMF often containing distinct physical significance. Several sets of disc brake squeal data were obtained and processed by EMD. A typical set data is presented in this paper for discussion. Employing a sifting process in the EMD, four prominent squeal-related IMFs are identified in this set of data. The Hilbert transform is then used to analyze the frequency and amplitude contents of the four IMFs, and it is shown that the first IMF is dominant. The spectrogram method is applied to analyze the time-evolution of the frequency components of the IMFs in the squeal process. This analysis procedure confirms an important squeal mechanism, i.e., the squeal condition is governed by the coupling of in-plane and out-of-plane vibration modes of the rotor and the coalescence of their natural frequencies. The inverse approach outlined in this paper is shown to be useful for providing new insights and confirming established hypotheses of disc brake squeal.Copyright © 2002 by ASME

Computer study of population evolution in a modified Penna model is presented. We introduced biological time scale for which time runs faster for younger individuals than for the old ones. Such mechanism is likely to be present in real organisms. Results of computer simulation are compared with the classical Penna model which accounts for genetic death caused by too many 'bad' mutations m, and with the simplest logistic model approach which ignores genetic death and accounts only for elimination due to limited environmental capacity. The first conclusion is that the partial distribution function p(m) of 'bad' mutations m in the population for groups of same age a, is different from the standard Penna model and shows a clear tendency that young population becomes healthier, that is with smaller portion of youngsters with many bad mutations. This effect is less pronounced for older individuals. It may be statistically significant to be observed in real populations. The second important conclusion is that scaling does not hold when we repeat calculations on machine of different number of bits per word, and/or when we code genomes on different number of words. This is a direct consequence of the fact that operations setting up for one evolution cycle do not commute in the limit of discrete age representation. For typical set of model parameters, calculations on population of order of one million items requires about 100MB memory and execution takes couple of hours for 2 or 3thousand iterations on HP S2000 machine.

An increasing number of applications of Artificial Neural Networks (ANN) in the field of Management Science demonstrates the growing relevance of modeling techniques summarized under this headline. This situation is also reflected in marketing where several papers published within the last few years have focused on ANN. To evaluate its potentials for market segmentation and consumer profiling a comparison of different approaches including connectionistic and traditional models will be performed by several independent experiments for a typical set of marketing data.

This paper describes an ongoing effort to verify the cache coherence protocol of the IEEE/ANSI Standard for Scalable Coherent Interface using the Murϕ verification system. A model of the typical set protocol was constructed in the Murϕ description language. This model was augmented with a specification of properties necessary for cache coherence. The Murϕ verification system automatically checks if all reachable states in the model satisfy the given specification. Although verification is still under way, we have already found several errors in the C-code defining the protocol. Finally, we elucidate the experiences gained in the verification project.