Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative geography : perspectives on spatial data analysis by

The authors of this text are at the vanguard of progress in quantitative human geography. Their work provides a welcome and refreshing insight into current research. The authors, and their publishers, are to be congratulated on the high quality of this publication: both in terms of textual layout, and the quality of the figures. The book is organised into 10 chapters, of which the first and last are contextual rather than technical. Chapters 2, 3, and 4 cover basic concepts of spatial data, GIS, and visual representation. There are then major contributions on local analysis techniques, point pattern analysis, spatial regression and geostatistical models, statistical inference of spatial data, and the relationship between spatial modelling and the evolution of spatial theory. In the preface and the first chapter, the authors provide a powerful defence of the importance of quantitative geography and lose no time (page 2! ) in suggesting that many of the critics of quantitative approaches are not writing from an informed perspective. Other critics may have moved away from the limitations of quantitative approaches that are now several decades old, and the authors hope to persuade them that substantial developments in theory, technique, and application are worthy of a new evaluation. Having injected some considerable vitality into the work, chapters 2 and 3 are, although perfectly competent, a little pedestrian and revisit some themes that a cynical reader would immediately identify as`traditional'. I think I might have been tempted to hide map projections , for example, somewhere in an appendix. However, it is reassuring to see a pragmatic approach to GIS. One of the unfortunate spin-offs of the widespread availability of desktop systems to the untrained user is a growth in inappropriate application, and in fundamental errors. Chapter 4 eventually gathers pace, inducing guilt in all those, like myself, who are often content to use a basic choropleth map. There was scope here to stimulate the reader a little more with some colourful multimedia dynamic approaches. Chapters 5 ^ 9 are comprehensive coverages of the bodies of work produced by the authors over the last few years. Geographically weighted regression is now well developed, and the comparison between this and the spatial expansion method is particularly instructive. It is encouraging to note the maintenance of a website on this work, and perhaps more such references could have been included (for example, to the work at the Centre for Computational …
Stop identity cue as a cue to language identity

STOP IDENTITY CUE AS A CUE TO LANGUAGE IDENTITY by PAULA LISA CASTONGUAY December 2016 Advisors: Dr. Geoffrey Nathan and Dr. Derek Daniels Major: Communication Sciences & Disorders (Cognitive Linguistics) Degree: Doctor of Philosophy The purpose of the present study was to determine whether language membership could potentially be cued by the acoustic-phonetic detail of word-initial stops and retained all the way through the process of lexical access to aid in language identification. Of particular interest were language-specific differences in CE and CF word-initial stops. Experiment 1 consisted of an interlingual homophone production task. The purpose of this study was to examine how word-initial stop consonants differ in terms of acoustic properties in Canadian English (CE) and Canadian French (CF) interlingual homophones. The analyses from the bilingual speakers in Experiment 1 indicate that bilinguals do produce language-specific differences in CE and CF wordinitial stops, and that closure duration, voice onset time, and burst spectral SD may provide cues to language identity in CE and CF stops. Experiment 2 consisted of a Phoneme and Language Categorization task. The purpose of this study was to examine how stop identity cues, such as VOT and closure duration, influence a listener to identify word-initial stop consonants as belonging to Canadian English (CE) or Canadian French
Notice of RetractionFormal Analysis for Cipher Chip's Security against Template Attack

In order to evaluate the security of cipher chips against template attack, the adversary's ability is defined combing the notion of equivalence relations and partitions after analyzing the character of key space partition in template matching phase, The distinguishing ability of a template attacking adversary is evaluated qualitatively and quantificationally with the indistinguishable of secret information and the remaining uncertainty of the secret information after template attack separately. The case analysis on RC4 cipher chip confirms the validity of this formal method.
Relationship between macroscopic physical properties and local distortions of low-doping La 1 − x Ca x MnO 3 : An EXAFS study

A temperature-dependent extended x-ray-absorption fine structure investigation of La1xCaxMnO3 is presented for the concentration range that spans the ferromagnetic-insulator FMI to ferromagnetic-metal FMM transition region, x=0.16, 0.18, 0.20, and 0.22; the titrated hole concentrations are slightly higher, y=0.2, 0.22, 0.24, and 0.25, respectively. For this range of Ca concentrations the samples are insulating for x=0.16‐0.2 and show a metal/insulator M /I transition for x=0.22. All samples are ferromagnetic although the saturation magnetization for the 16% Ca sample is only 70% of the expected value at 0.4 T. This raises a question as to the nature of the ferromagnetic coupling mechanism in such insulating samples. We find that the FMI samples have similar correlations between changes in the local Mn-O distortions and the magnetization as observed previously for the colossal magnetoresistance CMR samples 0.2x0. 5—except that the FMI samples never become fully magnetized. The data show that there are at least two distinct types of distortions. The initial distortions removed as the insulating sample becomes magnetized are small and provide direct evidence that roughly 50% of the Mn sites associated with the hole charge carriers have a small average distortion/site and are magnetized first. The large Mn-O distortions that remain at low T are attributed to a small fraction 30% of fully Jahn-Teller-distorted Mn sites that are either unmagnetized or antiferromagnetically ordered. Thus the insulating samples are very similar to the behavior of the CMR samples up to the point at which the M /I transition occurs for the CMR materials. The lack of metallic conductivity for x 0.2, when 50% or more of the sample is magnetic, implies that there must be preferred magnetized Mn sites that involve holes and that such sites do not percolate at these concentrations.
Feature Selection in Tumor Classification Using Microarray Gene Expression Data

Feature selection is the process of choosing a subset of the original predictive variables through the elimination of redundant and uninformative representatives. An example of importance is the analysis of gene expression data from DNA microarray hybridization experiments. The data obtained from the experiments usually contain a few samples each with expression levels of a large number of genes . We propose a procedure for feature selection based on a voting scheme through the solution of a sequence of linear programs. This method has been tested on the classification of human tumor samples from two microarray data sets. The comparison of these findings with the results generated by Partial Least Squares, Principal Component Analysis, and Fisher’s score rule show that the new method has a lower rate of misclassification in the leave-one-out cross validation.
A local dormancy cline is related to the seed maturation environment, population genetic composition and climate.

BACKGROUND AND AIMS Seed dormancy varies within species in response to climate, both in the long term (through ecotypes or clines) and in the short term (through the influence of the seed maturation environment). Disentangling both processes is crucial to understand plant adaptation to environmental changes. In this study, the local patterns of seed dormancy were investigated in a narrow endemic species, Centaurium somedanum, in order to determine the influence of the seed maturation environment, population genetic composition and climate. METHODS Laboratory germination experiments were performed to measure dormancy in (1) seeds collected from different wild populations along a local altitudinal gradient and (2) seeds of a subsequent generation produced in a common garden. The genetic composition of the original populations was characterized using intersimple sequence repeat (ISSR) PCR and principal co-ordinate analysis (PCoA), and its correlation with the dormancy patterns of both generations was analysed. The effect of the local climate on dormancy was also modelled. KEY RESULTS An altitudinal dormancy cline was found in the wild populations, which was maintained by the plants grown in the common garden. However, seeds from the common garden responded better to stratification, and their release from dormancy was more intense. The patterns of dormancy variation were correlated with genetic composition, whereas lower temperature and summer precipitation at the population sites predicted higher dormancy in the seeds of both generations. CONCLUSIONS The dormancy cline in C. somedanum is related to a local climatic gradient and also corresponds to genetic differentiation among populations. This cline is further affected by the weather conditions during seed maturation, which influence the receptiveness to dormancy-breaking factors. These results show that dormancy is influenced by both long-and short-term climatic variation. Such processes at such a reduced spatial scale highlight the potential of plants to adapt to fast environmental changes.
Recognition of Non-Harmonic Natural Sounds by Small Mammals Using Competitive Training

Animals recognize biologically relevant sounds, such as the non-harmonic sounds made by some predators, and respond with adaptive behaviors, such as escaping. To clarify which acoustic parameters are used for identifying non-harmonic, noise-like, broadband sounds, guinea pigs were conditioned to a natural target sound by introducing a novel training procedure in which 2 or 3 guinea pigs in a group competed for food. A set of distinct behavioral reactions was reliably induced almost exclusively to the target sound in a 2-week operant training. When fully conditioned, individual animals were separately tested for recognition of a set of target-like sounds that had been modified from the target sound, with spectral ranges eliminated or with fine or coarse temporal structures altered. The results show that guinea pigs are able to identify the noise-like non-harmonic natural sounds by relying on gross spectral compositions and/or fine temporal structures, just as birds are thought to do in the recognition of harmonic birdsongs. These findings are discussed with regard to similarities and dissimilarities to harmonic sound recognition. The results suggest that similar but not identical processing that requires different time scales might be used to recognize harmonic and non-harmonic sounds, at least in small mammals.
Forecasting the Price of Energy in Spain's Electricity Production Market

In this job, short-term forecasts are calculated for the Energy Price in the Electricity Production Market of Spain. The methodology used to achieve these forecasts is based on Artificial Neural Networks, which have been used succesfully in recent years in many forecasting applications. To gauge the quality of forecasts, they have been compared with those obtained with the Box-Jenkins ARIMA models, another well-known forecasting methodology. Energy Price time series are usually composed of too many data, which can be a problem if we are looking for a short period of time to reach an adequate forecast. In this job, a training method for Neural Nets is proposed, which is based on making a previous selection for the Multilayer Perceptron (MLP) training samples, using an ART-type neural network. The MLP is then trained and finally used to calculate forecasts.
Secure and Ef icient Iris and Fingerprint Identi ication

Advances in biometric recogni on and the increasing use of biometric data prompt significant privacy challenges associated with the possible misuse, loss, or the of biometric data. Biometric comparisons are o en performed by two mutually distrus ul par es, one of which holds a biometric sample while the other owns a possibly large collec on of biometric data. Due to privacy and liability considera ons, neither party is willing to share its data. This gives rise to the need to u lize secure computa on techniques over biometric data where no informa on is revealed to the par es except the outcome of the comparison or search for iden fica on purposes. In this chapter, we present the design, security analysis, and performance of privacy-preserving iden fica on protocols for iris codes and fingerprints. Combined with certain op miza ons, such techniques are suitable for prac cal use on large data sets. Index Terms Privacy-Preserving Protocols, Biometric Iden fica on, Secure Mul party Computa on, Iris, Fingerprints
Global geometry of the supersymmetric AdS 3 /CFT 2 correspondence in M-theory

We study the global geometry of a general class of spacetimes of relevance to the supersymmetric three-dimensional anti-de Sitter space/two-dimensional conformal field theory (AdS{sub 3}/CFT{sub 2}) correspondence in 11-dimensional supergravity. Specifically, we study spacetimes admitting a globally defined R{sup 1,1} frame, a globally defined frame bundle with structure group contained in Spin(7), and an AdS{sub 3} event horizon or conformal boundary. We show how the global frame bundle may be canonically realized by globally defined null sections of the spin bundle, which we use to truncate 11-dimensional supergravity to a gravitational theory of a frame with structure group Spin(7), SU(4), or Sp(2). By imposing an AdS{sub 3} boundary condition on the truncated supergravity equations, we define the geometry of all AdS{sub 3} horizons or boundaries which can be obtained from solutions of these truncations. In the most generic case we study, we reproduce the most general conditions for an AdS{sub 3} manifold in M-theory to admit a Killing spinor. As a consistency check on our definitions of AdS geometries we verify that they are satisfied by known gauged supergravity AdS{sub 3} solutions. We discuss future applications of our results.
STRUCTURE OF TYPE 5 ADENOVIRUS

Type 5 adenovirus was purified by fluorocarbon (freon 113) treatment followed by banding in a CsCl equilibrium density gradient. This method permitted separation of virus from normal host cell materials and virus-specific soluble antigens. Virus banded in CsCl with a mean bouyant density of 1.3349 gm/cm3. The three virus-specific soluble antigens (group- and type-specific antigens and toxin) banded together with a mean bouyant density of 1.2832 gm/cm3. The group-specific antigen was the predominant antigen of the purified virus particle, whereas the group- and type-specific antigens were present in equal titers in the antigen band. Infectious virus particles were inactivated by prolonged dialysis at pH 10.5. Centrifugation of inactivated virus preparations in a CsCl equilibrium density gradient resulted in separation of virus DNA from specific antigen: the antigens banded with a mean bouyant density of 1.2832 gm/cm3 and the DNA sedimented to the bottom of the tube. The predominant antigen derived from purified virus particles was the group-specific antigen and it was in the same relative proportion to the type-specific antigen as measured in intact particles. The antigens derived from disrupted virus were immunologically identical with the soluble virus antigens present in infected cells.
Convergence Analysis of ADMM for a Family of Nonconvex Problems

In this paper, we analyze the behavior of the well-known alte rnating direction method of multipliers (ADMM), for solving a family of noncon vex problems. Our focus is given to the well-known consensusandsharingproblems, both of which have wide applications in machine learning. We show th at in the presence of nonconvex objective, the classical ADMM is able to reach t he set of stationary solutions for these problems, if the stepsize is chosen larg e enough. An interesting consequence of our analysis is that the ADMM is convergen t for a family of sharing problems, regardless of the number of blocks or the c onvexity of the objective function. Our analysis can be generalized to allow p roximal update rules as well as other flexible block selection rules far beyond the tr aditional Gauss-Seidel rule.
Fertility after intrauterine insemination with conventional or low numbers of spermatozoa in sows with synchronized ovulation

Materials and methods: A total of 411 mixed-parity sows were subjected to controlled ovulation by injection of 600 IU equine chorionic gonadotrophin at weaning and 5 mg porcine luteinizing hormone (pLH) 80 hours later. Sows were assigned to a single insemination of 1 or 3 × 109 sperm delivered into either the cervix or uterus. Inseminations were performed approximately 36 hours after pLH injection. Intensity of standing estrus at insemination was subjectively scored as 1 to 3, with 3 being a stronger response, and semen backflow was recorded as yes or no.
Estimating the primary user location and transmit power in cognitive radio systems using extended Kalman filters

In cognitive radio systems, the primary user location and transmit power are valuable information in order to create an efficient secondary network that uses spatial spectrum holes without introducing interference to the primary users. Since primary users cannot be assumed to cooperate, their locations and transmit powers need to be estimated at the secondary users. Existing localization techniques, based on the received signal strength require a high amount of secondary users in order to achieve a high accuracy while direction of arrival based methods alone suffer from the random secondary user positions and the requirements for making the associated devices portable. In this paper we propose a hybrid solution using an extended Kalman filter that is able to localize a moving primary user and estimate its transmit power under the aforementioned conditions. Its performance is compared to an extended Kalman filter that uses only direction of arrival estimation by means of Monte Carlo simulations, and shown to clearly outperform the DOA-only based processing.
Machine Learning Techniques for Intrusion Detection

An Intrusion Detection System (IDS) is a software that monitors a single or a network of computers for malicious activities (attacks) that are aimed at stealing or censoring information or corrupting network protocols. Most techniques used in today's IDS are not able to deal with the dynamic and complex nature of cyber attacks on computer networks. Hence, efficient adaptive methods like various techniques of machine learning can result in higher detection rates, lower false alarm rates and reasonable computation and communication costs. In this paper, we study several such schemes and compare their performance. We divide the schemes into methods based on classical artificial intelligence (AI) and methods based on computational intelligence (CI). We explain how various characteristics of CI techniques can be used to build efficient IDS.
Indoor location recognition system using environmental sensors

In this paper, we present an indoor location recognition system using environmental sensors. The system gathers the environmental data and extracts the feature data from them. It also recognizes and classifies the current location information of the user. We describe the configuration of the sensor module used for location recognition, and present a recognition system that is designed and implemented to recognize the location based on data from the sensor signals, and describe the pertinent aspects of our experimental results.
European Conference on Information Systems ( ECIS ) 2007 On the Role of Conceptual Models in Information Systems Research-From Engineering to Research

Conceptual modelling deals with the process of building or interpreting a conceptual model. Stakeholders use the resulting model to reason and communicate about a domain in order to improve their common understanding of it. From this perspective, conceptual modelling and conceptual models are subjects for information systems research. In this paper, we argue that this engineering-driven view on conceptual models is only one possible perspective for information systems research. Based on language critique, we show how conceptual models can be used not as a subject of but as an important and useful instrument for information systems research. Conceptual models help to structure and formalize the interpretation of a subjective understanding in a domain of focus. We propose a research approach which is based on three roles that the researcher adopts and show how conceptual models are a useful source of knowledge and an instrument for interpretation respectively. We combine our view with an existing framework for information systems research and reinterpret existing research as matching to our approach.
Controllers for voltage source converters

The power system is dependent on control of power and voltage for its stability and reliability. Voltage Source Converter (VSC) technology has the advantage of being able to almost instantly change its working point within its capability limit. Due to this advantage, VSC can be used to support the system to maintain active power or output voltage constant during load variation. To achieve this, Proportional Integral (PI) controllers are used for its simplicity and robustness. In this paper mathematical model for Voltage Source Converter is developed. PI based controllers are developed for constant DC voltage as well as constant DC power for load variation. In addition to analysis of the mathematical model of the VSC, the controller performance analysis is also carried out for Two and Three level converter. The results are compared in terms of the THD and the controller parameters. Simulation is carried out in MATLAB/SIMULINK environment.
Attachment Theory and Group Therapy

The ways we interact with other people, how we view their needs, wishes, and emotions, and how we deal with our own needs, wishes, and emotions are all strongly influenced by our social psychological development and our relationship experiences in life. John Bowlby, the founder of attachment theory, argued that proximity-seeking is a fundamental behavior that is common to a wide variety of mammalian species (Bowlby, 1988). This attachment behavior system is activated if infants are separated from their caregivers or if a separation is threatening. Infants try to reestablish proximity to their parents or try to prevent separation (e.g., by crying or clinging). Although it started out as a theory of child development, attachment theory has found its place in the discourse of individual therapy (Wallin, 2007) as well as in psychotherapy research (Mallinckrodt & Jeong, 2015). International Journal of Group Psychotherapy, 66: 456–460, 2016 Copyright © The American Group Psychotherapy Association, Inc. ISSN: 0020-7284 print/1943-2836 online DOI: 10.1080/00207284.2016. 1156408
Reliable output feedback for linear systems with sensor mixed faults

A reliable control scheme is developed in this paper for a class of linear based on sensor mixed faults. A more practical mixed faults model of sensor than outage and continuous fault model is considered. The mixed faults model combine outage with continuous fault. Using linear matrix inequality, A sufficient condition is given to guaranteed asymptotic stability and H performance when all control components is operational, as well as when sensor faults occur. A numerical example is also given to illustrate the design procedures and their effectiveness.