Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent Artificial Ants based feature extraction from wavelet packet coefficients for biomedical signal classification

In this paper, a new feature extraction method utilizing ant colony optimization in the selection of wavelet packet transform (WPT) best basis is presented and adopted in classifying biomedical signals. The new algorithm, termed intelligent artificial ants (IAA), searches the wavelet packet tree for subsets of features that best interact together to produce high classification accuracies. While traversing the WPT tree, the IAA takes into account existing correlation between features thus avoiding information redundancy. The IAA method is a mixture of filter and wrapper approaches in feature subset selection. The pheromone that the ants lay down is updated by means of an estimation of the information contents of a single feature or feature subset. The significance of the subsets selected by the ants is measured using linear discriminant analysis (LDA) classifier. The IAA method is tested on one of the most important biosignal driven applications, which is the brain computer interface (BCI) problem with 56 EEG channels. Practical results indicate the significance of the proposed method achieving a maximum accuracy of 83%.
Preparing for Change: Leveraging Knowledge Activities to Enhance Organisational Preparedness in the Case of an Irish Software SME

In the current climate, preparing for change is an issue for companies large and small. However, there remains a dearth of empirical evidence that highlight how software Small to Medium Sized Enterprises (SMEs) operationalise their approach to knowledge management (KM) as a means of preparing themselves for the future. For an SME, the first step is to take stock of the types of knowledge that are valuable to the business, where it is stored and how it is used. In addition, consideration must be given to knowledge activities (KA), the constituent parts, of a company’s KM approach. By doing this, the organisation can identify where its strengths lie in terms of the type and extent to which knowledge is managed through acquisition, codification, storage, maintenance, transfer and creation activities. Using a qualitative analysis approach in a single case study, this chapter identifies occurrences of these knowledge activities as a means of assessing an SME’s approach to KM with a view to better facilitating an organisation’s ability to be increasingly flexible in the face of a changing environment. DOI: 10.4018/978-1-4666-3886-0.ch062
Urban Image Classification: Per-Pixel Classifiers, Subpixel Analysis, Object-Based Image Analysis, and Geospatial Methods

Remote sensing methods used to generate base maps to analyze the urban environment rely predominantly on digital sensor data from space-borne platforms. This is due in part from new sources of high spatial resolution data covering the globe, a variety of multispectral and multitemporal sources, sophisticated statistical and geospatial methods, and compatibility with GIS data sources and methods. The goal of this chapter is to review the four groups of classification methods for digital sensor data from space-borne platforms; per-pixel, sub-pixel, object-based (spatial-based), and geospatial methods. Per-pixel methods are widely used methods that classify pixels into distinct categories based solely on the spectral and ancillary information within that pixel. They are used for simple calculations of environmental indices (e.g., NDVI) to sophisticated expert systems to assign urban land covers. Researchers recognize however, that even with the smallest pixel size the spectral information within a pixel is really a combination of multiple urban surfaces. Sub-pixel classification methods therefore aim to statistically quantify the mixture of surfaces to improve overall classification accuracy. While within pixel variations exist, there is also significant evidence that groups of nearby pixels have similar spectral information and therefore belong to the same classification category. Object-oriented methods have emerged that group pixels prior to classification based on spectral similarity and spatial proximity. Classification accuracy using object-based methods show significant success and promise for numerous urban 3 applications. Like the object-oriented methods that recognize the importance of spatial proximity, geospatial methods for urban mapping also utilize neighboring pixels in the classification process. The primary difference though is that geostatistical methods (e.g., spatial autocorrelation methods) are utilized during both the pre- and post-classification steps. Within this chapter, each of the four approaches is described in terms of scale and accuracy classifying urban land use and urban land cover; and for its range of urban applications. We demonstrate the overview of four main classification groups in Figure 1 while Table 1 details the approaches with respect to classification requirements and procedures (e.g., reflectance conversion, steps before training sample selection, training samples, spatial approaches commonly used, classifiers, primary inputs for classification, output structures, number of output layers, and accuracy assessment). The chapter concludes with a brief summary of the methods reviewed and the challenges that remain in developing new classification methods for improving the efficiency and accuracy of mapping urban areas.
Automated Fault Diagnostics for AHU-VAV Systems: A Bayesian Network Approach

Although it is widely accepted that 20%-30% of total HVAC energy in commercial buildings is wasted due to faulty or inefficient operation, there presently exist no widely adopted solutions to identify and remedy this waste. This lack of adoption is due primarily to the high upfront costs associated with the manual process of customizing commissioning solutions for each individual building. In order to reduce these costs, diagnostic technologies must automate the process of installing and customizing solutions for each implementation. A novel approach to addressing this problem for air handling units (AHUs) and variable air volume (VAV) boxes is presented here. This strategy utilizes a Bayesian network to identify and understand the system operation, identify faults that are wasting energy or impacting occupant comfort, and then generate performance baselines against which future operation will be compared. When this algorithm is first connected to a new building, an adaptive diagnostic Bayesian network identifies the components and configuration of the AHUs and VAVs, and then generates probabilistic outputs indicating the root causes of potential faults and inefficiencies. Once these issues have been rectified to the satisfaction of the building operator, the algorithm then begins to accumulate training data with detailed information about the system operation (while simultaneously continuing to monitor for additional faults). As this training data is accumulated, the diagnostic confidence of the Bayesian network is continuously improved. Additionally, this use of an operational baseline allows for accurate detection and diagnosis of faults causing gradual performance degradation in addition to faults that abruptly occur.
Prevention and Management of Pain in the Neonate: An Update

The prevention of pain in neonates should be the goal of all caregivers, because repeated painful exposures have the potential for deleterious consequences. Neonates at greatest risk of neurodevelopmental impairment as a result of preterm birth (ie, the smallest and sickest) are also those most likely to be exposed to the greatest number of painful stimuli in the NICU. Although there are major gaps in our knowledge regarding the most effective way to prevent and relieve pain in neonates, proven and safe therapies are currently underused for routine minor yet painful procedures. Every health care facility caring for neonates should implement an effective pain-prevention program, which includes strategies for routinely assessing pain, minimizing the number of painful procedures performed, effectively using pharmacologic and nonpharmacologic therapies for the prevention of pain associated with routine minor procedures, and eliminating pain associated with surgery and other major procedures.
Evidence-Based Treatment of Stuttering : Empirical Bases and Clinical Applications

Let's read! We will often find out this sentence everywhere. When still being a kid, mom used to order us to always read, so did the teacher. Some books are fully read in a week and we need the obligation to support reading. What about now? Do you still love reading? Is reading only for you who have obligation? Absolutely not! We here offer you a new book enPDFd evidence based treatment of stuttering empirical bases and clinical applications to read.
Push and rotate: cooperative multi-agent path planning

In cooperative multi-agent path planning, agents must move between start and destination locations and avoid collisions with each other. Many recent algorithms require some sort of restriction in order to be complete, except for the Push and Swap algorithm [Luna and Bekris, 2011], which claims only to require two unoccupied locations in a connected graph. Our analysis shows, however, that for certain types of instances Push and Swap may fail to find a solution. We present the Push and Rotate algorithm, an adaptation of the Push and Swap algorithm, and prove that by fixing the latter's shortcomings, we obtain an algorithm that is complete for the class of instances with two unoccupied locations in a connected graph. In addition, we provide experimental results that show our algorithm to perform competitively on a set of benchmark problems from the video game industry.
Multiperson Bargaining and Strategic Complexity

The authors investigate the effect of introducing costs of complexity in the n- person unanimity bargaining game. In particular, the paper provides a justification for stationary equilibrium strategies in the class of games where complexity costs matter. As is well-known, every individually rational allocation is sustainable as a subgame perfect equilibrium in this game if players are sufficiently patient. By limiting ourselves to strategies which can be implemented by a finite-state machine and by suitably modifying the definition of complexity for the purpose of analysing a single extension form, we find that complexity costs do not reduce the range of possible allocations but do limit the amount of delay that can occur in any agreement and also do exclude use of non-stationary strategies in equilibrium. However, a `noisy Nash equilibrium' with complexity costs turns out to sustain on the unique stationary subgame perfect equilibrium allocation
On the motivic commutative ring spectrum BO.

We construct an algebraic commutative ring T- spectrum BO which is stably fibrant and (8,4)- periodic and such that on SmOp/S the cohomology theory (X,U) -> BO^{p,q}(X_{+}/U_{+}) and Schlichting's hermitian K-theory functor (X,U) -> KO^{[q]}_{2q-p}(X,U) are canonically isomorphic. We use the motivic weak equivalence Z x HGr -> KSp relating the infinite quaternionic Grassmannian to symplectic $K$-theory to equip BO with the structure of a commutative monoid in the motivic stable homotopy category. When the base scheme is Spec Z[1/2], this monoid structure and the induced ring structure on the cohomology theory BO^{*,*} are the unique structures compatible with the products KO^{[2m]}_{0}(X) x KO^{[2n]}_{0}(Y) -> KO^{[2m+2n]}_{0}(X x Y). on Grothendieck-Witt groups induced by the tensor product of symmetric chain complexes. The cohomology theory is bigraded commutative with the switch map acting on BO^{*,*}(T^{2}) in the same way as multiplication by the Grothendieck-Witt class of the symmetric bilinear space .
In-vehicle Visual Search Assistant System Designs Using Driver's Peripheral Vision

Drivers' inattention to obstacles on the road is a major cause of traffic accidents, and developing advanced driver assistance system (ADAS) to support the driver's visual search has been a challenge. This is partly due to the complexity of developing user interfaces that indicate the positional information of objects around the vehicle, such as pedestrians or bicyclists. In this study, we propose an interface design of an visual search assistance system displayed on an electronic instrument cluster. The graphical user interface that employs dynamic motion cues was designed to be perceived in a driver's peripheral vision. A user test is conducted to assess four experimental designs we implemented. The usability factors to evaluate the designs were introduced, and the results indicate that users' preferred design provide the better assistance.
Human Intrusion Detection Using Texture Classification in Real-time

The task of detecting people entering a sterile zone is a common scenario for visual surveillance systems. We propose a novel texture classifier to detect a person in a video frame without temporal information in real-time by identifying salient texture regions. An extension to this classifier by fusing it with simple motion information significantly outperforms standard motion tracking. Lower detection time can be achieved by combining texture classification with Kalman filtering. F1 measures are given for the i-LIDS sterile zone dataset of the UK Home Office. The fusion approach running on 10 frames per second gives the highest result of F1=0.92 for the 24 hour test dataset.
Age and sex dependencies of anxiety and depression in cardiologic patients compared with the general population

Objective: The aim of this study was to test age and sex effects on anxiety and depression using the Hospital Anxiety and Depression Scale HADS. Method: Sample 1 consisted of 2037 subjects of the German general population, and sample 2 comprised 2696 cardiologic patients. Results: In the group of the general population we observed a linear increase of depression and (to a lower extent) of anxiety with age. In contrast to that, the patients reached their anxiety and depression maxima in the range of 50 to 60 years, with decreasing mean values for older patients. This effect was observed in both sexes and was proved by an ANOVA interaction between age category and population (P<0.001). In the age range over 70 years the mean depression scores of the patients were even lower than those of the general population. Especially high anxiety and depression scores were found for retired males under 60 years of age. Conclusion: Premature retirement is associated with anxiety and depression in cardiologic patients which partly accounts for the different age effects of the samples. Longitudinal studies are needed to explain the underlying mechanisms of the age effects in more detail.
Learning Functions from Imperfect Positive

We introduce a Bayesian framework for learning functional hypotheses of unknown input domains from positive examples containing normally distributed noise in the outputs. Our method is embeded in the U-learning scheme of learning from positive data 11] and it subsumes a type of distance based learning as a special case. We also present an eeective method of outlier-identiication which may signiicantly improve the predictive accuracy of the nal multi-clause hypothesis if it is constructed in a clause-by-clause manner as in some inductive logic programming (ILP) systems. Our method is implemented within the ILP system Aleph 5] and tested on two experiments, one of which concerns numeric functions while the other treats non-numeric discrete data where the normal distribution is taken as an approximation of the discrete distribution of noise.
Dynamics of the Krichever construction in several variables

The Krichever construction in one variable, that is, for spectral curves, linearizes the KdV-hierarchy on the jacobian of the curve. We carry out an appropriate generalization of the Krichever construction for an arbitrary projective variety $X$ and determine the corresponding nonlinear dynamics, which are then linearized on an extension of $Pic^0(X)$.
Selective inhibitors of phosphoinositide 3-kinase delta: modulators of B-cell function with potential for treating autoimmune inflammatory diseases and B-cell malignancies

The delta isoform of the p110 catalytic subunit (p110δ) of phosphoinositide 3-kinase is expressed primarily in hematopoietic cells and plays an essential role in B-cell development and function. Studies employing mice lacking a functional p110δ protein, as well as the use of highly-selective chemical inhibitors of p110δ, have revealed that signaling via p110δ-containing PI3K complexes (PI3Kδ) is critical for B-cell survival, migration, and activation, functioning downstream of key receptors on B cells including the B-cell antigen receptor, chemokine receptors, pro-survival receptors such as BAFF-R and the IL-4 receptor, and co-stimulatory receptors such as CD40 and Toll-like receptors (TLRs). Similarly, this PI3K isoform plays a key role in the survival, proliferation, and dissemination of B-cell lymphomas. Herein we summarize studies showing that these processes can be inhibited in vitro and in vivo by small molecule inhibitors of p110δ enzymatic activity, and that these p110δ inhibitors have shown efficacy in clinical trials for the treatment of several types of B-cell malignancies including chronic lymphocytic leukemia (CLL) and non-Hodgkin lymphoma (NHL). PI3Kδ also plays a critical role in the activation, proliferation, and tissue homing of self-reactive B cells that contribute to autoimmune diseases, in particular innate-like B-cell populations such as marginal zone (MZ) B cells and B-1 cells that have been strongly linked to autoimmunity. We discuss the potential utility of p110δ inhibitors, either alone or in combination with B-cell depletion, for treating autoimmune diseases such as lupus, rheumatoid arthritis, and type 1 diabetes. Because PI3Kδ plays a major role in both B-cell-mediated autoimmune inflammation and B-cell malignancies, PI3Kδ inhibitors may represent a promising therapeutic approach for treating these diseases.
Theoretical and Experimental Studies of Flip-Chip Assembled High- $Q$ Suspended MEMS Inductors

This paper reports the theoretical and experimental studies of high-Q suspended microinductors produced by flip-chip assembly for multigigahertz RF integrated-circuit applications. The effects of device and substrate parameters on the Q factor of the inductor devices are studied by numerical simulation using Ansoft's high frequency structure simulator electromagnetic field simulation package. Suspended inductor devices are realized using a flip-chip assembly method in which the inductor structures with the supporting pillars are fabricated on a low-cost polyimide thin-film carrier and then assembled onto a low resistivity (3-4 Omegaldrcm) silicon substrate by flip-chip bonding. Individual and 2times2 arrays of meander and spiral inductor designs have been successfully fabricated with air gap heights ranging from 15 to 31 mum. Maximum Q factors of ~15 and ~13 at ~1 GHz have been achieved for meander and spiral suspended inductor devices before pad deembedding. It is shown that the optimal air gap between the inductor and substrate surface is ~15 mum beyond which no further enhancement in the Q factor can be obtained for devices on low-resistivity substrates. The experimental results are in excellent agreement with that of theoretical simulation. The inductor assembly method requires minimal chip/wafer processing for integration of high-Q inductors.
Illuminating Clay : A Tangible Interface for GRASS applications ? 2 3 Illuminating Clay

The development of cheaper and faster computation and the multiplying effect of open source initiatives such as GRASS have led to an increasing sophistication is GIS landscape analysis algorithms. However, little research has focused on the design of the computer interface through which users interact with GIS simulations. The conventional interface comprising of screen, keyboard and mouse is used by default and as such has an enormous impact on the process of computational landscape analysis. This paper introduces Illuminating Clay, an alternative interface for manipulating and navigating landscape representations that has been designed according to the specific needs of the landscape analyst.
Information Security Practices in Latin America: The case of Bolivia

REQUIRED) In this paper, we present a social/behavioral study of individual information security practices of internet users in Latin America, specifically presenting the case of Bolivia. The research model uses social cognitive theory in order to explain the individual cognitive factors that influence information security behavior. The model includes individuals' beliefs about their abilities to competently use computer information security tools and information security awareness in the determination of effective information security practices. The operationalization of constructs that are part of our research model, such as information security practice as the dependent variable, self-efficacy and information security awareness as independent variables , are presented both in Spanish and English. In this study, we offer the analysis of a survey of 255 Internet users from Bolivia who replied to our survey and provided responses about their information security behavior. A discussion about information security awareness and practices is presented.
Mitigating Voltage and Frequency Fluctuation in Microgrids Using Electric Springs

Voltage and frequency fluctuation associated with renewable integration have been well identified by power system operators and planners. At the microgrid level, a novel device for the implementation of dynamic load response, which is known as the electric springs (ES), has been developed for mitigating both active and reactive power imbalances. In this paper, a comprehensive control strategy is proposed for ES to participate in both voltage and frequency response control. It adopts the phase angle and amplitude control which respectively adjust the active power and the reactive power of the system. The proposed control strategy is validated using a model established with power system computer aided design/electro-magnetic transient in dc system. Results from the case studies show that with appropriate setting and operating strategy, ES can mitigate the voltage and frequency fluctuation caused by wind speed fluctuation, load fluctuation, and generator tripping wherever it is installed in the microgrid.