Miracle-dz/UniFAR-FTUs huggingface dataset:
Recognition of the making on Integrated Circuit Chips based on the hybrid Fourier-AFMT

In this paper, an automatic optical inspection system incorporating optical character recognition (OCR) is employed to inspect markings on integrated circuit (IC) chips. Here, we present a novel OCR-based method for character recognition based on the features extracted from the integrated discrete wavelet and the hybrid Fourier-AFMT framework (DWFAFMT) which is fast and yields better results as compared to basic Fourier Mellin Transform. We focus on the computation of a new set of invariant features allowing the classification of multi-oriented and multi-scaled patterns. Discrete Wavelet transform was used to smooth and preserve the local edges after image decomposition, making the character images less sensitive to shape distortion whilst Fourier-AFMT served to produce a translation, rotation and scale invariant feature, Multiple DWF-AFMT features could be used to form a reference invariant feature through the linearity property of Fourier-AFMT and reduce the variability of input images. The experiments showed the recognition rate reached over 100% when multiple DWF-AFMT features were used. Keywords-Printed marking recognition, analytical FourierMellin transform (AFMT), Wavelet transforms, Optical Character Recognition (OCR)\
Forecasting event outcomes from user predictions on Twitter

Social media websites like Twitter provide an ideal environment for people to express their opinions and beliefs about upcoming events. When an event like the Oscars is around the corner, users on social media websites try to make predictions about potential winners at the event. For example, Leo will finally win the Oscar for Revenant! suggests that the author of the tweet believes that Leonardo DiCaprio will win at the Oscars. Can user predictions on Twitter be an indicator of the actual outcome of these events? This work focuses on exploring the answer to this question by using the concept of veridicality. In social media, we find tweets of varying degrees of veridicality. Before the 2017 Oscars we see tweets about Moonlight such as Moonlight will win Best Picture! vs. Moonlight will lose to La La Land. and I need Moonlight to win! The first tweet indicates that the author believes, with certainty, that Moonlight will win. This is positive veridicality towards an outcome. The second tweet indicates the opposite Moonlight not winning and is an expression of negative veridicality towards the event. We build a classifier which can automatically detect the veridicality of a given tweet with high precision. Further, by using this classifier to detect tweets with positive veridicality, it can be shown that we can make predictions on outcomes of speculative events much better than sentiment and volume-based predictions made on the same events. Our analysis also allows us to retrospectively predict surprise outcomes in such speculative events.
The Spatially Separated Polarization Sensitive FDA-MIMO Radar: A New Antenna Structure for Unambiguous Parameter Estimation

Joint DOA-range-polarization estimation with a novel radar system, i.e., spatially separated polarization sensitive random frequency diverse array based on multiple-input multiple-output (SS-PSRFDA-MIMO) radar, is discussed. The proposed array can obtain not only unambiguous range estimation but also polarization parameter estimation. Firstly, the signal model of SS-PSRFDA-MIMO radar is constructed. Secondly, dimension reduction multiple signal classification (DR-MUSIC) algorithm is extended to parameter estimation with the proposed array. Last, simulations demonstrate the proposed algorithm is effective to estimate parameter, and the performance of proposed array is better than that of polarization sensitive frequency diverse array based on MIMO radar. It is worth mentioning that the Cramer–Rao lower bound (CRLB) of range estimation with the proposed array is much lower than that of PSFDA-MIMO radar.
Materials Liaisons: facilitating communication in Design-Driven Material Innovation (DDMI) projects

In an increasingly complex ‘problem’ landscape, interdisciplinary collaboration is becoming an important part of design practice. Yet designers use very different language and methods to other disciplines, which can be a significant barrier to communication, shared understanding and trust. New methods to enable effective communication between designers and other disciplines are needed across the design industry. This paper presents research from an EU H2020 funded project which is trialling a new Design-Driven Material Innovation (DDMI) methodology. The collaborative process, involving designers, scientists and manufacturers, presents a number of challenges, particularly in enabling people with very different disciplinary/national/cultural languages to understand one another. For the project to move forward, at the very least, designers need to understand the material’s potential and scientists need to understand what designers want the material to ‘be like’. Effective ‘materials communication’ is crucial. The study focusses on one approach – appointing ‘materials liaison officers’ – to facilitate the interdisciplinary exchange of materials information at a crucial stage in the project, when the first materials prototypes were being developed in response to design concepts. Drawing on interviews and workshop material the author discusses the benefits and limitations of using a ‘bilingual’ liaison to translate material understanding from one discipline to another. The findings highlight a number of aspects that affect interdisciplinary materials communication such as familiarity with the material type being developed, the number of processes involved in production of the material, the approach of the designer, and the role of materials samples as boundary objects to anchor the dialogue. There are implications for interdisciplinary design projects more generally, where communication is equally challenging and important.
Interactions between thin‐ and thick‐skinned tectonics at the northwestern front of the Jura fold‐and‐thrust belt (eastern France)

This study investigates spatial and temporal interactions of thin‐ and thick‐skinned tectonics in a classical foreland setting located at the front of the Jura fold‐and‐thrust belt in eastern France. The working area coincides with the intracontinental Rhine‐Bresse Transfer Zone and represents the most external front of the deformed Alpine foreland. The investigation combines analyses of largely unpublished and newly available subsurface information with our own structural data, including an exhaustive paleostress analysis and geomorphologic observations. Results are provided in the form of a new tectonic map and a series of regional cross sections through the study area. The Besançon Zone, forming the most external part of the thin‐skinned fold‐and‐thrust belt, encroached onto the Eo‐Oligocene Rhine‐Bresse Transfer Fault System until early Pliocene times. Thrust propagation was largely controlled by the Late Paleozoic to Paleogene preexisting fault pattern that characterizes the Rhine‐Bresse Transfer Zone. Thick‐skinned deformation, dominant throughout the Avant‐Monts Zone located farther to the west, was associated with compressional to transpressional reactivation of such faults. Overprinting and crosscutting criteria of fault slip data allow distinguishing between systematically fanning maximum horizontal stress axes that define the front of the thin‐skinned Jura fold‐and‐thrust belt and consistently NW–SE directed maximum horizontal stress axes that characterize deformation of the autochthonous cover of the foreland, which is affected by thick‐skinned tectonics. Tectonic and geomorphic analyses indicate that thick‐skinned tectonics started at a very late stage of foreland deformation (post‐early Pliocene). Geomorphic observations imply that deformation between Mesozoic cover and basement is locally still decoupled. However, overprinting relationships and recent seismicity suggest that present‐day tectonic activity is thick skinned, which probably reflects ongoing tectonic underplating in the Alpine foreland.
A Closed Form Expression for Predicting Fast Scale Instability in Switching Buck Converters

Fast scale instability is an undesired phenomenon in switching converters. In past studies, its predic- tion has been mainly carried out by deriving discrete time models and then linearizing the system in the vicinity of a fixed point. However, the results obtained from such an approach cannot be applied for design purpose except for simple cases of current mode control. Alternatively, in this paper, this phenomenon is analyzed by using a unified formal symbolic approach which can be applied for different control strategies. This approach is based on expressing the condition for fast scale instability occurrence using Fourier series and then converting the result into a matrix form expression which depends explicitly on the system parameters making the results directly applicable for design purpose. Under certain practical conditions concerning these parameters, the matrix form expression can be approximated by standard polynomial functions depending on the operating duty cycle. The approximating polynomial functions are widely related to the well known Clausen polynomial functions. The results presented in this work clearly generalize the well known stability condition of current mode control.
Domestic Systemically Important Banks: An Indicator-Based Measurement Approach for the Australian Banking System

This paper serves as a response to the assessment methodology of the Basel Committee on Banking Supervision to identify systemically important banks. Based on the official technique, which requires an extensive collection of bank data, our paper develops a practicable modification. Utilising readily available indicators, we determine the domestic systemic risk of each licensed bank in Australia in the period 2002-2011. Our quantitative results uncover not only high levels of systemic risk for the four major banks, but their rising dominance during the global financial crisis. Consequently, we introduce a regulatory proposal that enables authorities to reduce the systemic risk of individual institutions.
CROSS-CULTURAL TRANSFER LEARNING USING SAMPLE-LEVEL DEEP CONVOLUTIONAL NEURAL NETOWRKS

This submission aims to show how cultural differences in music affect audio feature learning. Measuring how largely music content differ in each culture is conducted via various MIREX 2017 audio classification tasks in a transfer learning setting. In this submission, two pre-trained deep neural networks are provided. One is trained with Million Song Dataset with the LastFM tag annotations and the other is learned from a music dataset from NAVER with genre annotations. Furthermore, two methods are applied to improve classification accuracy. One is using raw waveform-based sample-level deep convolutional neural networks as a feature extractor. The other is multi-level feature extraction and aggregation from the pre-trained networks to tackle various levels of abstractions in MIREX audio classification tasks. Finally, we put them into a classifier based on a support vector machine and make final predictions for each target task. Our submissions were ranked at the first in 6 out of a total of 8 Train/Test tasks of MIREX 2017.
Abstract-WSN-Erlang : a Functional , High Level Approach to WSN Development

The complexity in designing, coding, and testing WSN applications is considered among the most relevant factors that limit the diffusion of WSN technology. In this work we claim that Erlang, a concurrency and distribution-oriented, functional language, could greatly reduce this complexity. Moving from this premise we introduce a new platform, named WSN-Erlang, which leverages the Erlang peculiarities adapting them to the requirements of WSNs. WSN-Erlang also includes a testing and simulation framework, fully supporting the entire life-cycle of WSN applications.
Common Ragweed Invasion in Sweden: Impacts of the Lag Phase on Human Health

Common ragweed (Ambrosia artemisiifolia) is a neophyte from North America that has spread rapidly throughout Europe. Because the pollen of common ragweed is highly allergic, many countries have adopted containment and mitigation measures. The neophyte has only recently established flowering populations in Sweden. We use this well documented case to study the early impacts of an invasive species on human health. Our identification strategy relies on spatial and temporal variation in common ragweed populations and health data for 1998-2011, applying panel-data estimation techniques. To ensure the robustness of our findings, we test and correct for heteroskedasticity and autocorrelation. Our estimates show that an invasive species still in its lag phase can yet have adverse impacts on human health.
Marketing Manufacturer and Retailer House Brands: A Study of Shelf Space in Two Product Categories

This article investigates shelf space allocation in the marketing of manufacturer brands (national brands) and retailer house brands (store brands) in the consumer packaged goods sector in a highly concentrated grocery retail environment. Of special interest is the degree to which the market mechanism is still at play in this kind of environment where retail chains wield considerable power over manufacturers supplying the respective grocery retail categories. The study focuses on two consumer packaged goods categories, and data collection is conducted via a combination of in-store category observation and in-depth interviews. The results of in-store category observation data indicate that the shelf space occupied by retailer house brands is largely proportional to the market share of the retailer house brands, which tends to negate the possibility of abuse of power within the product categories studied. Analysis of research interview data unveiled a number of themes that seem to collectively indicate that, both the manufacturer brand and the retailer house brand will continue to have a home in the respective categories, and performance on the part of manufacturer brands is expected for them to be able to justify occupation of valuable shelf space ahead of other competing manufacturer brands in the tightly contested shelf arena. The study points to the importance of participation of both manufacturer and retailer house brands if optimum category performance is to be achieved.
Application of Spectral Unmixing on Hyperspectral Data of the Historic Volcanic Products of Mt. Etna (Italy)

In this study, we focus on the identification of various volcanic products of Mt. Etna (eastern Sicily, Italy). Mt. Etna is one of the most active basaltic composite stratovolcanoes with the ability to change its land field rapidly, vigorously and continuously. For this purpose, NASA EO-1/Hyperion hyperspectral data (HSI) are used for lava flow differentiation and mapping within the historic “1536” to “1669” era of the Torre del Filosofo formation. These volcanic products are selected, due to a) their distinct spatial distribution, b) spectral similarity and c) field segregation from surrounding younger lavas. Due to their high compositional variability, the corresponding HSI pixels are mixed thus the problem is tackled with Spectral Unmixing (SU) techniques. First, endmember extraction, for each lava type, is performed by averaging over a Gaussian distribution of pixel reflectances of its associated region of interest (ROI). Then, abundances are estimated by two unmixing models: Constraint Linear Least Squares Unmixing (LLSU) and Bilinear Unmixing (BLU), applied on both spectral signatures and transformed versions of them, i.e. in the frequency domain through a Fourier Transform (FT). Historic lava flow delineation results are presented creating abundance maps per method. Also, a qualitative evaluation is performed using the Etna geological map, while a quantitative assessment is performed through derivation of the Structural Similarity Index (SSIM) of each implemented method. Ultimately, we address the degree of lava flow separability with the intercomparison of all methods and give an estimation of the computationally most efficient method. The specific research shows that HSIs provide useful information for individual lava flow differentiation and mapping in a complex environment such as Mt. Etna, despite limitations such as the relatively coarse pixel size, noisy bands and the sparse number of bibliographic references on lava spectral measurements.
The ameliorative effect of mycosorb in aflatoxin contaminated diet of broiler chickens

This experiment was conducted to study the effect of Aflatoxins (AF) on broiler performance, organ weight, plasma characteristics, protein digestibility, and metabolizable energy of the diets. Dietary treatments were: 1) control diet based on corn and soybean meal; 2, 3 and 4) control diet plus 1 mg kg AF, 1 mg kg AF and 0.25% mycosorb, and 0.25% Mycosorb, respectively. The results in the Aflatoxins and Aflatoxins+ mycosorb treatments showed that dietary AF, significantly decreased the feed intake and weight gain as compared to the control diet (P<0.001). Treatment 2 resulted in inferior feed conversation ratio in comparison to the control diet (p<0.05). Uric acid and total protein in the second and third, and phosphorous only in the third treatment were significantly lower than the control (P<0.05). The in-vivo protein and dry matter digestibility, apparent metabolizable energy (AME) and nitrogen corrected-apparent metabolizable energy (AMEn) were not affected by the treatment (P>0.05). Aflatoxin resulted in the proventriculus enlargement, increased liver weight and AF deposition in the liver and breast muscle (P<0.05). This study clearly demonstrated that Mycosorb was effective in alleviating the adverse effects of dietary aflatoxins in broiler chickens.
A Simple Practical Algorithm for a Computationally Hard Problem

Two n-by-n matrices $A$ and $B$ are permutation-similar, if there exists a permutation matrix $P$ such that $A=PBP^t$. Deciding whether two matrices are permutation-similar, is a computationally hard problem. Because, all possible permutations should be checked in general. This decision problem is the core of many main problems, such as graph isomorphism problem. In the graph isomorphism problem, we should decide whether the adjacency matrices of a pair of graphs are permutation-similar. Here, a simple and fast algorithm is proposed to solve this generally hard problem efficiently in practice. The computations show that this proposed simple algorithm which is based on both matrix spectrum and randomness, successfully, solves the graph isomorphism problem for studied instances of hard cases of this problem.
A Forward-Backward Splitting Method for Monotone Inclusions Without Cocoercivity

In this work, we propose a simple modification of the forward-backward splitting method for finding a zero in the sum of two monotone operators. Our method converges under the same assumptions as Tseng's forward-backward-forward method, namely, it does not require cocoercivity of the single-valued operator. Moreover, each iteration only requires one forward evaluation rather than two as is the case for Tseng's method. Variants of the method incorporating a linesearch, relaxation and inertia, or a structured three operator inclusion are also discussed.
Aalborg Universitet Examining the heterogeneity and cost-effectiveness of a complex intervention by segmentation of chronic obstructive pulmonary disease

Objectives: To examine the heterogeneity in cost-effectiveness analyses of patient-tailored complex interventions. Methods: Latent class analysis (LCA) was performed on data from a randomized controlled trial evaluating a patient-tailored case management strategy for patients suffering from chronic obstructive pulmonary disease (COPD). LCA was conducted on detailed process variables representing service variation in the intervention group. Features of the identified latent classes were compared for consistency with baseline demographic, clinical, and economic characteristics for each class. Classes for the control group, corresponding to the identified latent classes for the intervention group, were identified using multinomial logistic regression. Cost-utility analyses were then conducted at the class level, and uncertainty surrounding the point estimates was assessed by probabilistic sensitivity analysis. Results: The LCA identified three distinct classes: the psychologically care class, the extensive COPD care class, and the limited COPD care class. Patient baseline characteristics were in line with the features identified in the LCA. Evaluation of cost-effectiveness revealed highly disparate results, and case ee front matter Copyright & 2018, International S r Inc. This is an open access article under the CC ons.org/licenses/by-nc-nd/4.0/). 1016/j.jval. 2017.08. 001 ondence to: Sabrina Storgaard Sørensen, Departm org University, Fibigerstræde 11, Aalborg 9220, D torgaardsoerensen@gmail.com. management for only the extensive COPD care class appeared costeffective with an incremental cost-effectiveness ratio of £26,986 per quality-adjusted life-year gained using the threshold value set by the National Institute of Health and Care Excellence. Conclusions: Findings indicate that researchers evaluating patient-tailored complex interventions need to address both supply-side variation and demand-side heterogeneity to link findings with outcome. The article specifically proposes the use of LCA because it is believed to have the potential to enable more appropriate targeting of complex care strategies.
Dignity in care in the clinical setting

This review aimed to explore nursing literature and research on dignity in care of inpatients and to evaluate how the care patients received in the hospital setting was related to perceived feelings of being dignified or undignified. Studies conducted between 2000 and 2010 were considered, using Cumulative Index to Nursing and Allied Health Literature and MEDLINE, and the search terms ‘patient dignity’, ‘dignity in care’, ‘human dignity and nursing’ and ‘dignity and nursing ethics’. Findings revealed, from the perspectives of nurses and patients, that dignity in care in the hospital setting is seen to be influenced by physical environment, staff attitude and behaviour, organisational culture and patient independence. This review can help nurses to better understand dignity in care, and for policy makers, there are implications about determining the physical environment, staff attitude and behaviour and organisational culture needed to promote patient dignity in nursing. By identifying the most important factors from patients’ and nurses’ perspectives that contribute to dignity in care, nursing interventions, such as campaigns and education in clinical practice, can be developed.
CALIBRAÇÃO DE UM DIAFRAGMA UTILIZANDO ÁGUA RESIDUÁRIA DA BOVINOCULTURA E SUINOCULTURA

Um bom controle da aplicacao de aguas residuarias no cultivo agricola e bastante relevante, pois o seu uso indiscriminado pode provocar muitos problemas ambientais, como: salinidade, dispersao do solo, contaminacao de aguas subterrâneas e superficiais, entre outros. Assim, o objetivo desse trabalho foi avaliar os efeitos dos fluidos resultantes da mistura agua-dejetos bovino e suino, na calibracao de um diafragma. Os resultados mostraram que as equacoes de calibracao encontradas podem ser consideradas iguais para todos os fluidos escoantes utilizados, ao nivel de 5% de probabilidade.