Miracle-dz/UniFAR-FTUs huggingface dataset:
Postharvest noninvasive classi fi cation of tough-fi brous asparagus using computed tomography images

This research was devised to evaluate Computed Tomography (CT) for asparagus fibrousness detection and more specifically develop and test an automatic image analysis method (algorithm) to classify CT images obtained from 859 asparagus (Asparagus officinalis L.) segment (samples), collected during two harvesting seasons (2014 and 2015). Classification accuracy was calculated by comparing the classes obtained using a combination of imaging, image processing, feature extraction, and classification schemes per asparagus segment against an industry-simulated invasive quality assessment. Grayscale intensity and textural features, 3762 total, were extracted from minimum and maximum resultant images from three CT planer views. A 4-fold cross-validation linear discriminant classifier with a performance accuracy of 91.2% was developed using 75 relevant features, which were selected using a sequential forward selection algorithm with the Fisher discriminant objective function. This objective method is accurate in determining the presence of tough-fibrous tissue in asparagus, which demonstrates a potential for such technology to objectively forecast asparagus quality and thus supports the asparagus industry through optimizing consumer acceptability and product utilization. ã 2016 Elsevier B.V. All rights reserved.
Design concepts in nutritional epidemiology

Part A The scientific concepts underlying study design overview of the principles of nutritional epidemiology design, planning and evaluation of nutritional epidemiological studies sampling, study size and power covariate measurement errors in nutritional epidemiology - effects and remedies. Part B The measurement of exposure and outcome food consumption, nutrient intake and the use of food composition tables assessment of food consumption and nutrient intake biochemical markers of nutrient intake the validation of dietary assessment socio-demographic and psycho-social variables anthropometric measures gene-nutrient interactions in epidemiological studies. Part C The design of nutritional epidemiological studies ecological studies cross-sectional studies cohort studies case-control studies experimental studies: clinical trials, field trials, community trials and intervention studies.
Frequency performance of Hamon transfer standards

Shielded and temperature controlled 1 000 Ω / 10 Ω and 10 000 Ω / 100 Ω transfer standards have been realized to be used in the frequency range up to 5 kHz. Their frequency performances have been evaluated by comparison with calculable resistors of quadrifilar and octofilar design. Thanks to the known frequency performances, both standards can serve as reference devices for precision AC measurements of resistance ratios made by means of commercial four terminal-pair bridges. Introduction The advent of quantum standards of voltage and resistance has increased the importance of highly accurate resistance-ratio devices, and especially Hamon transfer standards [1] proved to be useful tools for precision measurements of voltage and resistance ratios. These standards consist of n resistors of the same nominal value R permanently connected in series, additional potential and current terminals being connected to their junctions to make four-terminal measurement of the contribution of each resistor to the total C0 P0 C2 P2 C4 P4 Cn Pn
EasyChair Preprint No 1443 Airborne Particle Classification in LiDAR Point Clouds Using Deep Learning

LiDAR sensors have been very popular in robotics due to their ability to provide accurate range measurements and their robustness to lighting conditions. However, their sensitivity to airborne particles such as dust or fog can lead to perception algorithm failures (e.g. the detection of false obstacles by field robots). In this work we address this problem by proposing methods to classify airborne particles in LiDAR data. We propose and compare two deep learning approaches, the first is based on voxel-wise classification, while the second is based on point-wise classification. We also study the impact of different combinations of input features extracted from LiDAR data, including the use of multi-echo returns as a classification feature. We evaluate the performance of the proposed methods on a realistic dataset with the presence of fog and dust particles in outdoor scenes. We achieve an F1 score of 94% for the classification of airborne particles in LiDAR point clouds, thereby significantly outperforming the state-of-the-art. We show the practical significance of this work on two real-world use cases: a relative pose estimation task using point cloud matching, and an obstacle detection task. The code and dataset used for this work are available online1. Fig. 1: Left: Image of an experimental scene with dust behind a car. Middle: LiDAR point cloud with dust corruption (colored by height). Right: Predicted particles (white) and non-particles (red). Julian Nubert, Daniel Dugas, Julia Nitsch, Roland Siegwart, Cesar Cadena ETH Zurich, Zurich, Switzerland e-mail: nubertj@ethz.ch Julia Nitsch Ibeo Automotive Systems, Hamburg, Germany Leo Stanislas, Niko Sünderhauf, Thierry Peynot Queensland University of Technology, Brisbane, Australia, e-mail: l.stanislas@qut.edu. au * indicates equal contributions. 1 https://leo-stan.github. io/particles_detection_fsr
Children's understandings of mediated health campaigns for childhood obesity

Purpose – The purpose of this paper is to investigate children's understandings of the intent and importance of current media initiatives designed to target childhood obesity. Semi‐structured interviews were analysed using qualitative content analysis, for the responses of overweight and normal weight children.Design/methodology/approach – In total, 33 children were interviewed, 24 of normal weight and nine overweight. They were shown two print and four television advertisements from the New South Wales Health Department web site that were popularly broadcast between 2003 and 2007. Children were then asked if they had seen the advertisement prior to the interview, and their understanding of the intent and importance of the advertisements.Findings – Most children in both weight groups recalled seeing five out of the six presented advertisements prior to interview. The main themes identified were “Health Maintenance” and “Illness Prevention” for five of the six advertisements. Overweight children were more .
Structure and Reaction Mechanism of Basil Eugenol

*1Howard Hughes Medical Institute, Jack H. Skirball Center for Chemical Biology and Proteomics, The Salk Institute for Biological Studies, La Jolla,California, United States of America, 2Department of Molecular, Cellular and Developmental Biology, University of Michigan, Ann Arbor, Michigan,United States of America
1 MICROPHONE ARRAY MEASUREMENTS ON AEROACOUSTIC SOURCES

The flow around obstacles is often very complex, leading to distributed aeroacoustic sources. In experimental investigations, microphone arrays can help to separate, analyze and quantify these partial sources. In order to do so, a microphone array with a high spatial resolution and a high dynamic range is essential. In this publication, the setup and application of a microphone array for aeroacoustic measurements in a model scale wind tunnel will be discussed. Initially, the development and optimization of the microphone array will be described. Preliminary considerations and the derivation of major quality criteria will be explained. Methods for the enhancement of the measurement results as well as for the source characterization will be presented. These methods include the variation of the measurement conditions as well as advanced signal processing. Results of measurements on various test structures will be presented. These structures do all possess aeroacoustic sources with dipole sound radiation but do also exhibit different frequency behaviour of narrowband (cylinder) and broadband (generic wing profile) radiation. 1 Berlin Beamforming Conference
Reweighted ` 1 minimization for audio inpainting

Reweighted `1 minimization has been successfully applied to the task of audio declipping by Weinstein and Wakin (2011). We adapt the reweighting to the audio inpainting problem, for both the synthesis and the analysis models. It is shown that the reweighting provides a significant improvement in terms of SNR, especially in the analysis model.
Impact of amplification on speech enhancement algorithms using an objective evaluation metric

Hearing loss is prevalent among elderly adults, which leads to speech-understanding difficulties in noisy environments. Speech enhancement algorithms are thus proposed to alleviate this speech-in-noise problem. However, most of these algorithms have not been evaluated for hearing-impaired people either with or without the use of hearing aids. In this study, we evaluated the performance of several speech enhancement algorithms [i.e., nonnegative matrix factorization based, deep-neural-network based and long short-term memory (LSTM) based algorithms] for hearing-impaired listeners using an objective speech quality metric, namely the Hearing-Aid Speech Quality Index (HASQI). The HASQI is based on a physiologically inspired model of auditory processing, which also allows the simulation of hearing impairment. The evaluation was repeated separately for the typical hearing characteristics of different genders in various age groups. For the aided condition, linear amplification was implemented using the NAL-R prescription formula. The benefits from the speech enhancement algorithms decrease with increasing degrees of hearing loss. With amplification, the benefit diminishes for the listener group with the most severe hearing impairment. Among the various algorithms, the LSTM-based structures exhibit superior performance with and without amplification.
IMAGE ANALYSIS METHOD FOR OBSERVING CRACK , STRAIN AND DISPLACEMENT FIELDS IN RC STRUCTURAL EXPERIMENTS

This paper presents an image analysis method that is capable of capturing crack distributions, displacement and strain fields in structural testing of reinforced concrete (RC) elements. Traditionally, crack distributions are recorded by manually marking visible cracks in the concrete during an experiment. Strain profiles and displacements of the test specimen are recorded using strain and displacement gauges located at specific measurement locations on the test specimen. The use of such techniques can be time consuming and expensive, requiring significant investment in the cost of the sensors, time for their installation, and large data acquisition systems to collect the data. The use of such measurement systems also requires a priori knowledge of specific measurement locations, something that may not be obvious for large scale experimental testing. Alternatively, the image analysis technique presented herein is a freely available software tool, ImPro Stereo. ImPro Stereo provides a cost effective reliable measurement tool capable of capturing crack progressions, surface strain fields, and displacement time histories in a large-scale structural experiment. To validate the performance of the image analysis method, it is implemented in an experimental program on the in-plane seismic behavior of RC shear walls rehabilitated using fiber-reinforced polymer (FRP) sheets. The image analysis method is shown to be capable of measuring crack distributions and displacement fields over the entire surface of the shear wall with a high degree of accuracy. Strain profiles can be estimated according to the surface displacements. Experimental results from the image analysis method are utilized to develop a better understanding of the behaviour of RC shear walls retrofitted with FRP sheets for earthquake resistance. Potential field applications for the image analysis method in FRP-strengthened RC structures are also discussed.
Isolation and Characterization of Actinobacteria in Rhizosphere of Crinum latifolium ( L . ) Cultivated in Tay Ninh Province , Vietnam

Characteristics of plant growth promotion and biological antagonism of rhizospheric actinobacteria were initially investigated. Rhizospheric soil samples were collected from medicinal plant farms of Trang Bang district, Tay Ninh province. Actinobacteria were isolated by spreading soil suspension on Gauze's medium No.1 plates. The pure colonies were selected and streaked over the agar surfaces of Burk’s N free and NBRIP media plates. Sixty eight isolates had grown on both of media, indicated their abilities of nitrogen fixation and phosphate solubilization. Quantitative results showed that the nitrogen fixation ability of 68 isolates ranged from 0.4 – 8.8 mg L-1 NH4+, and the ability of phosphate solubilization of these were equivalent to 17.6 – 59.1 mg L-1 P2O5. There were 40 in the total 68 isolates showed positive reactions to Salkowski reagent. Hence quantification of IAA produced by these isolates had been conducted under the condition of adding 100 mg L-1 tryptophan into the cultural medium. The IAA production of 40 isolates ranged from 0.3 – 11.5 mg L-1. Eleven isolates that showing outstanding ability in nitrogen fixation, phosphate solubilization and IAA production had been tested ability of producing siderophore and antifungal activity. There were 3 isolates including C15A, C1, H6P that showed the production of siderophore in the CAS assay. Especially, C15A also showed antifungal ability. These three isolates were identified by using the MALDI Biotyper System (Germany). The identification result showed that C15A was Streptomyces aureofaciens, C1 was Streptomyces fabae. Only isolate H6P was not identified because no peak had found in the analysis. Results of this research indicate that two isolates C15A and C1 are promising candidates for application as inoculant for medicinal plants such as Crinum latifolium because they possess good characteristics of plant growth promotion and biological control.
Wisdom of Ignorance : BERT-wBiDAF for SQuAD 2

SQuAD v2.0, as compared to SQuAD v1.0, has a major change in including unanswerable questions into the dataset. This has led to significant performance drop in models previously trained for SQuAD v1.0. We propose two main areas in improving the state-of-the-art BERT model for SQuAD v2.0. First, to improve the model for correctly distinguishing between answerable and unanswerable questions, we take answerable/unanswerable classification into account either through a twostage model or adding an extra binary cross-entropy loss into the training objective. Secondly, we believe that an answer is closely related to the type of the question. We encourage the model to focus on question types by either training a model on each type separately or introducing a weighted attention mechanism. The best model is a combination of BERT pre-trained embeddings and BiDAF architecture with classification loss (BERT-wBiDAF), where the context-to-question attention is up-weighted for keywords in the questions. Our BERT-wBiDAF model achieves 73.89 EM, 77.45 F1 and 81.11 AvNA on the dev set, and 72.97 EM and 76.66 F1 on the test set.
Mining and Insurgency in the Philippines : A Subnational Analysis of Natural Resource Conflict Using Spatial Regression Analysis of Remotely Sensed Data

The relationship between natural resource exploitation and civil conflict has long been of interest to social scientists, and cross-country quantitative studies, applying various regression analysis methods, abound on the subject. Although the limited availability of data has historically prevented researchers from examining natural resource conflict at subnational scales, emerging techniques in the use of remote sensing and Geographic Information Science hold great promise for overcoming that challenge. The paper investigates the relationship between natural resource exploitation and civil conflict in the Republic of the Philippines. Georeferenced event data and remotely sensed land cover and nighttime light data were used to identify natural resource extraction projects, quantify environmental degradation, and construct subnational socioeconomic and conflict variables. A spatial probit regression model was estimated on a dataset comprising 1647 cities and municipalities in order to assess the strength of the relationship between mining activities and risk of conflict at the subnational scale, and to identify the contextual factors that shape that relationship. Results of the regression analysis indicate a strong relationship between the presence of mining activity in a municipality or city and the probability of conflict occurring, an effect that is strongest in areas affected by environmental degradation and land scarcity.
Preprocessing ( a ) Low-Pass Filter Noise Filter Decoding ( c ) Feature Extraction ( b ) " Hello , how ' re you ? " Text Accoustic Models

Automatic speech recognition and voice identification systems are being deployed in a wide array of applications, from providing control mechanisms to devices lacking traditional interfaces, to the automatic transcription of conversations and authentication of users. Many of these applications have significant security and privacy considerations. We develop attacks that force mistranscription and misidentification in state of the art systems, with minimal impact on human comprehension. Processing pipelines for modern systems are comprised of signal preprocessing and feature extraction steps, whose output is fed to a machine-learned model. Prior work has focused on the models, using white-box knowledge to tailor model-specific attacks. We focus on the pipeline stages before the models, which (unlike the models) are quite similar across systems. As such, our attacks are black-box and transferable, and demonstrably achieve mistranscription and misidentification rates as high as 100% by modifying only a few frames of audio. We perform a study via Amazon Mechanical Turk demonstrating that there is no statistically significant difference between human perception of regular and perturbed audio. Our findings suggest that models may learn aspects of speech that are generally not perceived by human subjects, but that are crucial for model accuracy. We also find that certain English language phonemes (in particular, vowels) are significantly more susceptible to our attack. We show that the attacks are effective when mounted over cellular networks, where signals are subject to degradation due to transcoding, jitter, and packet loss.
Make or Break : Business Model Determinants of FinTech Venture Success

In recent years, the phenomenon of rapidly proliferating FinTech companies along diverse segments of the financial services value chain has attracted considerable interest in academic research and practice. So far, various factors of FinTech venture success have been explored, but there is little empirical insight through the lens of business model theory. To close this gap, we build on a FinTech business model taxonomy and examine 221 FinTech companies in order to statistically infer crucial business model determinants responsible for FinTech venture success. Our findings show that the business model component “Product/Service Offering” is the most important determinant for the success of a FinTech venture.
Cutting Time Prediction Methods in Cheese Making

Cheese is defined as the fresh or ripened product obtained by coagulation of milk and subsequent separation of the liquid and solid phases constituting the milk coagulum called whey and curd, respectively. The curd is further processed into cheese. Formation of a milk gel and cutting the gel into curd grains to allow whey separation are two major unit operations in cheese making. The first step of gel formation consists of casein micelle colloidal destabilization owing to chemical modification of the protective k-casein hairy coat by the coagulating agents. The second step consists of aggregation of the destabilized casein micelles to form the gel network. Further cross-linking of casein micelles results in the development of a firm gel. For most cheese types, whey and curd separation does not take place spontaneously and requires cutting the gel into small cubes (curd grains). This operation increases the gel surface/volume ratio, allowing the whey to escape while curd grains contract.
The European Centre forMedium ‐ Range Forecasts Reanalysis ‐ 40 andNational Centers for Environmental Prediction ( NCEP ) / Department of Energy reanalyses are downscaled over the eastern Caribbean and Lesser Antilles using the NCEP ‐ Scripps Regional Spectral Model

[1] The European Centre forMedium‐Range Forecasts Reanalysis‐40 andNational Centers for Environmental Prediction (NCEP)/Department of Energy reanalyses are downscaled over the eastern Caribbean and Lesser Antilles using the NCEP‐Scripps Regional Spectral Model for Augusts when the Atlantic Warm Pool (AWP) area is the most anomalous. The simulations show a two‐way influence between the Lesser Antilles and the AWP: the islands modulate the regional atmospheric circulation, and AWP variations modulate the interannual variabilities of the islands. The Lesser Antilles introduce diurnal variations and drag to the easterlies. The presence of the islands modulates the prevalent easterlies as a result of the daytime heating of the islands and the consequent boundary layer expansion. The modulations are sensitive to the islands’ size and topography. Small and flat islands act as thermal plumes, but the modulations of large and hilly islands are during the daytime as their boundary layer expands. The manifestation of the atmospheric response to the sea surface temperature (SST) anomalies over the islands is sensitive to the island orography. For most islands, the atmospheric response to the SST anomalies is reflected only during the daytime. For all one‐grid‐point islands and Antigua, nighttime and dawn minimum temperatures are modulated to the same degree as the daytime maximum. For island rainfall, downscaling reduces the gross overestimations of rainfall in the reanalyses. However, our downscaling results suggest that there is room for improvement in simulating the marine surface diurnal cycle.
"Your hashed IP address: Ubuntu.": perspectives on transparency tools for online advertising

Ad personalization has been criticized in the past for invading privacy, lack of transparency, and improper controls offered to users. Recently, companies started to provide web portals and other means for users to access data collected about them. In this paper, we study these new transparency tools from multiple perspectives using a mixed-methods approach. Still practices of data sharing barely changed until recently when new legislation required all companies to grant individual access to personal data stored about them. Using a mixed-methods approach we study the benefits of the new rights for users. First, we analyze transparency tools provided by 22 companies and check whether they follow previous recommendations for usability and user expectations. Based on these insights, we conduct a survey with 490 participants to evaluate three common approaches to disclose data. To complement this user-centric view, we shed light on the design decisions and complexities of transparency in online advertising using an online survey (n = 24) and in-person interviews (n = 8) with experts from the industry. We find that newly created transparency tools present a variety of information to users, from detailed technical logs to high-level interest segment information. Our results indicate that users do not (yet) know what to learn from the data and mistrust the accuracy of the information shown to them. At the same time, new transparency requirements pose several challenges to an industry that excessively shares data that even they sometimes cannot relate to an individual.