Miracle-dz/UniFAR-FTUs huggingface dataset:
An Efficient Technique for Solving Inhomogeneous Electromagnetic Inverse Scattering Problems

The electromagnetic inverse scattering approach seeks to obtain the electric characteristics of a scatterer using information about the source and the scattered data. The inverse scattering problem usually suffers from limited knowledge about the scatterer used, which makes its solution more challenging than the forward problem. This paper presents an inversion approach to estimating the unknown electric properties of a twoand three-dimensional inhomogeneous scatterer. The presented approach considers the inverse scattering problem as a global minimization problem with a meshless forward formulation for the computation of the scattered electromagnetic field. Various simulated annealing cooling schedules are applied and assessed to solve the problem, and the results of several case studies are presented for both twoand three-dimensional electromagnetic inverse scattering problems.
Enabling Data Processing under Erasure Coding in the Fog

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Enabling Data Processing under Erasure Coding in the Fog Jad Darrous, Shadi Ibrahim
A model of determinants for continuous usage of business intelligence in Malaysian manufacturing organizations using theoretical

Business Intelligence (BI) offered many advantages to organizations adopting the system such as improved decision making and boost organization’s performance. The lack of research on the continuous usage of BI in manufacturing motivates the initiative in this study to have an understanding of the determinants that influenced it. The study proposed a model of individual-related determinants that lead to the continuous usage of BI in manufacturing. A model integrating Unified Theory of Acceptance and Use of Technology (UTAUT) and Information System Continuance Model (ISCM) will be developed. The model will portray 20 hypotheses and 11 determinants leading continuance usage of BI. Data will be collected through survey questionnaires instrument and validated using Structural Equation Modelling (SEM). The result is hoping to show significant relationships between the determinants towards the continuous usage of BI in manufacturing. The study can potentially be used to guide manufacturers and practitioners for considerations in implementing BI in the manufacturing industry.
A surface deformation method based on stiffness control

© 2020 The Japan Society of Mechanical Engineers [DOI: 10.1299/jamdsm.2020jamdsm0010] Paper No.19-00256 Abstract Surface deformation operations commonly require the local details to be preserved as much as possible. In recent years, the As-Rigid-As-Possible(ARAP) shape deformation has gained popularity. Existing ARAP deformation methods define a local cell at each vertex as its 1-ring neighborhoods, and keep the deformation in each local cell as rigid as possible. Since the local cells of adjacent vertices share a single edge, the consistency between adjacent local rigid transformations maintains relative weak. In this paper, we define a new face-based local cell, which expands the overlapping areas between adjacent local cells, thereby enhancing the consistency of adjacent local rigid transformations. Based on this, we further present a stiffness control surface deformation method. The size of the proposed local cell controls global stiffness of the shape. For each local cell, a local stiffness parameter can be specified by the user or can be learned from a set of deforming models automatically to control the local deformation. Through adjusting the size of the local cell and local stiffness parameter, we can generate physically plausible, material-aware deformation results. Based on this local cell, we further propose a shape interpolation method, which has better performance and extrapolation capabilities. Experimental results demonstrate the effectiveness of our method.
Adaptability of the high first pod height, shattering-resistant soybean cultivar ‘Saegeum’ to mechanized harvesting

The soybean cultivar, ‘Saegeum’, has been developed for preparing soy-paste and tofu. The soybean cultivars ‘Daepung’ and ‘SS98207-3SSD-168’ were crossed in 2003 to obtain ‘Saegeum’. Single seed descent method was used to advance the generation from F3 to F5, and the plant lines with promising traits were selected from F6 to F7 by pedigree method. The preliminary yield (PYT) and advanced yield trials (AYT) were conducted from 2009 to 2010, and the regional yield trial (RYT) was conducted in 12 regions between 2011 and 2013. The morphological characteristics of ‘Saegeum’ were as follows: determinate plant type, white flower, tawny pubescence color, and brown pod color. Flowering and maturity dates were August 2, XXXX and October 17, XXXX, respectively. Plant height, first pod height, number of nodes, number of branches, and number of pods were 79 cm, 18 cm, 16, 2.3, and 44, respectively. The seed characteristics of ‘Saegeum’ were as follows: yellow spherical shape, yellow hilum, and the 100-seed weight was 25.4 g. ‘Saegeum’ was resistant to bacterial pustule and SMV in the field test, and its lodging resistance was mildly strong, whereas its shattering resistance was excellent. The ability of this cultivar to be processed into tofu, soybean malt, and other fermented products was comparable with that of ‘Daewonkong’. The yield of ‘Saegeum’ in the adaptable regions was 3.02 ton ha -1 . Thus, ‘Saegeum’ is adaptable to mechanized harvesting because of its high first pod height, as well as lodging and shattering resistance. (Registration number: 5929)
SCELMo: Source Code Embeddings from Language Models

Continuous embeddings of tokens in computer programs have been used to support a variety of software development tools, including readability, code search, and program repair. Contextual embeddings are common in natural language processing but have not been previously applied in software engineering. We introduce a new set of deep contextualized word representations for computer programs based on language models. We train a set of embeddings using the ELMo (embeddings from language models) framework of Peters et al (2018). We investigate whether these embeddings are effective when fine-tuned for the downstream task of bug detection. We show that even a low-dimensional embedding trained on a relatively small corpus of programs can improve a state-of-the-art machine learning system for bug detection.
Harmonic-balance circuit analysis for electro-neural interfaces

Objective. Avoidance of the adverse electrochemical reactions at the electrode-electrolyte interface defines the voltage safety window and limits the charge injection capacity (CIC) of an electrode material. For an electrode that is not ideally capacitive, the CIC depends on the waveform of the stimulus. We study the modeling of the charge injection dynamics to optimize the waveforms for efficient neural stimulation within the electrochemical safety limits. Approach. The charge injection dynamics at the electrode-electrolyte interface is typically characterized by the electrochemical impedance spectrum, and is often approximated by discrete-element circuit models. We compare the modeling of the complete circuit, including a non-linear driver such as a photodiode, based on the harmonic-balance (HB) analysis with the analysis based on various - (discrete-element) approximations. To validate the modeling results, we performed experiments with iridium-oxide electrodes driven by a current source with diodes in parallel, which mimics a photovoltaic circuit. Main results. Application of HB analysis based on a full impedance spectrum eliminates the complication of finding the discrete-element circuit model in traditional approaches. HB-based results agree with the experimental data better than the discrete-element circuit. HB technique can be applied not only to demonstrate the circuit response to periodic stimulation, but also to describe the initial transient behavior when a burst waveform is applied. Significance. HB-based circuit analysis accurately describes the dynamics of electrode-electrolyte interfaces and driving circuits for all pulsing schemes. This allows optimizing the stimulus waveform to maximize the CIC, based on the impedance spectrum alone.
Quality Characteristics of Seaweed (Kappaphycus alvarezii) Transparent Solid Soap with Different Glycerine Concentrations

Soap is a form of cosmetic preparation that is in demand by the public for the skin. This study aims to determine the optimum concentration of glycerin and determine the characteristics of transparent solid soap of seaweed produced. The research was carried out in April-October 2018. The making of soap uses three different of glycerin concentration (49 g, 59 g and 69 g). Based on the results of the study, seaweed transparant solid soap in accordance with Indonesian National Standarization 2016, except water content. Water content are 29.70%, 29.87%, and 39.77%. The best results for free fatty acid level testing were at glycerin concentration 59 g of 0.07%, the best results from non-soapy numbers were at glycerin concentration of 49 g and 69 g of 0.16%. The results of sensory analysis showed that the addition of glycerin 59 g was the best result based on the panelist's evaluation of the transparency parameter, while for the best impression the net concentration was based on the panelist's assessment of the addition of glycerin 49 g.
A Bi-Level Optimization Formulation of Priority Service Pricing

Priority service pricing is a promising approach for mobilizing residential demand response, by offering electricity as a service with various levels of reliability. Higher levels of reliability correspond to higher prices. Proper pricing guarantees that consumers self-select a level of reliability that corresponds to the reliability that the system can offer. However, the traditional theory for menu design is based on numerous stringent assumptions, which may not be respected in practice, such as well-behaved convex cost functions for generators. In this article, we design a priority service menu as the equilibrium solution to a Stackelberg game, which is modeled as a bi-level optimization problem involving a vertically integrated utility and consumers. We reformulate the equilibrium as a mixed-integer problem. As a consequence of this approach, we can integrate the menu design problem within a day-ahead unit commitment model. This allows us to design a menu which exactly meets the profit requirements of a firm. The approach is illustrated on a toy numerical example as well as a large-scale model of the Belgian power market.
Amélioration du processus de testabilité des circuits intégrés asynchrones dérivés de la topologie de conception d'Octasic

Les circuits asynchrones regroupent une grande variete de technique de conception. Octasic, une entreprise montrealaise, concoit des processeurs dedies au traitement de signal (DSP) qui exploitent une solution asynchrone particuliere de sa propre invention. La testabilite de ce type de circuit a deja fait l’objet de precedents travaux de recherche qui ont mene au developpement d’une premiere methode de test et d’algorithme d’analyse. Cependant, l’aspect de l’automatisation de cette methode qui est pourtant necessaire a sa democratisation n’a pour l’instant pas ete traite. Ce memoire propose donc d’ameliorer et d’automatiser autant que possible la methode de test precedemment developpee pour les circuits asynchrones qui utilisent la topologie de design des DSP d’Octasic. Contrairement a la methode de test initial, le processus developpe prend en charge la testabilite des machines a etats finis et la gestion des structures de reseau d’horloges complexe qui peuvent contenir des registres. A travers plusieurs circuits asynchrones de differentes complexites, on introduit un flot de testabilite en partie automatise qui debute a partir de la synthese et se deroule jusqu’a la simulation des vecteurs de tests. De plus, on y presente un programme capable d’analyser l’arrangement interne des circuits pour integrer et connecter les structures specifiques a la technique de test. Enfin, on y expose le processus de creation des procedures de test necessaire a la generation automatisee des vecteurs de test. Pour mesurer l’efficacite du flot de testabilite cree, des vecteurs de tests sont generes et simules. Les tests menes grâce a l’outil d’ATPG (Automatic Test Pattern Generator) et la simulation des vecteurs de test nous permettent d’obtenir un taux de couverture de pannes de 76.08%. Ces tests exploitent la technique du launch-on-capture a vitesse nominale sur notre circuit le plus complexe, un microprocesseur mini-MIPS asynchrone derive de l’architecture des DSP d’Octasic et implemente grâce a la technologie 45nm de Cadence.
Comparison of Heat Generation Models in Finite Element Analysis of Friction Welding

Comparison of Heat Generation Models in Finite Element Analysis of Friction Welding Richard Verile Livingston Department of Mechanical Engineering, BYU Master of Science Finite element models of friction welding can be used to estimate internal conditions of welds which are useful for weld analysis and developing experimental welding procedures. Many modeling techniques are used to accomplish these goals, each with relative strengths and weaknesses. A comparative analysis of friction welding models using different heat generation methods is presented. The three different heat generation methods examined were viscoplastic friction, constant steady-state generation, and experimentally measured power data. The models were compared against each other using three output measurements: temperature, axial force, and upset. The friction model predicted temperatures within 40◦C. Temperature accuracy improved at a higher upset rate and higher spindle speed, when weld samples heated up faster. The model was excellent at predicting upset, with accuracy within 1.5%. Maximum force was predicted within 9-18%. The constant heat generation model typically predicted temperatures within 30 ◦C. Upset was estimated within 7%. Maximum force was predicted within 12% at high feed rates, but accuracy dropped to 28% when feed rate was reduced. The motor power model was the most accurate model at estimating temperature, with a typical accuracy within 25◦C. Axial upset was predicted within 5%. Maximum force was predicted within 1-8%, with greater accuracy occurring at higher feed rates.
Fault diagnosis of reciprocating compressor based on group self-attention network

Reciprocating compressors are widely used in the petroleum industry and because of their complex and nonlinear signals, it is difficult to extract fault features. Recently, deep learning has been used in intelligent mechanical fault diagnosis and achieved great success. In the deep learning model, the recursive neural network (RNN) can capture global features, but it is difficult to parallelize and not good at dealing with long sequences. The convolutional neural network (CNN) can capture local features, but its receptive field is limited by the number of layers of the network and the size of the sliding window, resulting in the model not capturing sufficient features. In this paper, we propose a deep learning model without any RNN or CNN structures, called the group self-attention network (GSAN), for fault diagnosis of multisource signals in reciprocating compressors. The GSAN model mainly includes intra-group self-attention, inter-group self-attention and a fusion gate. Among them, intra-group self-attention is used to capture local features within a group, inter-group self-attention is used to capture global features between groups, and the fusion gate finally integrates these features. Experimental results show that compared with other models based on the RNN or the CNNs, the GSAN proposed in this paper not only has higher prediction accuracy, but also better anti-noise performance. In addition, the effectiveness of each part of the model is verified by ablation experiment.
Fecal Metabolomics Insights of Agavins Intake in Overweight Mice

Targeted and non-targeted metabolite profiling can identify biomarkers after a dietary treatment leading to a better understanding of interactions between diet and health. This study was conducted to establish enriched or depleted metabolites in the feces of overweight mice after a diet shift plus agavins or inulins supplementation, and their possible association with beneficial effects on host health. Thirty-eight male C57BL/6 mice were fed with a high-fat diet for 5 weeks followed by a diet shift to a standard diet supplemented with agavins (HF-ST + A) or inulins (HF-ST + I) for five more weeks. Feces were collected before and after prebiotic supplementation for metabolomics analyses. HF-ST + I group increased the fecal excretion of two methyl esters: linoleic and oleic acid, while HF-ST + A mice showed a substantial augment of 2-decenal, fructose, cyclohexanol, and the acids: 10-undecenoic, 3-phenyllactic, nicotinic, 5-hydroxyvaleric, and lactic. From the metabolites identified in HF-ST + A, only lactic acid has been reported previously and associated with beneficial effects on host health. However, the identification of new metabolites, coming from the microbial fermentation of agavins, opens opportunities to transform this information into practical solutions to tackle overweight and associated metabolic syndrome.
Employment-at-Will Exceptions, Social Welfare Programs and the Decline of Unions

Evidence from a fairly extensive literature in economics concludes that the adoption by state courts of exceptions to the common law employment-at-will doctrine has had far-reaching unintended impacts on firm behavior and labor market outcomes on several behaviorally distinct margins. We extend this literature by examining their unintended effects on union membership. Additionally, we examine the unintended effects on union membership that resulted from government adoption of union-like social welfare programs. Our results strongly suggest that these legal and policy interventions, which provide just-cause protections, social insurance and health and safety protections, have had the unintended effects of contributing to the long-run decline in union density.
Accurate playground localisation based on multi-feature extraction and cascade classifier in optical remote sensing images

ABSTRACT To address the low accuracy problem of playground detection under complex background, the accurate playground localization based on multi-feature extraction and cascade classifier is proposed in this paper. It is difficult to utilize this information to separate objects from the complex background. Therefore, we adopt multi-feature extraction method to make the playgrounds more easily to be detected. The proposed localization method is partitioned into two modules: feature extraction and classification. First, multi feature extraction method combining histogram of oriented gradients (HOG) and Haar is utilized to extract features from raw images. HOG can authentically capture the shape information, which is extracted to characterize the local region. Haar can improve the image eigenvalue calculation effectively. Afterwards, cascade classifier based on AdaBoost algorithm is adopted to classify the extracted features. Finally we conduct the experiments with our proposed methodology on a publicly accessible remote sensing images from Google Earth. The results demonstrate that the proposed framework has a better effect with achieving high levels of recall, precision and F-score compared to the state-of-the-art alternatives, without sacrificing computational soundness. What is more, the results indicate that the proposed playground 1ocalisation method has strong robustness under different complex backgrounds with high detection rate.
Improving technology of producing non-alcoholic drinks using non-traditional raw materials

Introduction. The technology for the production of soft drinks using non-traditional raw materials with the aim of improving and expanding the range of products was investigated. Materials and methods. Non-traditional raw materials were used to create the basis of a soft drink, in particular, strawberry and raspberry extract. The number of polyphenols in the objects of study were determined by spectrophotometric method. The optical density was measured in a cuvette with a layer thickness of 10 mm on a SF-46 spectrophotometer. Results and discussion. The content of phenolic compounds is crucial for the stability of beverages. The usіng of morphological particles of raw materials makes it possible not only to improve the sensory properties of beverages, but also to extend their stability. Raspberry powder extract (2.30 and 1.02) had better phenolic compounds and rutin content than strawberry powder extract (1.50 and 0.30). Available data indicate that the vegetative parts of plants contain no less biologically active substances, and sometimes even more than fruits, berries and vegetables, and their using allows to get concentrates and drinks from them with soft, piquant, harmoniously individual flavor and aroma. Focusing on the rich content of valuable components, the leaves and stems of raspberries and strawberries were investigated for the using of additives to the concentrate of soft drinks. 3 preparing raspberry is
Developing team based acute care scenarios: A rural hospital experience

abstract Background: Health professionals work in teams in a variety of health care settings especially in medicalemergency teams at times of crisis. However, Registered Nurses (RNs) rarely have the chance to partakein educational programs designed for teams of nurses to practice working together in life-threatening sit-uations. Further RN’s employed in rural setting have less opportunities for professional development thantheir city based counterparts. Simulated scenarios with a patient actor in a rural hospital have been uti-lised in this study to provide nurses with the opportunity to work as a team in the early recognition andmanagement of patients with acute medical conditions.Aim: This discussion paper focuses on one aspect of a larger research project with the aim of describingthe development of team based scenarios for a rural hospital setting, focusing on the detection and man-agement of a deteriorating patient.Methods: Three team based scenarios, the related assessments and feedback techniques are all described.Conclusion: Team based simulation provides a unique opportunity to assist registered nurses in rural set-tings in re-skilling or maintaining their emergency management skills. 2012 Elsevier Ltd. All rights reserved.