Miracle-dz/UniFAR-FTUs huggingface dataset:
Symbolic-Numeric Reachability Analysis of Closed-Loop Control Software

We study the problem of falsifying reachability properties of real-time control software acting in a closed-loop with a given model of the plant dynamics. Our approach employs numerical techniques to simulate a plant model, which may be highly nonlinear and hybrid, in combination with symbolic simulation of the controller software. The state-space and input-space of the plant are systematically searched using a plant abstraction that is implicitly defined by ``quantization'' of the plant state, but never explicitly constructed. Simultaneously, the controller behaviors are explored using a symbolic execution of the control software. On-the-fly exploration of the overall closed-loop abstraction results in abstract counterexamples, which are used to refine the plant abstraction iteratively until a concrete violation is found. Empirical evaluation of our approach shows its promise in treating controller software that has precise, formal semantics, using an exact method such as symbolic execution, while using numerical simulations to produce abstractions of the underlying plant model that is often an approximation of the actual plant. We also discuss a preliminary comparison of our approach with techniques that are primarily simulation-based.
Review of research in the determination of process parameters for plastic injection molding

This article aims to review the research in determining process parameters of injection molding. A number of research works based on various approaches have been performed in the domain of the parameter setting for injection molding. These approaches, including mathematical models, numerical simulation, process windows, design of experiment (DOE), expert systems, Artificial Neural Networks (ANN), Case Based Reasoning (CBR), Genetic Algorithms (GA), and evolutionary strategies, are described in this article. The strength and the weakness of individual approaches are discussed. It is then followed by conclusions and discussions of the potential research in determining process parameters for injection molding. © 1999 John Wiley & Sons, Inc. Adv Polym Techn 18: 225–236, 1999
School Bullying in Twitter and Weibo: A Comparative Study

School-based bullying is a serious health issue among adolescents world wide. We identify several differences in microblogs of school-based bullying between Twitter (mostly representing the USA) and Weibo (mostly representing China). First, we see a smaller fraction of victim authors in Weibo than in Twitter. We hypothesize that this may be due to Asian culture's emphasis on saving face where it is more of a taboo to be a victim or label someone a victim. Second, we see different temporal dynamics of school bullying posts due to differences in holidays and length of school days. Finally, bullying posts from Weibo contain more mentions of family than those from Twitter. This may be due to the greater emphasis on family in Asian cultures.
Relation between friction and hardness

Although hardness has little effect on friction there is evidence that in general the friction is less with harder metals. Experiments on a carefully selected series of copper beryllium alloys show that the friction decreases linearly with the hardness. For a given load the amount of plastic deformation at the points of intimate contact is greater for a soft metal. It is suggested that this deformation facilitates disruption of the oxide film so that for softer metals the proportion of oxide-free junctions is greater. The resulting frictional force is therefore higher.
DEM by Ground-Based SAR Interferometry

In this letter, a ground-based synthetic aperture radar (SAR) interferometer was used to generate digital elevation maps (DEMs) of the illuminated area. With respect to other ground-based data processing techniques, here, the effect of the propagation through the atmosphere is considered. An algorithm similar to multipass satellite SAR techniques was developed in accordance with the phase model used in the ground-based interferometry. Many images taken from different viewing angles were collected and combined to form different interferograms at a test site in Austria. Results from this technique have been compared with an existing geographic model of the test area.
Thoughts on User Studies: Why, How and When

Visualization as currently practiced is mostly a craft. Methods are often designed and evaluated by presenting results informally to potential users. No matter how efficient a visualization technique may be, or how well motivated from theory, if it does not convey information effectively, it is of little use. User studies offer a scientifically sound method to measure a visualization’s performance. Although their use has become more widespread, we believe they have the potential for a much broader impact. This article describes our experiences with user studies. We offer some examples of our own studies, talk about the pitfalls and problems we encountered, and show how the results were applied to produce successful visualizations. Although our main goal is to encourage the use of studies in visualization, we recognize that other disciplines also offer important insights into visualization design, for example, the areas of visual design or the visual arts. We conclude by discussing when knowledge from these areas might be preferable to a traditional user study.
Simple and low cost method for metal-based micro-capillary channels for heat exchanger use

In this work, we present an alternative, low cost method for the fabrication of a heat exchanger utilizing metal-based microchannels using the UV-LiGA technique. Lithography is used to pattern dry film negative photoresist (Ordyl P-50100) on the substrate. The resist is laminated over the substrate and exposed with a UV source. The use of dry film resist allows for simple and inexpensive microchannel patterns without requiring advanced cleanroom equipment. Following the lithography process, electrodeposition of metals is used to fill the recesses patterned in the resist. In this work, nickel has been electroplated into the bounding resist structure. After electroplating, the remaining resist is dissolved leaving free standing metal structures. The fabricated exchanger is then evaluated based on thermal absorption of simulated waste heat sources and capillary action of the metal channels themselves. Channels are fabricated to heights of 60, 70 and 90 μm respectively on copper substrate using these methods. Working fluid mass transfer rate from the heated microchannel heat exchanger (MHE) is utilized as a basic metric of operation. The mass transfer rate recorded from the nickel-based MHE is 2.19, 2.81 and 3.20 mg s−1 respectively for the different channel heights. This implies an effective thermal power consumption rate of 1.66, 2.13 and 2.42 kW m−2 respectively. By contrast, an MHE fabricated with 115 and 142 μm tall channels on silicon substrate is shown to evaporate up to 2.84 and 3.04 mg s−1 respectively, giving an effective thermal power consumption of 2.15 and 2.31 kW m−2 respectively. An investigation of working fluid contact angle with the electroplated nickel surface is also presented. The surface is found to be a porous structure stemming from the electroplating process.
Correlation of Mechanical and Microstructural Properties in SMAW Welded Cr-Mo Boiler Steels Subjected to Different Post Weld Heat Treatment Soaking Times

Abstract: In the present work the effect of different durations of Post Weld Heat Treatment soaking times (0.5,2,10,50 hours) are analyzed on the mechanical and microstructural properties of Cr-Mo alloy steel of ASTM A387 Gr-22,2.25% Cr-1%Mo alloy steel. These are used in high temperature services in steam generation applications, Oil and Gas industries, Thermal and Nuclear power plants etc. The work is focused on different regions of weldment like base metal, HAZ and weld metal to compare and analyze the results obtained in as-welded and different soaking times from hardness test, tensile testing and microstructural examination. Results showed that the hardness varies from weld centre line to base metal and peak hardness was found in the HAZ. The hardness is reduced to large extent when PWHT is done at 50 h. Microstructural changes were observed during different post weld heat treatments and their effect on mechanical properties and best suitable soaking times were reported.
Achieving numerical accuracy and high performance using recursive tile LU factorization with partial pivoting

The LU factorization is an important numerical algorithm for solving systems of linear equations in science and engineering and is a characteristic of many dense linear algebra computations. For example, it has become the de facto numerical algorithm implemented within the LINPACK benchmark to rank the most powerful supercomputers in the world, collected by the TOP500 website. Multicore processors continue to present challenges to the development of fast and robust numerical software due to the increasing levels of hardware parallelism and widening gap between core and memory speeds. In this context, the difficulty in developing new algorithms for the scientific community resides in the combination of two goals: achieving high performance while maintaining the accuracy of the numerical algorithm. This paper proposes a new approach for computing the LU factorization in parallel on multicore architectures, which not only improves the overall performance but also sustains the numerical quality of the standard LU factorization algorithm with partial pivoting. While the update of the trailing submatrix is computationally intensive and highly parallel, the inherently problematic portion of the LU factorization is the panel factorization due to its memory‐bound characteristic as well as the atomicity of selecting the appropriate pivots. Our approach uses a parallel fine‐grained recursive formulation of the panel factorization step and implements the update of the trailing submatrix with the tile algorithm. Based on conflict‐free partitioning of the data and lockless synchronization mechanisms, our implementation lets the overall computation flow naturally without contention. The dynamic runtime system called QUARK is then able to schedule tasks with heterogeneous granularities and to transparently introduce algorithmic lookahead. The performance results of our implementation are competitive compared to the currently available software packages and libraries. For example, it is up to 40% faster when compared to the equivalent Intel MKL routine and up to threefold faster than LAPACK with multithreaded Intel MKL BLAS. Copyright © 2013 John Wiley & Sons, Ltd.
Knowledge Unit Relation Recognition Based on Markov Logic Networks

Knowledge unit (KU) is the smallest integral knowledge object in a given domain. Knowledge unit relation recognition is to discover implicit relations among KUs, which is a crucial problem in information extraction. This paper proposes a knowledge unit relation recognition framework based on Markov Logic Networks, which combines probabilistic graphical models and first-order logic by attaching a weight to each first-order formula. The framework is composed principally of structure learning, artificial add or delete formulas, weight learning and inferring. According to the semantic analysis of KUs and their relations, ground predicate set is first extracted. Next, the ground predicate set is inputted into structure learning module to achieve weight formula set. Then, in order to overcome limitations of structure learning, the weight rule set is added or deleted by human. The new weight formula set is turned into weight learning module to acquire the last weight formula set. Finally, knowledge unit relations are recognized by inferring module with the last weight formula set. Experiments on the four data sets related to computer domain show the utility of this approach. The time complexity of structure learning is also analyzed
Insights into wideband fractional All-Digital PLLs for RF applications

Technology scaling and large-scale integration make the operating environment increasingly hostile for traditional analog design. In the area of frequency synthesis, All-Digital PLLs (ADPLLs) provide an attractive alternative to conventional PLLs: their wide programmability allows for multistandard application, and a digital intensive design means easy reconfigurability and shorter design cycles. However, wideband fractional ADPLLs come with a different set of problems, principally in-band spurious tones. Techniques to suppress spurious tones would eliminate a major obstacle for ADPLLs' widespread proliferation into wireless RF applications. In this paper we first describe the evolution from the analog PLL to the divider-less ADPLL, of major interest for RF to date, then develop a model to predict location and level of spurs. Finally, we present a technique for spur reduction by means of digital calibration. Validation is performed through experiments on an ADPLL fabricated in 65nm digital CMOS.
Genome-wide associations for feed utilisation complex in primiparous Holstein-Friesian dairy cows from experimental research herds in four European countries.

Genome-wide association studies for difficult-to-measure traits are generally limited by the sample size with accurate phenotypic data. The objective of this study was to utilise data on primiparous Holstein–Friesian cows from experimental farms in Ireland, the United Kingdom, the Netherlands and Sweden to identify genomic regions associated with the feed utilisation complex: fat and protein corrected milk yield (FPCM), dry matter intake (DMI), body condition score (BCS) and live-weight (LW). Phenotypic data and 37 590 single nucleotide polymorphisms (SNPs) were available on up to 1629 animals. Genetic parameters of the traits were estimated using a linear animal model with pedigree information, and univariate genome-wide association analyses were undertaken using Bayesian stochastic search variable selection performed using Gibbs sampling. The variation in the phenotypes explained by the SNPs on each chromosome was related to the size of the chromosome and was relatively consistent for each trait with the possible exceptions of BTA4 for BCS, BTA7, BTA13, BTA14, BTA18 for LW and BTA27 for DMI. For LW, BCS, DMI and FPCM, 266, 178, 206 and 254 SNPs had a Bayes factor . 3, respectively. Olfactory genes and genes involved in the sensory smell process were overrepresented in a 500 kbp window around the significant SNPs. Potential candidate genes were involved with functions linked to insulin, epidermal growth factor and tryptophan.
Random Forests and Adaptive Nearest Neighbors

In this article we study random forests through their connection with a new framework of adaptive nearest-neighbor methods. We introduce a concept of potential nearest neighbors (k-PNNs) and show that random forests can be viewed as adaptively weighted k-PNN methods. Various aspects of random forests can be studied from this perspective. We study the effect of terminal node sizes on the prediction accuracy of random forests. We further show that random forests with adaptive splitting schemes assign weights to k-PNNs in a desirable way: for the estimation at a given target point, these random forests assign voting weights to the k-PNNs of the target point according to the local importance of different input variables. We propose a new simple splitting scheme that achieves desirable adaptivity in a straightforward fashion. This simple scheme can be combined with existing algorithms. The resulting algorithm is computationally faster and gives comparable results. Other possible aspects of random forests, such as using linear combinations in splitting, are also discussed. Simulations and real datasets are used to illustrate the results.
Interactive evolutionary multi-objective optimization and decision-making using reference direction method

In this paper, we borrow the concept of reference direction approach from the multi-criterion decision-making literature and combine it with an EMOprocedure to develop an algorithm for finding a single preferred solution in a multi-objective optimization scenario efficiently. EMO methodologies are adequately used to find a set of representative efficient solutions over the past decade. This study is timely in addressing the issue of optimizing and choosing a single solution using certain preference information. In this approach, the user supplies one or more reference directions in the objective space. The population approach of EMO methodologies is exploited to find a set of efficient solutions corresponding to a number of representative points along the reference direction. By using a utility function, a single solution is chosen for further analysis. This procedure is continued till no further improvement is possible. The working of the procedure is demonstrated on a set of test problems having two to ten objectives and on an engineering design problem. Results are verified with theoretically exact solutions on two-objective test problems.
Rank degree: An efficient algorithm for graph sampling

The study of a large real world network in terms of graph sample representation constitutes a very powerful and useful tool in several domains of network analysis. This is the motivation that has led the work of this paper towards the development of a new graph sampling algorithm. Previous research in this area proposed simple processes such as the classic Random Walk algorithm, Random node and Random edge sampling and has evolved during the last decade to more advanced graph exploration approaches such as Forest Fire and Frontier sampling. In this paper, we propose a new graph sampling method based on edge selection. In addition, we crawled Facebook collecting a large dataset consisting of 10 million users and 80 million users' relations, which we have also used to evaluate our sampling algorithm. The experimental evaluation on several datasets proves that our approach preserves several properties of the initial graphs, leading to representative samples and outperforms all the other approaches.
Micro-billing Framework for IoT: Research &amp; Technological Foundations

In traditional product companies, creating value meant identifying enduring customer needs and manufacturing well-engineered solutions. Two hundred and fifty years after the start of the Industrial Revolution, this pattern of activity plays out every day in a connected world where products are no longer one-and-done. Making money is not anymore limited to physical product sales, other downstream revenue streams become possible (e.g., service-based information, Apps). Nonetheless, it is still challenging to stimulate the IoT market by enabling IoT stakeholders (from organizations to an individual persons) to make money out of the information that surrounds them. Generally speaking, there is a lack of micro-billing frameworks and platforms that enable IoT stakeholders to publish/discover, and potentially sell/buy relevant and useful IoT information items. This paper discusses important aspects that need to be considered when investigating and developing such a framework/platform. A high-level requirement analysis is then carried out to identify key technological and scientific building blocks for laying the foundation of an innovative micro-billing framework named IoTBnB (IoT puBlication aNd Billing).
An ancient FMRFamide-related peptide–receptor pair induces defence behaviour in a brachiopod larva

Animals show different behaviors that can consist of various spatially or temporally separated sub-reactions. Even less complex organisms, like ciliated larvae that display important behaviors (e.g. metamorphosis, defense, feeding), need to coordinate coherent sub-reactions with their simple nervous system. These behaviors can be triggered by neuropeptides, which are short signaling peptides. Despite the high diversity of neuropeptides in animals, and although their immunoreactivity is widely used in morphological studies of animal nervous systems (e.g. FMRFamide), their function and role in trochozoan larval behavior has so far only been tested in a few cases. When mechanically disturbed, the planktonic larvae of the brachiopod Terebratalia transversa protrude their stiff and pointy chaetae in a defensive manner and sink down slowly: a startle reaction that is known from different chaetous trochozoan larvae. We found that both of these reactions can be induced simultaneously by the FMRFamide-related neuropeptide FLRFamide. We deorphanized the Terebratalia FLRFamide receptor and found its expression spatially separated in the apical lobe at the prototroch of the larvae and in the trunk musculature, which correlates with the tissues that are responsible to perform the two sub-reactions. A behavioral assay showed a decreasing efficiency of modified peptides in triggering this behavior, which correlates with the decreasing efficiency of activating the FLRFamide receptor in transfected CHO-K1 cells. Immunohistochemistry and in situ hybridization show FLRFamidergic neurons in the apical lobe as well as next to the trunk musculature. Our results show that the single neuropeptide FLRFamide can specifically induce the two coherent sub-reactions of the T. transversa startle behavior.
AR4AR Based on ARVIDA Reference Architecture: Application Demonstration

A recurring challenge when setting up any Augmented Reality system is integration as well as the correct calibration and registration of the involved devices. To gather, the input data the user has to interact with the system which requires certain knowledge on how to perform the task. It is possible the user performs the current task to the best of his knowledge and still produces suboptimal results. Augmented Reality for Augmented Reality (AR4AR) generates AR guides by using the already existing knowledge about the AR system which stems from the setup of the AR system itself. As these guides involve plenty of 3D information, it is again best presented through means of Augmented Reality, thus the name AR4AR.