Čujni zvuk kao signal za izravnu kontrolu elektrolučnog procesa zavarivanja

In this paper sound generated during the gas-metal arc welding process was studded. Experimental analyses of the acoustic signals have shown that there are two main noise-generating mechanisms, first having impulse form is arc extinction and arc ignition; the second is the arc itself acting as an ionization sound source. The sound signal is used for assessing and monitoring of the welding process, and for prediction of welding process stability and quality. A new algorithm based on the measured welding current was established for the calculation of emitted sound during the welding process. The comparisons have shown that the calculated values are in good agreement with the measured values.U radu je istraživan čujni zvuk, koja se generira kod procesa elektrolučnog zavarivanja po MAG postupku. Eksperimentalna analiza zvučnog signala je pokazala, da se javljaju dva glavna mehanizma generiranja zvuka, prvi, koji ima karakter impulza, je posljedica paljenja i gašenja električnog luka (plazme); drugi je sam električni luk, koji djeluje kao ionizirajući izvor zvuka. Zvučni signal je upotrijebljen za ocjenjivanje i nadzor procesa zavarivanja, te za ocjenjivanje kvalitete i stabilnosti procesa zavarivanja. Razvijen je novi matematički model za izračun emitiranog zvuka kod procesa zavarivanja a koji bazira na izmjerenoj struji zavarivanja. Usporedba izračunanih i izmjerenih vrijednosti zvučnog signala je pokazala veliku suglasnost

RELPRON: A Relative Clause Evaluation Data Set for Compositional Distributional Semantics

This article introduces RELPRON, a large data set of subject and object relative clauses, for the evaluation of methods in compositional distributional semantics. RELPRON targets an intermediate level of grammatical complexity between content-word pairs and full sentences. The task involves matching terms, such as “wisdom,” with representative properties, such as “quality that experience teaches.” A unique feature of RELPRON is that it is built from attested properties, but without the need for them to appear in relative clause format in the source corpus. The article also presents some initial experiments on RELPRON, using a variety of composition methods including simple baselines, arithmetic operators on vectors, and finally, more complex methods in which argument-taking words are represented as tensors. The latter methods are based on the Categorial framework, which is described in detail. The results show that vector addition is difficult to beat—in line with the existing literature—but that an implementation of the Categorial framework based on the Practical Lexical Function model is able to match the performance of vector addition. The article finishes with an in-depth analysis of RELPRON, showing how results vary across subject and object relative clauses, across different head nouns, and how the methods perform on the subtasks necessary for capturing relative clause semantics, as well as providing a qualitative analysis highlighting some of the more common errors. Our hope is that the competitive results presented here, in which the best systems are on average ranking one out of every two properties correctly for a given term, will inspire new approaches to the RELPRON ranking task and other tasks based on linguistically interesting constructions.Laura Rimell and Stephen Clark were supported by EPSRC grant EP/I037512/1. Jean Maillard is supported by an EPSRC Doctoral Training Grant and a St. John’s Scholarship. Laura Rimell, Tamara Polajnar, and Stephen Clark are supported by ERC Starting Grant DisCoTex (306920)

Substrate-borne vibrations disrupt the mating behaviors of the neotropical brown stink bug, Euschistus heros: implications for pest management.

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Evolving Gaussian Process Kernels for Translation Editing Effort Estimation

In many Natural Language Processing problems the combination of machine learning and optimization techniques is essential. One of these problems is estimating the effort required to improve, under direct human supervision, a text that has been translated using a machine translation method. Recent developments in this area have shown that Gaussian Processes can be accurate for post-editing effort prediction. However, the Gaussian Process kernel has to be chosen in advance, and this choice in- fluences the quality of the prediction. In this paper, we propose a Genetic Programming algorithm to evolve kernels for Gaussian Processes. We show that the combination of evolutionary optimization and Gaussian Processes removes the need for a-priori specification of the kernel choice, and achieves predictions that, in many cases, outperform those obtained with fixed kernels.TIN2016-78365-

Using laser vibrometry to understand and exploit vibrational signals of insetcs

Vibrational communication is one of the least understood modes of communication in insects, and laser vibrometry has already proven a valuable tool in research on this subject. Lasers are used for real-time monitoring and recording of signalling behaviour, with the advantage of not mechanically loading the surface. This is of crucial importance because of low intensities and rapid amplitude modulation, characteristic of insect vibrational signals. Plant-dwelling insects that use green plant tissues as a signal transmission medium comprise several economically important pests. From recent advances in understanding of communication between mates in some of those species, there emerged an idea of using artificially induced vibrations to disrupt pair-forming behaviour and therefore prevent mating in the field. This idea, which is currently being developed, has potential to substitute chemical methods of pest control with a more environment-friendy approach in certain settings, such as vineyards and greenhouse

Developing an acoustic tool for mating disruption of Scaphoideus titanus (Hemiptera: Cicadellidae) = Razvoj akustične metode za motenje paritvenega vedenja ameriškega škržatka (Scaphoideus titanus; Hemiptera: Cicadellidae)

Leafhoppers (Hemiptera: Cicadellidae) rely exclusively on vibrational signals to guide their mating behaviour, which opens a possibility for innovative approaches to controlling pest populations. Artificially induced mechanical vibrations are, in principle, able to prevent mating by obscuring information about the emitter's location, identity and quality, contained in vibrational signals and necessary for mating success. We developed a proof of concept, targeting an invasive leafhopper species Scaphoideus titanus, which acts as a vector for the phytoplasma Flavescence dorée in grapevines. We used a disturbance signal, such as it is used by males of this species in rival interactions with other males, and transmitted it into plants using a minishaker or a loudspeaker playback. We tested efficiency and limitations of the technique in laboratory and semi-natural conditions, focusing on amplitude, diel pattern of activation and method of transmitting disturbance signals to host plants of S. titanus. Our ultimate goal is to develop an environmentally friendly technique for insect pest control that could replace pesticide use in certain settings, such as vineyards and greenhouse