Labor-intensive Part Research Articles

Building ESP Corpus-driven Specialized Words in Vocational Education in Saudi Arabia

Both corpus revolution and advances in computer-based technologies have a remarkable impact on teaching and learning English as well as corpus studies. Nevertheless, Jablonkai (2020) observed that professional or occupational programs are less studied or researched compared to academic focus courses. Therefore, this paper is based on a replication study of Coxhead and Demecheleer (2018, cited in Jablonkai and Csomay, 2023) to develop ESP corpus-driven specialized words in vocational education. This process is tackled in three main phases: collection, computerization, and annotation of data. Data collection will be in mixed method from written and spoken ESP corpuses before using qualitative and quantitative analysis to measure frequency, key words and concordance comparing with other ESP corpora. The computerization phase will be based on lexical frame analysis (LFA) framework to convert a text to corpus, and this is quite labor-intensive part of creating the corpus. Finally, the annotation phase includes further lexical information covering semantic, pragmatic, and syntactic details. The first phase, data collection and analysis, will be reflected in Coxhead and Demecheleer's (2018) and the remaining two phases, annotating and computerizing data, will be elaborated through using LFA with two similar Business English corpora, PROLEX and PROCOMPARE, cited in Vincent (2009). The findings and conclusion of using three corpora could be effective in conducting this study as a preparation for creating a comprehensive technical corpus covering specialized words for all oil industry majors in my context. Further research could be conducted in the service of replication studies and expanding areas of ESP and vocabulary research using corpora.

Reliability of river fleet vessels hull elements

Improving the process of fault detection of metal ship hull elements by using a probabilistic approach is considered in the paper. The most labor-intensive part of the defect detection report, namely, measurement and assessment of hull structures individual elements wear, accounting for more than 90 % of the total measurements, is reviewed. Defect detection of a ship hull means the examination, measurement and assessment of defects in each element of the ship hull in order to establish method and volumes of repairs that ensure its reliable operation until the next survey under specified operating conditions. The necessity of carrying out a preliminary calculation stage for defect detection is substantiated. It allows you to significantly reduce the number of measurements of hull structures elements, which will have a positive effect on reducing the cost of repair both due to a smaller number of measurements and the duration of repairs. It has been proved that using the probability approach to predict the residual thickness of individual elements also takes into account the effect on the total strength, which guarantees the reliability of the ship hull in operation. Tables to assess the technical condition of individual hull elements based on their level of wear have been developed, and a method for filling them has improved. The tables are made in two versions, namely, paper and electronic, the most convenient for a specific user — the designer of the defect detection report tables. A test example of using the electronic tables for assessing technical condition by wear level, which proves that the predicted residual thicknesses obtained by calculation will in all cases, be less, than similar ones obtained from measurements results, is carried out using a representative vessel. This proves the reliability and feasibility of using the preliminary defect detection stage, which is essentially an analogue of the concept of the zero stage in ship repair. Using the probability approach to determine the residual thicknesses will allow you not only to reduce the costs of defect detection of the hull itself, but also at early stages (before placing the ship on a slip or dock) to reduce the volume of hull structures repairs, and to choose the most appropriate and effective method of repair.

MODERNIZATION OF BOTTOM SEDIMENT SCOURING PROCESS IN RVSP 20000 TANKS

According to the existing norms a tank should be necessarily taken out of operation once in 8-10 years for diagnostic works. The most labor-intensive part is removal of paraffin deposits from its bottom. In this regard, the main purpose of the study is to study the technology of the process of scouring bottom sediments in steel vertical cylindrical tanks with a pontoon volume of 20000 m3 (RVSP 20000) and modeling the operation of various cleaning devices to determine the most effective of them.
 The RVSP 20000 tank includes a device for bottom sediment scouring «DIOGEN-700». In the process of its operation under the action of the rotating blade of the propeller a jet of liquid is created, which mixes oil in the tank due to circular movement of streams. The greatest ac- cumulation of paraffin trace is observed in the-near-wall zone of the tank, therefore there is a need to find a new method of hydromechanical prevention of sludge accumulation on the bottoms of oil tanks.
 As the main device for bottom cleaning it is proposed to use a stirring jet device («UPS-EVNAT»). It divides one main stream into several equal parts. As a result, the area of sediment scouring is higher than when using standard equipment.
 In this work, the turbulent string flow with the use of screw agitator «DIOGEN-700» and with the use of «UPS-EVNAT» was modeled. The revealed results allow to assert that the application of agitating jet device allows to realize better quality erosion of paraffin deposits and cover a larger area in comparison with «DIOGEN-700».

Design and Test of an Automatic Navigation Fruit-Picking Platform

With the development in agricultural mechanization and information technology, orchard agricultural machinery is also constantly pursuing the goal of intelligence and efficiency. Fruit picking is the most labor-intensive part of the orchard harvesting process. In order to resolve the problems of high labor intensity, low picking efficiency, and labor shortage when harvesting dwarf high-density orchards, an automatic navigation fruit-picking platform with voice control was developed in the present study. First, the platform utilized a voice-controlled high-level extendable working platform and a fruit-box-lifting device to adapt to varying orchard planting row spacing and enable convenient fruit box loading and unloading. Second, an automatic navigation system, which employed China’s Beidou navigation satellite system to acquire positional data and the Stanley algorithm for path-tracking control, was implemented. Third, the fruit-picking platform with automatic navigation system was fabricated and assembled, its outer wheel steering was measured to have a maximum angle of 30.3° and an average minimum turning radius of 4.5 m, meeting the turning radius requirements under orchard conditions. Finally, automatic navigation tests of the developed platform were performed in the orchard conditions. The results indicated that the platform could maintain a straight-line path with a maximum lateral deviation of 101.5 mm and a maximum absolute average deviation of 44.1 mm at 0.4 m/s. Under the U-shaped paths, the measured maximum lateral deviation was 148.6 mm and the maximum absolute average deviation was 57.2 mm. The navigation accuracy was sufficient to meet the requirements for the harvesting platform’s routine operation in the orchards.

Probabilistic Pareto plan generation for semiautomated multicriteria radiation therapy treatment planning

Objective. We propose a semiautomatic pipeline for radiation therapy treatment planning, combining ideas from machine learning–automated planning and multicriteria optimization (MCO). Approach. Using knowledge extracted from historically delivered plans, prediction models for spatial dose and dose statistics are trained and furthermore systematically modified to simulate changes in tradeoff priorities, creating a set of differently biased predictions. Based on the predictions, an MCO problem is subsequently constructed using previously developed dose mimicking functions, designed in such a way that its Pareto surface spans the range of clinically acceptable yet realistically achievable plans as exactly as possible. The result is an algorithm outputting a set of Pareto optimal plans, either fluence-based or machine parameter–based, which the user can navigate between in real time to make adjustments before a final deliverable plan is created. Main results. Numerical experiments performed on a dataset of prostate cancer patients show that one may often navigate to a better plan than one produced by a single-plan-output algorithm. Significance. We demonstrate the potential of merging MCO and a data-driven workflow to automate labor-intensive parts of the treatment planning process while maintaining a certain extent of manual control for the user.

Egy LC-MS/MS alapú élelmiszervizsgálati módszer nemzetközi szabványosítása: egységesen elfogadott vizsgálati eljárás kidolgozása Alternaria toxinokra

There are more than seventy varieties of Alternaria toxins, but researchers have so far identified only a few of them structurally. The objective of this paper is to present a nearly ten-year process, during which an international standard for the simultaneous analysis of five Alternaria toxins in food samples was developed. This long process includes the development of the need for the standard and, in addition to the preparation and evaluation of the standardization tender, the development of the method, its validation and documentation. The paper focuses mainly on the development and validation of the analytical method, which is the longest and most labor-intensive part of the process, but in order to understand the overall picture, it is also necessary to emphasize the first and final steps. The development of a standard is a task of great responsibility for both the preparers of the standard and those involved in the validation and documentation of the standard, as the use of standardized methods is expected by the customers of the laboratories. On the other hand, laboratories that choose unique, self-developed methods can ascertain the accuracy and precision of their procedure by comparing them with the standard method. In this process that went on for nearly ten years, the original analytical method underwent several changes; the goal of these improvements was to make the procedure as simple and reproducible as possible. This is how the use isotope dilution mass spectrometry was reached through derivatization. It is important to emphasize that one of the goals of standardization is to have an appropriate analytical method available to authority laboratories for the testing of legally prescribed food contaminants, which procedure is available to any laboratory, however, it is questionable, whether the cost of the test covers its application. Consequently, it is not necessarily the most cost-effective analysis which is recommended by the standard, which may be the cause of conflict between the professional and economic managers of a laboratory in the case of private laboratories. The final form of the liquid chromatography/isotope dilution mass spectrometry (LC-IDMS) standard method developed for Alternaria toxins is likely to be approved and published by the European Committee for Standardization (CEN) in the end of 2021 (the standard has been issued since the article was submitted: CEN EN 17521:2021 Foodstuffs - Determination of Alternaria toxins in tomato, wheat and sunflower seeds by SPE clean-up and HPLC-MS/MS. The Editor). The standard will contain the determination of tenuazonic acid (TEA), altenuane (ALT), alternariol (AOH), tentoxin (TEN) and alternariol monomethyl ether (AME).

Part-Level Car Parsing and Reconstruction in Single Street View Images.

Part information has been proven to be resistant to occlusions and viewpoint changes, which are main difficulties in car parsing and reconstruction. However, in the absence of datasets and approaches incorporating car parts, there are limited works that benefit from it. In this paper, we propose the first part-aware approach for joint part-level car parsing and reconstruction in single street view images. Without labor-intensive part annotations on real images, our approach simultaneously estimates pose, shape, and semantic parts of cars. There are two contributions in this paper. First, our network introduces dense part information to facilitate pose and shape estimation, which is further optimized with a novel 3D loss. To obtain part information in real images, a class-consistent method is introduced to implicitly transfer part knowledge from synthesized images. Second, we construct the first high-quality dataset containing 348 car models with physical dimensions and part annotations. Given these models, 60K synthesized images with randomized configurations are generated. Experimental results demonstrate that part knowledge can be effectively transferred with our class-consistent method, which significantly improves part segmentation performance on real street views. By fusing dense part information, our pose and shape estimation results achieve the state-of-the-art performance on the ApolloCar3D and outperform previous approaches by large margins in terms of both A3DP-Abs and A3DP-Rel.

Using a neural network-based feature extraction method to facilitate citation screening for systematic reviews

Citation screening is a labour-intensive part of the process of a systematic literature review that identifies citations eligible for inclusion in the review. In this paper, we present an automatic text classification approach that aims to prioritise eligible citations earlier than ineligible ones and thus reduces the manual labelling effort that is involved in the screening process. e.g. by automatically excluding lower ranked citations. To improve the performance of the text classifier, we develop a novel neural network-based feature extraction method. Unlike previous approaches to citation screening that employ unsupervised feature extraction methods to address a supervised classification task, our proposed method extracts document features in a supervised setting. In particular, our method generates a feature representation for documents, which is explicitly optimised to discriminate between eligible and ineligible citations.The generated document representation is subsequently used to train a text classifier.Experiments show that our feature extraction method obtains average workload savings of 56% when evaluated across 23 medical systematic reviews. The proposed method outperforms 10 baseline feature extraction methods by approximately 6% in terms of the WSS@95% metric.

PET segmentation of bulky tumors: Strategies and workflows to improve inter-observer variability.

BackgroundPET-based tumor delineation is an error prone and labor intensive part of image analysis. Especially for patients with advanced disease showing bulky tumor FDG load, segmentations are challenging. Reducing the amount of user-interaction in the segmentation might help to facilitate segmentation tasks especially when labeling bulky and complex tumors. Therefore, this study reports on segmentation workflows/strategies that may reduce the inter-observer variability for large tumors with complex shapes with different levels of user-interaction.MethodsTwenty PET images of bulky tumors were delineated independently by six observers using four strategies: (I) manual, (II) interactive threshold-based, (III) interactive threshold-based segmentation with the additional presentation of the PET-gradient image and (IV) the selection of the most reasonable result out of four established semi-automatic segmentation algorithms (Select-the-best approach). The segmentations were compared using Jaccard coefficients (JC) and percentage volume differences. To obtain a reference standard, a majority vote (MV) segmentation was calculated including all segmentations of experienced observers. Performed and MV segmentations were compared regarding positive predictive value (PPV), sensitivity (SE), and percentage volume differences.ResultsThe results show that with decreasing user-interaction the inter-observer variability decreases. JC values and percentage volume differences of Select-the-best and a workflow including gradient information were significantly better than the measurements of the other segmentation strategies (p-value<0.01). Interactive threshold-based and manual segmentations also result in significant lower and more variable PPV/SE values when compared with the MV segmentation.ConclusionsFDG PET segmentations of bulky tumors using strategies with lower user-interaction showed less inter-observer variability. None of the methods led to good results in all cases, but use of either the gradient or the Select-the-best workflow did outperform the other strategies tested and may be a good candidate for fast and reliable labeling of bulky and heterogeneous tumors.

An automated solid phase extraction procedure for lipid biomarker purification and stable isotope analysis

Effective recovery and high purity of lipid biomarkers are essential for compound-specific stable isotope analysis in a variety of fields ranging from hydrocarbon research, paleoclimatology, food and drug analysis and medicine. Solid-phase extraction (SPE) is the most common method for purifying organic compounds from complex mixtures. SPE constitutes the most labor-intensive part of laboratory work often limiting the number of samples that can be analyzed. Reliable, easy-to-use, automated methods could increase sample throughput as well as reproducibility. Here we introduce such a method using a Gilson ASPEC GX-271 system and test the separation quality, reproducibility, and efficiency in comparison to a classical manual SPE lipid purification procedure. Using multiple extractions of the same natural soil sample we show that the automated SPE is comparable in overall quality and slightly superior in reproducibility to a manual SPE. We demonstrate that stable hydrogen isotope measurements of n-alkanes purified using an automated SPE extraction showed significantly lower standard errors. Furthermore, the unattended operation of the system eases the purification of large sample sets. Generally, the automated SPE using the Gilson ASPEC GX-271 for lipid biomarker separation provides qualitatively and quantitatively accurate and reproducible results with more efficient purification of compounds than the manual method.

МЕТОДЫ КОНТРОЛЯ ВНУТРЕННЕЙ ПОЛОСТИ ОХЛАЖДАЕМЫХ ЛОПАТОК ТВД С ПЕРСПЕКТИВНЫМИ СИСТЕМАМИ ОХЛАЖДЕНИЯ

The cooled turbine blades are very complex, labor-intensive parts, both for manufacturing and for inspection. With the development of aviation gas-turbine engines, the design of cooled turbine blades is becoming more complicated. To create new promising cooled turbine blades requires the introduction of new advanced manufacturing technologies and new progressive methods of dimensional control. This paper discusses the existing methods of inspection, which are used in the manufacture of turbine blades in mass production. Their advantages and disadvantages are given. The results of the work carried out in the framework of the international project "AERO.UA" are presented. The work was carried out to develop the inspection method of the internal cavity of the high-pressure turbine (HPT) blade with a promising cooling system developed at Ivchenko-Progress. The inspection of the internal cavity of the HPT blade with a promising cooling system was performed using computed tomography. Computed tomography performed at the Air Force Institute of Technology (ITWL) Warsaw on the General Electric X-Ray phoenix V | tome | X m tomograph. According to the results of testing the inspection method, the possibility of identifying manufacturing defects, the detection of which under the conditions of steady-state production is associated with very labor-intensive operations, is shown, and in some cases, inspection is impossible at all without destroying the part or performing expensive repairs. An assessment was made of the possibility of monitoring the geometrical dimensions of the internal cavity and external surfaces of cooled turbine blades. With the use of computed tomography, the dimensional control is possible with an accuracy of 0.01 mm. But to bind the blades to the base surfaces specified in the drawing when scanning, you must use a special snap. To confirm the possibility of controlling the dimensions specified in the drawing, it is necessary to continue work on scanning the cooled turbine blades using special tools.

Rapid electrophoretic recovery of DNA from dried blood spots.

Large-scale genetic screening of neonatal dried blood spots for episomal DNA has a great potential to lower patient mortality and morbidity through early diagnosis of primary immunodeficiencies. However, DNA extraction from the surface of dried blood spots remains one of the most time consuming, costly, and labor-intensive parts of DNA analysis. In the present study, we developed and optimized a rapid methodology using only 50V and heat to extract episomal DNA from dried blood spots prepared from diagnostic cord blood samples. This electric field DNA extraction is the first methodology to use an electric field to extract episomal DNA from a dried blood spot. This 25-minute procedure has one of the lowest times for the extraction of episomal DNA found within the literature and this novel procedure not only negates the need for costly treatment and wash steps, but reduces the time of manual procedures by more than 30 min while retaining the 75-80% of the yield. Combined with real-time PCR, this novel method of electric field extraction not only provides an effective tool for the large scale genetic analysis of neonates, but a key step forward in the simplification and standardization of diagnostic testing.

Automatic migration velocity estimation for prestack time migration

Migration velocity analysis is a labor-intensive part of the iterative prestack time migration (PSTM) process. We have developed a velocity estimation scheme to improve the efficiency of the velocity analysis process using an automatic approach. Our scheme is the numerical implementation of the conventional velocity analysis process based on residual moveout analysis. The key aspect of this scheme is the automatic event picking in the common-reflection point (CRP) gathers, which is implemented by semblance scanning trace by trace. With the picked traveltime curves, we estimate the velocities at discrete grids in the velocity model using the least-squares method, and build the final root-mean-square (rms) velocity model by spatial interpolation. The main advantage of our method is that it can generate an appropriate rms velocity model for PSTM in just a few iterations without manual manipulations. In addition, using the fitting curves of the picked events in a range of offsets to estimate the velocity model, which is fitting to a normal moveout correction, can prevent our scheme from the local minima issue. The Sigsbee2B model and a field data set are used to verify the feasibility of our scheme. High-quality velocity model and imaging results are obtained. Compared with the computational cost to generate the CRP gathers, the cost of our scheme can be neglected, and the quality of the initial velocity is not critical.

Rapid Recovery of DNA from Dried Blood Spots: Use of a Novel Electrophoretic Method

The demand for rapid, effective point of care diagnostics has created a pressing need for new and improved methods to quantify DNA from patient samples. Dried blood spotting is a well‐established testing methodology that has gained increasing importance in in vitro diagnostics due to its low cost, low sampling requirements, and long‐term sample stability. In recent years, dried blood spots have been increasingly used for targeted genetic and metabolite profiling. Large‐scale genetic screening of neonatal dried blood spots has a great potential to lower patient mortality and morbidity through early diagnosis of primary immunodeficiencies. However, DNA extraction from the surface of the dried blood spot remains the most time consuming, costly and labor‐intensive part of DNA analysis. Thus, the objective of this study was to develop and optimize a simple and rapid methodology to extract DNA from dried blood spots.In the present study, we created a novel methodology to extract DNA from a dried blood spot using only a lysis buffer (10mM KOH/30mM Tris buffer), 50V, and heat. Briefly, during the electric field extraction spots and lysis buffer were placed in an electroporation cuvette and DNA was extracted by applying 25–50 volts across the plates of the cuvette. The spot was then removed and DNA in the supernatant was analyzed using qPCR or fluorescent nucleic acid stains. This methodology was optimized by the addition of a 70°C heating step before the electric field extraction to better retrieve episomal DNA.This electric field DNA extraction is to our knowledge, the first methodology to use an electric field to extract episomal DNA from a dried blood spot. Results of this study show that this methodology produces significant recoveries of both genomic and episomal DNA (Ct (FAM) 33.0 (50V, 60s) to Ct (FAM) 35.0 (heating alone) p &lt;0.01). Varying recoveries of episomal and genomic DNA were also seen at different voltage conditions suggesting that this methodology may be useful for the isolation and purification of episomal DNA (FAM (25V, 300s (no amplification) and 50V, 60s (Ct 33.0)). Furthermore, preliminary qualitative and spectroscopic analyses suggest that protein removal could be achieved using this dual voltage technique. The 25‐minute electric field extraction procedure has one of the lowest times for the extraction of DNA found within the literature. This optimized procedure negates the need for costly treatment and wash steps, simplifying DNA extraction considerably. Most importantly, the electric field extraction reduces the time of proprietary procedures by more than 30 minutes, while retaining 75–80% of the yield. Thus, the results show that this novel method of electric field extraction provides a rapid and effective protocol to remove episomal and genomic DNA from dried blood spots. This optimized electric field device not only simplifies bioanalytical techniques, but provides a significant step towards point of care diagnostics and should be expanded to other sample types.Support or Funding InformationThe authors thank PerkinElmer for providing the funding for this study.This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal.

Recent advances in microextraction procedures for determination of amphetamines in biological samples.

Amphetamine and its related derivatives have stimulant and hallucinogenic properties. Illegal use of these drugs is an increasing global problem resulting in significant public health and legal problems. Deaths have been reported after intake of these drugs due to overdose. It is important to determine the type and concentration of illicit drugs in biological samples. These compounds are found in complex matrices at low concentration levels. The microextraction techniques are dominant sample preparation procedure and they are widely accepted as the most labor-intensive part of the bioanalytical process. For this purpose, a survey of recent published advances in microextraction procedures for quantification of amphetamines in biological samples found in the different databases from 2008 to date will be conducted.

Production and Marketing Challenges of Handicraft Products with Special Reference to Wood Craft

Handicrafts sector means those sectors producing products in hands with lower use of technologies and machines. The Indian handicraft sector is majorly labour intensive part of small scale business. The industry is spread all over the country from east to west and from north to south most of the manufacturing units are located in rural and in small towns. The handicraft statistically forms the second largest source of unorganised sector employment in India. Handicraft sector got boost since the new Economic Philosophy of Inclusive Growth has been initiated as a route to success towards sustainability by the government of India. The concept of inclusive growth says for the firmness of Indian economy all sectors of economy including handicraft must be given equal magnitude and for the inclusive growth both rural and urban sector must be given proper attention. While in India rural economy is the backbone as well as the vital of growth of the economy at all so it must be given most priority

Vehicle joint make and model recognition with multiscale attention windows

Vehicle Make and Model Recognition (VMMR) deals with the problem of classifying vehicles whose appearance may vary significantly when captured from different perspectives. A number of successful approaches to this problem rely on part-based models, requiring however labor-intensive parts annotations. In this work, we address the VMMR problem proposing a deep convolutional architecture built upon multi-scale attention windows. The proposed architecture classifies a vehicle over attention windows which are predicted to minimize the classification error. Through these windows, the visual representations of the most discriminative part of the vehicle are aggregated over different scales which in fact provide more representative features for the classifier. In addition, we define a loss function accounting for the joint classification error across make and model. Besides, a training methodology is devised to stabilize the training process and to impose multi-scale constraints on predicted attention windows. The proposed architecture outperforms state-of-the-art schemes reducing the model classification error over the Stanford dataset by 1.7 % and improving the classification accuracy by 0.2 % and 0.3 % on model and make respectively over the CompCar dataset.

Comparison of volume and stand table estimates with alternate methods for selecting measurement trees in point samples

Point sampling, which does not require measuring plot area, is an efficient sampling approach for forest inventory. However, in order to estimate stand volume and stand tables, it is necessary to take tree measurements, which is the most time-consuming and labour-intensive part of the field work. In this study, we compared three methods for selecting measurement trees, including Big basal-area factor (BAF), measuring every tree on every fourth point, and randomly selecting two trees on every point. Total stand volume and stand tables were estimated in nine 37.63-ha simulated loblolly pine plantations with varying levels of spatial heterogeneity. Results indicated that all three methods performed satisfactorily for estimating stand volume. Using number of trees selected at each sample point as a weight did not show a noticeable improvement for stand volume estimation when measurement trees were randomly selected. For stand tables estimation, number of trees in small-size classes were overestimated across the three tree-selection methods when binned sample data were used. However, if the exact expansion factor computed by dbh values recorded to the nearest 0.25 cm of each sample tree (i.e. unbinned sample data) was utilized in calculation of tree frequency, measurement trees selected by Big BAF or by measuring every tree on every fourth point provided reliable estimates of stand tables.

On the use of model-driven engineering principles for the management of simulation experiments

Simulation experiments are an essential part of computational science and engineering. The use of simulation models is widely adopted by practitioners from diverse areas of applied sciences. Nevertheless, simulations are rarely replicated due to reuse and maintenance challenges related to models and data. In this respect, we propose that crucial and labor intensive parts of simulation experiments could be supported by model transformations. This work focuses on model-driven engineering practices to enable replicable and reusable simulation experiments. These practices are used to devote researchers’ time to analyze the system under investigation rather than dealing with low level details to create a working environment. The results of our framework development work are presented.

Eyra - Speech Data Acquisition System for Many Languages

Speech data acquisition is particularly important for under-resourced languages. The data gathering is the most labour-intensive part of developing speech technologies such as automatic speech recognizers and synthesizers. It is therefore important to facilitate this process with as much automation and labour-cutting tools as possible. This paper describes a new open-source system called Eyra which enables distributed speech data collecting through a variety of devices. It addresses internet connectivity issues by allowing the data collectors to run the back-end server off a local laptop, thereby facilitating automatic quality control and less labour-intensive data uploading and compiling. It can also be used in a crowd-sourcing set-up where volunteers can donate voice samples through a desktop web-browser interface. An initial test shows that the system works well in an offline mode using smart-phones for data collection.