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28 results for “supermarket”
Bonpreu-Esclat Online Supermarket Products
<p>Dataset obtingut capturant tots els productes que s'ofereixen al supermercat online de Bonpreu-Esclat. Durant aquesta captura, hem obtingut informació com: el nom del producte, el seu preu, la quantitat de producte, el preu per unitat de referència, cinc categories de classificació, si el producte es troba en oferta o no, quina promoció té, l'enllaç url del producte i la data en la que s’han obtingut els valors.</p>
Bonpreu-Esclat Online Supermarket Products
<p>Dataset obtingut capturant tots els productes que s'ofereixen al supermercat online de Bonpreu-Esclat. Durant aquesta captura hem obtingut informació com: el nom del producte, el seu preu, la quantitat de producte, el preu per unitat de referència, cinc categories de classificació, si el producte es troba en oferta o no, quina promoció té, l'enllaç url del producte i la data en la que s’han obtingut els valors. Les dades han estat capturades diàriament al llarg de la setmana del 02/11/2020 al 06/11/2020 i finalment s'han agrupat totes en un únic dataset on es pot veure l'evolució temporal de la informació continguda.</p>
Availability and trends in sports foods available for sale at New Zealand supermarketsy of sports foods globally and in New Zealand supermarkets
<p>Sports foods are specially formulated to help people achieve specific nutritional or sporting performance goals. Anecdotal evidence suggests increasing availability and marketing of such products to consumers, however, very few studies have looked at in-store product availability. Data for 2013 to 2018 were collected from the Nutritrack database, an online searchable database of all unique packaged foods and beverages sold at four main supermarket chains in New Zealand. Availability of sports foods and on-pack marketing techniques were assessed in 2018 using descriptive analysis, and changes in proportions over time were assessed using Chi-Square analyses. In 2018, the proportion of packaged foods available in major New Zealand supermarkets which were classified as sports foods was 2.1% (n=325), which had increased from 1.8% (n=247) in 2013. Sports foods also appeared in more food groups and subcategories in 2018 compared with 2013 (11 vs. 6 food groups, and 25 vs. 19 subcategories, respectively). The use of on-pack marketing techniques also increased over time, with Nutrient Claims present on 87% of sports foods in 2013 and 98% in 2018. The implications of the increase in product availability and on-pack marketing of sports foods in New Zealand supermarkets warrants consideration from public health, sporting, and consumer sectors.</p> <p>Sports foods are specially formulated to help people achieve specific nutritional or sporting performance goals. Anecdotal evidence suggests increasing availability and marketing of such products to consumers, however, very few studies have looked at in-store product availability. Data for 2013 to 2018 were collected from the Nutritrack database, an online searchable database of all unique packaged foods and beverages sold at four main supermarket chains in New Zealand. Availability of sports foods and on-pack marketing techniques were assessed in 2018 using descriptive analysis, and changes in proportions over time were assessed using Chi-Square analyses. In 2018, the proportion of packaged foods available in major New Zealand supermarkets which were classified as sports foods was 2.1% (n=325), which had increased from 1.8% (n=247) in 2013. Sports foods also appeared in more food groups and subcategories in 2018 compared with 2013 (11 vs. 6 food groups, and 25 vs. 19 subcategories, respectively). Use of on-pack marketing techniques also increased over time, with Nutrient Claims present on 87% of sports foods in 2013 and 98% in 2018. The implications of the increase in product availability and on-pack marketing of sports foods in New Zealand supermarkets warrants consideration from public health, sporting, and consumer sectors.</p> <p> </p>
Manual material handling in the supermarket sector: full dataset
<p><strong>Manual material handling in the supermarket sector: full dataset</strong></p> <p><strong>Sup. figures 1-50:</strong> Trunk flexion/extension (T8 relative to pelvis), lateral bending and rotation, knee flexion/extension and shoulder flexion/extension joint angles over the complete lifting cycles for all 50 analyzed manual material handling tasks (listed in Tables 1a and 1b).</p> <p><strong>Sup. figures 51-76:</strong> Knee and shoulder (glenohumeral) resultant joint reaction forces, as well as L4-L5 and L5-S1 axial compression, anteroposterior shear and mediolateral shear forces over the complete lifting cycles for the 26 manual material handling tasks included in the musculoskeletal model analysis (listed in Table 9) .</p> <p><strong>Tables 1-8 (a and b):</strong> Peak, 90<sup>th</sup> and 50<sup>th</sup> percentile muscle activity of trapezius descendens and erector spinae longissimus, bilateral peak joint angle and ROM for knee flexion-extension and shoulder flexion-extension for the 50 manual material handling tasks (description in Table 1a and 1b). The tasks are ranked from 1 to 50 (highest to lowest) for each outcome variable. </p> <p><strong>Tables 9-12:</strong> L5-S1 axial compression peak force and impulse, anteroposterior shear and mediolateral shear peak forces (Table 10), bilateral knee and shoulder (glenohumeral) peak resultant joint reaction forces (Table 11) as well as bilateral peak net total shoulder joint and knee flexion/extension moment (Table 12) for the 26 manual material handling tasks included in the musculoskeletal model analysis (description in Table 9). The tasks are ranked from 1 to 26 (highest to lowest) for each variable. </p>
Figure 2 in Detection of enteroparasites in foliar vegetables commercialized in street- and supermarkets in Aparecida de Goiânia, Goiás, Brazil
Figure 2. Protozoa detected in samples of lettuce and collard greens from street market and supermarkets in Aparecida de Goiânia, Goiás. (A) Cyst; (B) coccid oocyst with multiple sporocysts; (C) oocyst from Cystoisospora sp. resemble the C. belli; (D) oocyst of C. canis, (E) and (F) oocyst of Eimeriidae.
Supplementary file to "Effect of heat treatment on microbiological safety of supermarket food waste as substrate for black soldier fly larvae (Hermetia illucens)"
Open the record for dataset details and reuse information.
Domain-adaptive Data Synthesis for Large-scale Supermarket Product Recognition
<p><strong>Domain-Adaptive Data Synthesis for Large-Scale Supermarket Product Recognition</strong></p> <p>This repository contains the data synthesis pipeline and synthetic product recognition datasets proposed in [1].</p> <p><strong>Data Synthesis Pipeline:</strong></p> <p>We provide the Blender 3.1 project files and Python source code of our data synthesis pipeline <em>pipeline.zip, </em>accompanied by the<em> </em><a href="https://github.com/taesungp/contrastive-unpaired-translation">FastCUT</a> models used for synthetic-to-real domain translation<em> models.zip</em>. For the synthesis of new shelf images, a product assortment list and product images must be provided in the corresponding directories <em>products/assortment/</em> and <em>products/img/</em>. The pipeline expects product images to follow the naming convention <em>c</em>.png, with <em>c</em> corresponding to a GTIN or generic class label (e.g., 9120050882171.png). The assortment list, <em>assortment.csv</em>, is expected to use the sample format [<em>c, w, d, h</em>], with <em>c</em> being the class label and <em>w, d,</em> and <em>h</em> being the packaging dimensions of the given product in mm (e.g., [4004218143128, 140, 70, 160]). The assortment list to use and the number of images to generate can be specified in <em>generateImages.py </em>(see comments). The rendering process is initiated by either executing <em>load.py</em> from within Blender or within a command-line terminal as a background process. </p> <p><strong>Datasets:</strong></p> <ul> <li><strong>SG3k</strong> - Synthetic GroZi-3.2k (SG3k) dataset, consisting of 10,000 synthetic shelf images with 851,801 instances of 3,234 GroZi-3.2k products. Instance-level bounding boxes and generic class labels are provided for all product instances.</li> <li><strong>SG3kt</strong> - Domain-translated version of SGI3k, utilizing GroZi-3.2k as the target domain. Instance-level bounding boxes and generic class labels are provided for all product instances.</li> <li><strong>SGI3k</strong> - Synthetic GroZi-3.2k (SG3k) dataset, consisting of 10,000 synthetic shelf images with 838,696 instances of 1,063 GroZi-3.2k products. Instance-level bounding boxes and generic class labels are provided for all product instances.</li> <li><strong>SGI3kt</strong> - Domain-translated version of SGI3k, utilizing GroZi-3.2k as the target domain. Instance-level bounding boxes and generic class labels are provided for all product instances.</li> <li><strong>SPS8k</strong> - Synthetic Product Shelves 8k (SPS8k) dataset, comprised of 16,224 synthetic shelf images with 1,981,967 instances of 8,112 supermarket products. Instance-level bounding boxes and GTIN class labels are provided for all product instances.</li> <li><strong>SPS8kt</strong> - Domain-translated version of SPS8k, utilizing SKU110k as the target domain. Instance-level bounding boxes and GTIN class labels for all product instances.</li> </ul> <p>Table 1: Dataset characteristics. </p> <table> <tbody> <tr> <td><strong>Dataset</strong></td> <td><strong>#images</strong></td> <td><strong>#products</strong></td> <td><strong>#instances</strong></td> <td> <strong>labels </strong></td> <td><strong>translation</strong></td> </tr> <tr> <td>SG3k</td> <td>10,000</td> <td>3,234</td> <td>851,801</td> <td>bounding box & generic class¹</td> <td>none</td> </tr> <tr> <td>SG3kt</td> <td>10,000</td> <td>3,234</td> <td>851,801</td> <td>bounding box & generic class¹</td> <td>GroZi-3.2k</td> </tr> <tr> <td>SGI3k</td> <td>10,000</td> <td>1,063</td> <td>838,696</td> <td>bounding box & generic class²</td> <td>none</td> </tr> <tr> <td>SGI3kt</td> <td>10,000</td> <td>1,063</td> <td>838,696</td> <td>bounding box & generic class²</td> <td>GroZi-3.2k</td> </tr> <tr> <td>SPS8k</td> <td>16,224</td> <td>8,112</td> <td>1,981,967</td> <td>bounding box & GTIN</td> <td>none</td> </tr> <tr> <td>SPS8kt</td> <td>16,224</td> <td>8,112</td> <td>1,981,967</td> <td>bounding box & GTIN</td> <td>SKU110k</td> </tr> </tbody> </table> <p> </p> <p><strong>Sample Format</strong></p> <p>A sample consists of an RGB image (i.png) and an accompanying label file (i.txt), which contains the labels for all product instances present in the image. Labels use the YOLO format [c, x, y, w, h].</p> <p>¹SG3k and SG3kt use generic pseudo-GTIN class labels, created by combining the GroZi-3.2k food product category number <em>i</em> (1-27) with the product image index <em>j </em>(j.jpg)<em>, </em>following the convention<em> i0000j </em>(e.g., 13000097).</p> <p>²SGI3k and SGI3kt use the generic GroZi-3.2k class labels from <a href="https://arxiv.org/abs/2003.06800">https://arxiv.org/abs/2003.06800</a>.</p> <p><strong>Download and Use</strong><br>This data may be used for non-commercial research purposes only. If you publish material based on this data, we request that you include a reference to our paper [1].</p> <p>[1] Strohmayer, Julian, and Martin Kampel. "Domain-Adaptive Data Synthesis for Large-Scale Supermarket Product Recognition." <em>International Conference on Computer Analysis of Images and Patterns</em>. Cham: Springer Nature Switzerland, 2023.</p> <p>BibTeX citation:</p> <pre>@inproceedings{strohmayer2023domain, title={Domain-Adaptive Data Synthesis for Large-Scale Supermarket Product Recognition}, author={Strohmayer, Julian and Kampel, Martin}, booktitle={International Conference on Computer Analysis of Images and Patterns}, pages={239--250}, year={2023}, organization={Springer} }</pre>
Promotional Scheduling Software Price For Supermarkets
<p>Supermarket chains and independent grocers use Demo Wizard <a href="http://https//www.demo-wizard.com/pricing.html">promotional Scheduling Software</a> Price to maximize utilization of their floor space for in store demos and improve their customer experience.</p>
Product prices of the Mercadona supermarket in Spain (November 2023)
<p>The prices of all products that are available online on November 13 on the Mercadona supermarket website in Barcelona, Spain. Since the prices of Mercadona products are supposedly unified in all regions, we assume central Barcelona as a reference point for all of Spain. Mercadona online shop: <a href="https://tienda.mercadona.es/categories">https://tienda.mercadona.es/categories.</a></p><p>The dataset consists of the following columns: classification, category; sub_category; product_name; product_format; product_price; product_unit.</p><ul><li><strong>classification</strong>: Product classification can be understood as a higher and more general level than the category. E.g Marisco y pescado</li><li><strong>category</strong>: The product category. E.g Pescado fresco</li><li><strong>sub_category</strong>: The subcategory of the product. E.g Salmón</li><li><strong>product_name</strong>: The name of the product. E.g Filete de salmón, Salmón sin aletas y sin escamas</li><li><strong>product_format</strong>: The format that the product presents. E.g Bandeja 400 g aprox., Pieza 2,61 kg aprox., etc.</li><li><strong>product_price</strong>: The price of the product. E.g 9,58 €</li><li><strong>product_unit</strong>: The unit of the product. E.g /ud, /pack</li></ul>
List of questions related to surveys made at supermarket and consumer levels about post-harvest practices (strawberry)
<p>This file contains the list of questions contained in two surveys:</p> <p>- distributor survey: this survey aimed at getting more information about distribution of French strawberries. This questionnaire contains 57 questions</p> <p>- consumer survey: this survey aimed at getting more information about consumers' practices about fresh strawberries. This questionnaire contains 22 questions.</p>
Multi-level Supermarket Discount Study
ClinicalTrials.gov study NCT04178824. IPD Sharing: YES. Countries: 1. Publications: 4.
Encouraging Healthy Food Shopping and Eating Behaviors by Price Reduction: A Community Supermarket Study
ClinicalTrials.gov study NCT01509664. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Gluten Free Products in a supermarket
<p>Collection of information on gluten-free products offered by the Eroski supermarket, taking advantage of the fact that on its website it offers the possibility of displaying all products that do not contain this protein</p>
Supermarket and Web-Based Intervention Targeting Nutrition (SuperWIN) for Cardiovascular Risk Reduction
ClinicalTrials.gov study NCT03895580. IPD Sharing: NO. Countries: 1. Publications: 1.
Environmental Labelling in a Virtual Supermarket
ClinicalTrials.gov study NCT04909372. IPD Sharing: YES. Countries: 1. Publications: 1.
Pharmacist Impact on Pneumococcal Polysaccharide Vaccination Rates in Patients With Diabetes in a Supermarket Pharmacy Chain
ClinicalTrials.gov study NCT03851978. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Online Experimental Supermarket
ClinicalTrials.gov study NCT02769455. IPD Sharing: NO. Countries: 1. Publications: 3.
Change in Executive Function and IADL Using a Virtual Supermarket Environment Among People With MCI
ClinicalTrials.gov study NCT01103453. IPD Sharing: Not stated. Countries: 1. Publications: 4.
Figure 1 in Detection of enteroparasites in foliar vegetables commercialized in street- and supermarkets in Aparecida de Goiânia, Goiás, Brazil
Figure 1. Eggs and larvae of helminths detected in samples of lettuce and collard greens from street market and supermarkets in Aparecida de Goiânia, Goiás. (A) Ancylostomatidae / Strongyloididae; (B) Ascarididae; (C) Hymenolepis nana; (D) ovigerous capsule of Dipylidium caninum; (E) Taeniidae, (F) Toxocara sp.; (G) and (H) probably Trematodae; (I) probably Trypanoxyuris sp.; (J) unidentified nematode larvae.
Supermarket Science: Multipronged Approaches to Increasing Fresh, Frozen and Canned Fruit and Vegetable Purchases
ClinicalTrials.gov study NCT02975232. IPD Sharing: NO. Countries: 0. Publications: 1.
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Allen Brain Atlas
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