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620 results for “sector”
Dataset: Victoryshares Westend U.S. Sector ETF (MODL) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Fig. 1 in Lista preliminar de coleópteros (Insecta: Coleoptera) del sector "LA GredA", Buenos Aires, Morropón, Piura (Peṙ).
Fig. 1.- Mapa de Piura, donde puede observarse el distrito de Morropón (rosado), la provincia de Buenos Aires (rojo) y el sector "La Greda" (Delimitación con línea naranja), donde se señalan las tres zonas de estudio.
Fig. 1 in A report of Zebra Mussel Dreissena polymorpha (Pallas, 1771) (Bivalvia: Dreissenidae) in the middle sector of Iskar River, Bulgaria
Fig. 1. Study sector of the Iskar River: white circles marked macrozoobenthos sampling sites, dark circles marked microreservoirs of SHPPs.
Fig. 2 in A report of Zebra Mussel Dreissena polymorpha (Pallas, 1771) (Bivalvia: Dreissenidae) in the middle sector of Iskar River, Bulgaria
Fig. 2. Zebra Mussels from Iskar River near Tserovo village. Left: first recorded individual, 2016 September 29. Right: location (yellow arrow) of single specimens in the border (red lines) between ripal zone (0-0.5m depth) and medial river zone (over 1.5m depth). Photos: Ivaylo Yotinov.
Рис. 1. МестопоΛожение НационаΛьного парка «СмоΛьный» в МорΑовии (A) (на основе карты в https://old.bigenc.ru/geography/text/5746181) и схема НационаΛьного парка «СмоΛьный», показывающая номера квартаΛов в Λесничествах (Б) (оригинаΛ). a, корΑон Обрезки; b, корΑон Мокров; c, санаторий «АΛатырь»; d, урочище «СеΛищинская чащоба» Fig. 1. The location of the Smolny National Park in Mordovia; Fig. 1А. (based on the map at https://old. bigenc.ru/geography/text/5746181) and the map of the Smolny National Park showing sector numbers in forest ranges; Fig. 1Б. (original). a, Obrezki ranger station; b, Mokrov ranger station; c, Alatyr health centre; d, the natural boundary of Selishchinskaya Chashchoba in Neuroptera and Raphidioptera of the Smolny National Park, Republic of Mordovia, Russia
Рис. 1. МестопоΛожение НационаΛьного парка «СмоΛьный» в МорΑовии (A) (на основе карты в https://old.bigenc.ru/geography/text/5746181) и схема НационаΛьного парка «СмоΛьный», показывающая номера квартаΛов в Λесничествах (Б) (оригинаΛ). a, корΑон Обрезки; b, корΑон Мокров; c, санаторий «АΛатырь»; d, урочище «СеΛищинская чащоба» Fig. 1. The location of the Smolny National Park in Mordovia; Fig. 1А. (based on the map at https://old. bigenc.ru/geography/text/5746181) and the map of the Smolny National Park showing sector numbers in forest ranges; Fig. 1Б. (original). a, Obrezki ranger station; b, Mokrov ranger station; c, Alatyr health centre; d, the natural boundary of Selishchinskaya Chashchoba
Fig. 1 in Predatory behaviors: Pristimantis savagei (Anura: Craugastoridae) as prey of Trechalea sp. spiders (Araneae: Trechaleidae) in a sector of the Piedemonte Llanero, Villavicencio, Colombia
Fig. 1. Site of Pristimantis savagei predation by Trechalea sp., in a sector of Piedemonte Villavicencio-Meta, Colombia. The red dot indicates the exact site of discovery in the Caño Buque.
Fig. 2 in Predatory behaviors: Pristimantis savagei (Anura: Craugastoridae) as prey of Trechalea sp. spiders (Araneae: Trechaleidae) in a sector of the Piedemonte Llanero, Villavicencio, Colombia
Fig. 2. Record of predation of Pristimantis savagei by Trechalea sp., in a sector of Piedemonte, Villavicencio-Meta, Colombia.
Fig. 3 in Predatory behaviors: Pristimantis savagei (Anura: Craugastoridae) as prey of Trechalea sp. spiders (Araneae: Trechaleidae) in a sector of the Piedemonte Llanero, Villavicencio, Colombia
Fig. 3. Warning stance of the spider Trechalea sp. The individual was on a rock at an approximate height of 150 cm, less than 1 m from the water source.
Actors and Satellites in the African Earth Observations Sector: Insights from the 2021 Radiant Earth ML for EO Market Map and the Union of Concerned Scientists Database
<p>The database of organizational actors, "Actors and Satellites in the African Earth Observations Sector: Insights from the 2021 Radiant Earth ML for EO Market Map and the Union of Concerned Scientists Database" analyzed in "<span>Whose Priorities? Examining Inequities in Earth </span><span>Observation Advancements Across Africa" </span>this study, is available on Zenodo, an open-access repository developed under the European OpenAIRE program. The dataset comprises information on 310 space-centric earth observation organizations, including headquarters locations. For the 31 organizations in our sample, we provide additional details including the African countries where their projects are active, the type of initiative or program, other focus areas, organizational classification (commercial, government, or nongovernmental), funding source (public or private), organizational type (research, startup, or established industry), capabilities (data analysis, data storage, image labeling, competition platforms), involvement in early warning systems, data accessibility, availability of global products, and whether they build commercial satellites.</p> <p>This open sharing of the compiled organizational data aims to promote transparency, reproducibility, and additional investigations into the evolving landscape of earth observation activities globally and across Africa. Analyses of this dataset's relationships, funding flows, and priorities can provide further insights to guide equitable advancement of earth observation capabilities.</p>
Fotografías incendios sector Campamento Manuel Bustos
<p><span>Fotografías con los impactos del incendio urbano-forestal en el sector del Campamento Manuel Bustos, Viña del Mar, Valparaíso, Chile. Fotografías tomadas por Ricardo Acevedo (periodista del Observatorio de la Costa UC), Simón Inzunza, Esteban Araya, Stefan Vögel, Randy Román y Javiera Zuñiga. Fecha de captura: 6 y 7 de febrero de 2024</span></p>
Fotografías incendios sector El Olivar
<p><span>Fotografías de los impactos del incendio urbano-forestal en el sector El Olivar, Viña del Mar, Valparaíso, Chile. Fotografías tomadas por Ricardo Acevedo (periodista del Observatorio de la Costa UC), Simón Inzunza, Esteban Araya, Stefan Vögel, Randy Román y Javiera Zuñiga. Fecha de captura: 5, 6 y 7 de febrero de 2024</span></p>
Fotografías incendios sector Villa Independencia
<p>Fotografías de con los impactos del incendio urbano-forestal en el sector Villa Independencia, Viña del Mar, Valparaíso, Chile. Fotografías tomadas por Ricardo Acevedo (periodista del Observatorio de la Costa UC), Simón Inzunza, Esteban Araya, Stefan Vögel, Randy Román y Javiera Zuñiga. Fecha de captura: 5, 6 y 7 de febrero de 2024</p>
Fotografías incendios sector El Salto
<p><span>Fotografías de con los impactos del incendio urbano-forestal en el sector de El Salto, Viña del Mar, Valparaíso, Chile. Fotografías tomadas por Ricardo Acevedo (periodista del Observatorio de la Costa UC). Fecha de captura: 5 de febrero de 2024</span></p>
Data sets for distributed ionospheric L-band scintillation and TEC observations made in the American sector during the March 23-24, 2023 geomagnetic storm
<p>These data sets contain the scintillation measurements presented in the manuscript titled, "On the extraordinary L-band scintillation event observed in the American sector during the March 23-24, 2023 geomagnetic storm".</p> <p><br>The HDF5 files are organized by constellations and satellites. Each satellite includes the following parameters: Azimuth (AZIM), Elevation (ELEV), Number of Samples (NOS), Amplitude Scintillation Index (S4), 1-minute average SNR (SNR), relative Total Electron Content (PTEC), and Time of Week in seconds (S_TW)</p>
SENTIMENT ANALYSIS OF CUSTOMER FEEDBACK IN THE BANKING SECTOR: A COMPARATIVE STUDY OF MACHINE LEARNING MODELS
<p><span>This study investigates the application of sentiment analysis to customer feedback in the banking sector, utilizing natural language processing (NLP) techniques and machine learning models to classify customer sentiments into positive, neutral, and negative categories. Feedback was sourced from online platforms, including bank websites, social media, and third-party review sites. Data preprocessing steps, such as tokenization, stemming, and feature extraction using TF-IDF, were employed to prepare the text for analysis. Various machine learning algorithms, including Logistic Regression, Random Forest, Support Vector Machine (SVM), Long Short-Term Memory (LSTM), and Naïve Bayes, were implemented and evaluated using metrics such as accuracy, precision, recall, and F1-score. The results show that LSTM outperformed all models with a 91% accuracy, followed closely by SVM at 89%. These findings demonstrate the potential of advanced machine learning techniques in accurately classifying sentiments and provide valuable insights into customer satisfaction and areas for improvement within the banking sector. Future work aims to further optimize models for better classification of neutral feedback and explore more advanced deep learning models, such as BERT.</span></p>
Linked collectors and determiners for: All herbarium specimens of grasses from Madagascar and the surrounding islands: family Poaceae, sector AFM.
Natural history specimen data linked to collectors and determiners held within, "All herbarium specimens of grasses from Madagascar and the surrounding islands: family Poaceae, sector AFM". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/ac8e5183-e233-4168-96a5-67541049aa67">https://bionomia.net/dataset/ac8e5183-e233-4168-96a5-67541049aa67</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/ac8e5183-e233-4168-96a5-67541049aa67">https://gbif.org/dataset/ac8e5183-e233-4168-96a5-67541049aa67</a>. Formatted as a Frictionless Data package.
Linked collectors and determiners for: Colección de Cnidarios del sector costero del departamento del Magdalena.
Natural history specimen data linked to collectors and determiners held within, "Colección de Cnidarios del sector costero del departamento del Magdalena". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/79b6d0ce-92da-44ec-886d-40fe445a017c">https://bionomia.net/dataset/79b6d0ce-92da-44ec-886d-40fe445a017c</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/79b6d0ce-92da-44ec-886d-40fe445a017c">https://gbif.org/dataset/79b6d0ce-92da-44ec-886d-40fe445a017c</a>. Formatted as a Frictionless Data package.
Data input for the RegMex model experiment on the power system and flexible sector coupling
<p>This file provides the input data used in the power system flexibility model experiment performed within the RegMex project. Comprehensive information about the project can be found in the project report [Lechtenböhmer2018] (in German, see link in the file). In the experiment performed with the data documented here, three scenarios were considered, labelled "Import", "Decentralized" and "Offshore". This file contains the input for all scenarios. All further information on the model and scenario configuration is available from the project report. Many technology parameter have been derived as own assumptions within previous projects, relying on different sources. Details can be found in the cited PhD and masters theses. In the experiment, Germany was modelled with 18 regions reflecting the transmission grid operator zones (see map in the file).</p>
Text-fig. 7. Photo of a skull with lower jaw of a cave lion subadult female (registration number is Ok-139786), discovered in layer C of sector 4 of the Under the Ladder test pit. Photo by V. Káňa. in The Mammalian Fauna Of Barová Cave (Moravian Karst, The Czech Republic)
Text-fig. 7. Photo of a skull with lower jaw of a cave lion subadult female (registration number is Ok-139786), discovered in layer C of sector 4 of the Under the Ladder test pit. Photo by V. Káňa.
Text-fig. 4. Layout of the Under the Ladder test pit. Sectors of the Under the Ladder test pit are marked by rectangles with numbers and letters: 0, 1, 2, 3, 4, R4, R5. in The Mammalian Fauna Of Barová Cave (Moravian Karst, The Czech Republic)
Text-fig. 4. Layout of the Under the Ladder test pit. Sectors of the Under the Ladder test pit are marked by rectangles with numbers and letters: 0, 1, 2, 3, 4, R4, R5.
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.