cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/tu.the.2023.634
title: A scalable and secure outsourced IoT electronic health records with efficient user revocation using fog-assisted cloud model

description: With the integration of IoT technology and cloud computing in healthcare, outsourcing Electronic Health Records (EHRs) generated by IoT devices becomes a critical issue. This is due to multiple stages of data transfer and storage in the cloud. Typically, EHRs from IoT medical devices are sent to a data aggregation service, where the aggregated data are encrypted before being stored in the cloud. However, initial data transfers from IoT devices to the aggregation service often occur in a closed network environment. Despite this, EHRs may be collected by various hospital units and transmitted over intranets or public networks, making them vulnerable to privacy breaches. Existing cloud-based access control models typically focus on preserving the privacy of aggregated EHRs but often neglect the privacy of the data before it is transferred to the aggregation service. However, in an IoT cloud data sharing environment, where data originate from numerous devices and user authorization statuses frequently change, there is a need for a comprehensive and systematic integration of secure data transfer, aggregation, and efficient user revocation. In this research, we propose a fine-grained, secure cloud-based access control scheme with efficient and scalable revocation for IoT-based EHRs using Ciphertext Policy Attribute-Based Encryption (CP-ABE) and fog-assisted computing. We introduce an IoT data encryption and secure aggregation algorithm. Our scheme leverages outsourced encryption and decryption to enable secure and lightweight access control in fog-cloud computing. Additionally, we develop a revocation protocol using a graph database to facilitate an efficient user revocation mechanism in a dynamic access control system. To enhance transaction processing, we also introduce a secure load-sharing protocol to distribute computation burdens among fog nodes. Finally, we present security analysis, comparative computation analysis, and experimental results to demonstrate that our scheme is both secure and efficient in practice.
DOI: 10.14457/tu.the.2023.635
title: Spoof detection using voice contribution on LFCC features and ResNet-34

description: Recent advancements in biometric authentication, particularly within the realm of speaker verification, have been notable. However, despite these strides, the persisting vulnerability to spoofing attacks is evident, necessitating specialized measures for detection across various attack types. This study focuses specifically on the identification of replay, speech synthesis, and voice conversion attacks. Our approach to spoof detection involves the utilization of linear frequency cepstral coefficients (LFCC) for the extraction of front-end features, coupled with ResNet-34 for the discrimination between genuine and spoofed speech samples. Through the integration of LFCC with ResNet-34, we rigorously evaluated our proposed method using the ASVspoof 2019 dataset. We investigated scenarios involving Physical Access (PA), focusing on replay attacks, and Logical Access (LA), which encompassed speech synthesis and voice conversion attacks. In our investigation, we compare the efficacy of utilizing the entire utterance for feature extraction against an alternative method that extracts features from a specific segment of the voice within the utterance for classification. Additionally, we conducted a comprehensive evaluation by benchmarking our proposed method against established baseline techniques, namely linear frequency cepstral coefficients - gaussian mixture model (LFCC-GMM) and constant Q cepstral coefficients - gaussian mixture model (CQCC-GMM), as well as contemporary state-of-the-art approaches. The results of our study demonstrate promising performance outcomes. Specifically, our proposed method achieves an equal error rate (EER) of 1.85% and 2.74% for replay attacks (PA) in the development and evaluation datasets, respectively. For voice conversion and speech synthesis attacks (LA), the method attains EER of 0.01% and 5.16% in the corresponding datasets. These findings underscore the effectiveness of our method in identifying spoof attacks across both PA and LA scenarios. Furthermore, we extend our analysis by conducting cross-dataset validation and addressing gender bias to thoroughly evaluate the robustness and generalizability of our model. These additional assessments provide further insights into the performance and reliability of our proposed approach in real-world settings.
DOI: 10.14457/tu.the.2023.636
title: Enhancing PM 2.5 prediction coverage in Northern Thailand using ground station information assisted with aerosol optical depth and weather data from NASA satellite instruments

description: Air pollution has become a significant issue in Northern Thailand due to forest fires, human activities, and seasonal climate variations. This study primarily addresses the issue of missing data in PM10 measurements obtained from the Pollution Control Department (PCD) stations in the provinces of Chiang Mai, Lampang, and Nan, which limited the capability to predict future pollutant levels. The study proposed three imputation methods: k-nearest neighbors (KNN), last observation carried forward (LOCF), and nearest observation carried backward (NOCB) to solve the existing missing gaps in the dataset. The NOCB method yielded the highest R², the lowest mean absolute error (MAE), and the lowest root mean squared error (RMSE) across varied proportions of mimic missing data. The imputed data were then used for time-series predictions with long short-term memory (LSTM) neural networks, achieving an R² of approximately 0.92 for PM10 predictions. Building on these foundations, the research extends by incorporating the data from the National Astronomical Research Institute of Thailand (NARIT) and the National Aeronautics and Space Administration (NASA) satellite observations to enhance the prediction of PM2.5 levels. The results demonstrated a strong relationship between ground-based PM2.5 and satellite data suggesting that the incorporation of satellite data enables more accurate PM2.5 analysis, even in the absence of ground monitoring stations. The findings indicate that satellite-derived aerosol optical depth (AOD) and other meteorological weather variables from NASA instruments can effectively supplement ground-based PM2.5 prediction, ensuring reliable pollution forecasting and enhanced environmental management in Northern Thailand. This approach not only addresses data gaps but also highlights the potential of utilizing satellite data in regions lacking extensive ground monitoring infrastructure.
DOI: 10.14457/tu.the.2023.637
title: A traffic monitoring method using accumulative difference images

description: This paper presents a traffic monitoring method to count the number of vehicles from video surveillance on a highway. The proposed method uses the accumulative difference images (ADI) for extracting the vehicles from stationary background scenes. The result of ADI is a sequence of images, namely, x-y planes. However, we cannot count the number of vehicles in full frame directly because the vehicles far from the video camera are small and occluded. The horizontal-temporal cross-section plane is applied for ADI result that is the 3-Dimensional data (x, y, t) to slice into y-t plane at a certain level of x to observe the moving object or vehicles on video within one frame. To count the number of vehicles in cross-section planes with 1-D projection, we propose to separate the lanes of the road to avoid missing vehicles caused by connection of vehicles that extracted from original video. The result shows that counting the number of vehicles within the full frame of x-y planes is less accurate by the video environment than the proposed method counting the number of vehicles within the horizontal-temporal cross-section that is the y-t planes.
DOI: 10.14457/tu.the.2023.639
title: Demand forecasting framework for dynamic fleet sizing decision: a case study of pickup-and-delivery services in Thailand

description: Accurate demand forecasting is essential for optimizing fleet sizing in pickup-and-delivery services. This study evaluates a demand forecasting framework for dynamic fleet sizing decisions in Thailand's pickup-and-delivery industry. Various models, including ARIMAX, Exponential Smoothing, Random Forest, Multiple Linear Regression (MLR), Artificial Neural Network (ANN), STL Decomposition, and Holt-Winters models, are compared using performance metrics such as MAD, MAPE, MSE, and RMSE. Historical data is used to forecast demand, providing insights for effective fleet sizing. The results highlight the strengths and weaknesses of each model, offering a practical approach for logistics optimization. This research fills the gap in model evaluation and presents a robust framework for demand forecasting in dynamic operational contexts.
DOI: 10.14457/tu.the.2023.640
title: Storage location management in the distribution center by heuristic method

description: This paper studies the characteristics of real petrochemical warehouse operations in Thailand, which uses storage management of block stacking in a randomization strategy. The current strategy results in inefficient operation and storage management inside the warehouse. The scope of this study is to analyze the historical data in the warehouse management system, including understanding the characteristics of each customer product behavior and current warehouse zoning to minimize the overall forklift traveling distance. The proposed method of dedicated storage with zoning strategy was applied using historical inbound and outbound data to evaluate the average distance traveled by the forklift trucks. The proposed method shows a significant reduction in overall forklift travel distances compared to the current randomization method. This suggests the potential benefits of implementing the strategy in real operations to enhance resource utilization efficiency.
DOI: 10.15468/dl.63q6yp
title: Occurrence Download

description: A dataset containing 575 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Passiflora apetala Killip"
 ]
}

 The dataset includes 575 records from 27 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014179-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wp2s55
title: Occurrence Download

description: A dataset containing 3272 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Columba rupestris Pallas, 1811",
 "Year 2013-2022"
 ]
}

 The dataset includes 3272 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014180-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.26186/149884
title: SI 1030 Bass Pyramid to Wright Block (HIPP) Bathymetry Acquisition (20230020S)

description: The Bass Pyramid to Wright Block bathymetry survey was acquired for the Australian Hydrographic Office (AHO) during the period 16 Oct 2023 – 10 Jan 2024. This was a contracted survey conducted for the Australian Hydrographic Office as part of the Hydroscheme Industry Partnership Program. The survey area encompasses an area in Bass Pyramid to Wright Block. Bathymetry data was acquired using a Kongsberg EM2040-07, and processed using CARIS HIPS and SIPS processing software. The dataset was then exported as a 30m resolution, 32 bit floating point GeoTIFF grid of the survey area.This dataset is not to be used for navigational purposes.
DOI: 10.26186/149880
title: SI 1017 Varzin Passage to Merkara Shoal (HIPP) Bathymetry Acquisition (20230015S)

description: The Varzin Passage to Merkara Shoal bathymetry survey was acquired for the Australian Hydrographic Office (AHO) during the period 4 Sep 2023 – 12 Apr 2024. This was a contracted survey conducted for the Australian Hydrographic Office by Fugro Australia as part of the Hydroscheme Industry Partnership Program. The survey area encompasses an area in Varzin Passage to Merkara Shoal. Bathymetry data was acquired using a LADS HD+, and processed using CARIS HIPS and SIPS, and QIMERA processing software. The dataset was then exported as a 30m resolution, 32 bit floating point GeoTIFF grid of the survey area.This dataset is not to be used for navigational purposes.
DOI: 10.26186/149889
title: SI 1046 Howard Channel (HIPP) Bathymetry Acquisition (20230007S)

description: The Howard Channel bathymetry survey was acquired for the Australian Hydrographic Office (AHO) during the period 9 Aug 2023 – 13 Sep 2023. This was a contracted survey conducted for the Australian Hydrographic Office by EGS Australia as part of the Hydroscheme Industry Partnership Program. The survey area encompasses an area in Howard Channel. Bathymetry data was acquired using a Kongsberg EM2040C, and processed using CARIS HIPS and SIPS, and QIMERA processing software. The dataset was then exported as a 30m resolution, 32 bit floating point GeoTIFF grid of the survey area.This dataset is not to be used for navigational purposes.
DOI: 10.26186/149887
title: SI 1043 Cape Fourcroy (West) (HIPP) Bathymetry Acquisition (20230016S)

description: The Cape Fourcroy (West) bathymetry survey was acquired for the Australian Hydrographic Office (AHO) during the period 18 Aug 2023 – 15 Oct 2023. This was a contracted survey conducted for the Australian Hydrographic Office as part of the Hydroscheme Industry Partnership Program. The survey area encompasses an area in Cape Fourcroy (West). Bathymetry data was acquired using a Kongsberg EM2040 MKII, and processed using CARIS HIPS and SIPS, and QIMERA processing software. The dataset was then exported as a 30m resolution, 32 bit floating point GeoTIFF grid of the survey area.This dataset is not to be used for navigational purposes.
DOI: 10.15468/dl.72utdc
title: Occurrence Download

description: A dataset containing 24 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Citharichthys mariajorisae van der Heiden & Mussot-Pérez, 1995"
 ]
}

 The dataset includes 24 records from 7 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014181-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.5281/zenodo.13744263
title: Lithological and geochemical data of the Naqing section
DOI: 10.5281/zenodo.13744264
title: Lithological and geochemical data of the Naqing section
DOI: 10.15468/dl.f6f2r9
title: Occurrence Download

description: A dataset containing 56 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-104.36449 21.11477,-104.35562 21.08134,-104.33464 21.09114,-104.34179 21.1218,-104.36449 21.11477))",
 "OccurrenceStatus is Present"
 ]
}

 The dataset includes 56 records from 10 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014183-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.jx6dsq
title: Occurrence Download

description: A dataset containing 732 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Colombia",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "OccurrenceStatus is Present",
 "TaxonKey is Conepatus semistriatus (Boddaert, 1785)"
 ]
}

 The dataset includes 732 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014184-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.6084/m9.figshare.27011953
title: <b>From Data to Action: Leveraging Pareto Analysis of Outpatient Morbidity for Strategic Drug Procurement and Health Promotion in Resource-Constrained Setting in Ghana</b>

description: This study therefore Pareto analysis to outpatient morbidity data from local health facilities to identify the most prevalent conditions and provide actionable recommendations for improving drug procurement processes and optimizing health promotion strategies.
DOI: 10.6084/m9.figshare.27011953.v1
title: <b>From Data to Action: Leveraging Pareto Analysis of Outpatient Morbidity for Strategic Drug Procurement and Health Promotion in Resource-Constrained Setting in Ghana</b>

description: This study therefore Pareto analysis to outpatient morbidity data from local health facilities to identify the most prevalent conditions and provide actionable recommendations for improving drug procurement processes and optimizing health promotion strategies.
DOI: 10.15468/dl.e4nrkg
title: Occurrence Download

description: A dataset containing 17862 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is China",
 "TaxonKey is Streptopelia orientalis (Latham, 1790)",
 "Year 2013-2022"
 ]
}

 The dataset includes 17862 records from 9 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014186-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.84yxyj
title: Occurrence Download

description: A dataset containing 13163 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-123.86051 48.39016,-124.20237 39.58831,-116.63756 32.18507,-104.86452 30.98415,-104.37139 48.80831,-123.86051 48.39016))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Reithrodontomys megalotis (Baird, 1857)"
 ]
}

 The dataset includes 13163 records from 67 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0014185-240906103802322/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.zd48nu
title: Occurrence Download

description: A dataset containing 493489 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Continent is Europe",
 "Country is Switzerland",
 "TaxonKey is Orthoptera"
 ]
}

 The dataset includes 493489 records from 39 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0111796-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fbtszb
title: Occurrence Download

description: A dataset containing 11 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Canthigaster cyanetron Randall & Cea-Egaña, 1989"
 ]
}

 The dataset includes 11 records from 5 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0067663-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.dcnmwt
title: Occurrence Download

description: A dataset containing 81 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Astragalus tolmaczevii Jurtzev"
 ]
}

 The dataset includes 81 records from 8 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080276-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.57b8tu
title: Occurrence Download

description: A dataset containing 1450 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is Respaldo de las colecciones de tejidos del Museo de Zoología, Departamento de Biología Evolutiva, Facultad de Ciencias, UNAM (Aves)"
 ]
}

 The dataset includes 1450 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0172210-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.3sa59t
title: Occurrence Download

description: A dataset containing 664 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Gymnocranius euanus (Günther, 1879)"
 ]
}

 The dataset includes 664 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0111804-230530130749713/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.qqpdcg
title: Occurrence Download

description: A dataset containing 2373 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is one of (Peniophora pini (Schleich. ex DC.) Boidin, Peniophora polygonia (Pers.) Bourdot & Galzin)",
 "Geometry POLYGON((-9.36035 44.71551,-10.59082 42.81152,-11.82129 36.80928,-7.69043 36.17336,-3.38379 35.88905,3.12012 38.13456,9.18457 38.20366,11.7334 37.16032,12.78809 34.74161,17.09473 33.79741, 23.15918 34.23451,30.10254 32.62087,33.2666 32.99024,35.72754 35.03,33.00293 35.53223,28.69629 35.17381,28.34473 36.31513,25.7959 37.50973,24.91699 39.90974,28.78418 40.6473,30.71777 41.17865,36.87012 45.213,38.18848 46.98025,38.71582 47.7541,39.94629 47.93107,40.20996 49.61071,37.0459 50.34546,35.72754 50.40152,33.79395 52.26816,31.68457 51.94426,31.4209 53.27835,32.56348 53.43572,30.98145 54.77535,30.89355 55.52863,28.43262 56.02295,27.20215 57.65716,27.37793 58.30949,27.90527 59.17593,29.66309 59.88894,27.6416 60.58697,31.50879 62.75473,28.78418 69.83962,30.89355 70.28912,29.22363 71.55274,21.75293 71.30079,14.28223 70.14036,11.38184 67.47492,4.87793 63.66576,-5.53711 71.52491,-10.63477 71.69129,-21.5332 67.74276,-28.56445 65.36684,-24.3457 61.35461,-9.36035 44.71551))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "Year is greater than or equal to 1980",
 "Year is less than or equal to 2021"
 ]
}

 The dataset includes 2373 records from 65 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0248486-210914110416597/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.28se4j
title: Occurrence Download

description: A dataset containing 11246 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Continent is Europe",
 "Year is greater than 1978",
 "Year is less than 2014",
 "HasGeospatialIssue is false",
 "TaxonKey is Cotinus coggygria Scop."
 ]
}

 The dataset includes 11246 records from 155 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080261-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.6w9qwn
title: Occurrence Download

description: A dataset containing 53 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Metis holothuriae (Edwards, 1891)"
 ]
}

 The dataset includes 53 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0124496-220831081235567/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.w58bfs
title: Occurrence Download

description: A dataset containing 281712 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasCoordinate is true",
 "Continent is Europe",
 "Year is greater than 1978",
 "Year is less than 2014",
 "HasGeospatialIssue is false",
 "TaxonKey is Rumex crispus L."
 ]
}

 The dataset includes 281712 records from 837 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0080270-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.