cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.15468/dl.xhffb3
title: Occurrence Download

description: A dataset containing 1461 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Sematophyllum subhumile (Müll.Hal.) M.Fleisch."
 ]
}

 The dataset includes 1461 records from 45 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0024467-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wqmrca
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A new species of Melampyrum (Orobanchaceae) from Southern Korea"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0184542-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.44smw9
title: Occurrence Download

description: A dataset containing 1 species occurrences available in GBIF matching the query:
{
 "DatasetKey" : [
 "is A new species of Melampyrum (Orobanchaceae) from Southern Korea"
 ]
}

 The dataset includes 1 records from 1 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0184545-240321170329656/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.rpowpv
title: Occurrence Download

description: A dataset containing 226 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Canis lupus baileyi Nelson & Goldman, 1929",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 226 records from 14 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000586-160430102343922/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.1uwktv
title: Occurrence Download

description: A dataset containing 626 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Metallura aeneocauda (Gould, 1846)"
 ]
}

 The dataset includes 626 records from 17 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028349-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.33xkaa
title: Occurrence Download

description: A dataset containing 176 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Androsace vitaliana subsp. cinerea (Sünd.) Kress"
 ]
}

 The dataset includes 176 records from 26 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0176782-230224095556074/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.j2oroe
title: Occurrence Download

description: A dataset containing 80 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cephalocereus senilis (Haw.) Pfeiff."
 ]
}

 The dataset includes 80 records from 15 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000586-160509122628363/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.k5zlgo
title: Occurrence Download

description: A dataset containing 66 species occurrences available in GBIF matching the query:
{
 "and" : [
 "ScientificName is Macrozamia elegans K.D.Hill & D.L.Jones",
 "DecimalLatitude is greater than or equal to -90",
 "DecimalLongitude is greater than or equal to -180"
 ]
}

 The dataset includes 66 records from 2 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0028332-191105090559680/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.wmbwcw
title: Occurrence Download

description: A dataset containing 8222 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Geometry POLYGON((-127.0872 -0.87241,-70.29644 -0.87241,-70.29644 37.80553,-127.0872 37.80553,-127.0872 -0.87241))",
 "HasGeospatialIssue is false",
 "TaxonKey is Ursus americanus Pallas, 1780"
 ]
}

 The dataset includes 8222 records from 54 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002024-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.lzbhuc
title: Occurrence Download

description: A dataset containing 928 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Hedychium coronarium J.Koenig",
 "HasCoordinate is true",
 "HasGeospatialIssue is false"
 ]
}

 The dataset includes 928 records from 106 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000586-160526112335914/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.e5vtz6
title: Occurrence Download

description: A dataset containing 752 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Cuscuta chinensis Lam."
 ]
}

 The dataset includes 752 records from 75 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0222178-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.fheggv
title: Occurrence Download

description: A dataset containing 4116 species occurrences available in GBIF matching the query:
{
 "and" : [
 "Country is Brazil",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Pteroglossus bailloni (Vieillot, 1819)"
 ]
}

 The dataset includes 4116 records from 16 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0012480-230918134249559/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ycebxs
title: Occurrence Download

description: A dataset containing 559 species occurrences available in GBIF matching the query:
{
 "TaxonKey" : [
 "is Kogia sima (Owen, 1866)"
 ]
}

 The dataset includes 559 records from 29 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000586-160623103540712/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.ssqkyj
title: Occurrence Download

description: A dataset containing 357 species occurrences available in GBIF matching the query:
{
 "and" : [
 {
 "or" : [
 "BasisOfRecord is Human Observation",
 "BasisOfRecord is Specimen"
 ]
 },
 "Country is United States of America",
 "Geometry POLYGON((-80.33908 26.37017,-72.65215 24.70493,-66.82557 39.89033,-68.55141 40.25816,-69.14337 41.65494,-71.16966 41.82419,-73.01883 42.01313,-77.49919 38.52413,-76.50717 37.14555,-78.97155 34.12564,-82.33048 31.49288,-80.33908 26.37017))",
 "HasCoordinate is true",
 "HasGeospatialIssue is false",
 "TaxonKey is Asterias forbesi (Desor, 1848)",
 "Year 1970-2021"
 ]
}

 The dataset includes 357 records from 11 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0222182-200613084148143/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.cbbkv6
title: Occurrence Download

description: A dataset containing 3266 species occurrences available in GBIF matching the query:
{
 "and" : [
 "TaxonKey is Neotoma micropus Baird, 1855",
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 "Year is greater than or equal to 1900",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "Country is United States of America",
 {
 "or" : [
 "CoordinateUncertaintyInMeters is less than 3000",
 "CoordinateUncertaintyInMeters is null"
 ]
 }
 ]
}

 The dataset includes 3266 records from 41 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0002017-231002084531237/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.15468/dl.0zdg4n
title: Occurrence Download

description: A dataset containing 3842854 species occurrences available in GBIF matching the query:
{
 "Country" : [
 "is China"
 ]
}

 The dataset includes 3842854 records from 1206 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0000586-170817152713382/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.14457/tu.the.2023.525
title: Feature-based next-best-view selection for scanning 3D objects

description: This thesis presents a method to observe a 3D object’s surface that needs to be scanned and find the next positions for a sensor or camera with a minimum number of iterations. This process is the Next Best View (NBV). We propose a method that uses a point cloud density measurement technique to determine the NBV positions. The point cloud density technique assesses the point cloud density which is determined from point cloud acquired from scanning the object's surface. The point cloud obtained from the scanned surface has different densities on each part of the object. The point cloud density measurement is used as an indicator to determine the completion of the scanning process. Our proposed algorithm verifies that the acquired point cloud is good and covers every part of the object whenever the quality measurement is satisfied and meets criteria. We tested our method in a simulation environment. Our proposed algorithm gives a lower number of iterations compared to the state-of-the-art methods that are used as the baseline algorithm.
DOI: 10.14457/tu.the.2023.526
title: Pre-screening of healthy retinal using geometrical features extracted from OCT retinal images

description: Optical Coherence Tomography (OCT) retinal imaging is essential in ophthalmology for the diagnosis of eye diseases. To date, identifying healthy OCT retinal images can be challenging due to the large volume of images but limited time for ophthalmologists. In this study, we developed a classification technique that differentiates between healthy and unhealthy OCT images of the retina. We applied the Standard Deviation Profiling (SDP) method that can accurately detect the inner limiting membrane (ILM) and retinal pigment epithelium (RPE), determining the region of interest for observing the structural information. First of all, the outer nuclear layer (ONL) was detected using k-means clustering segmentation, applied to the region between the ILM and RPE layers. Then, 24 geometrical features involving area-based, distance-based, intensity-based, and symmetry-based features, so-called “feature sets,” were extracted with the assistance of the three layers. A number of machine learning classifiers were built using such 24 geometrical features with a train:test data splitting of 80:20 among the dataset containing 80 OCT images. The results show that the extracted features quantitatively represented the structural conditions of the retina using geometrical relevance. We achieved 100% classification accuracy in various models, including fine tree, linear discriminant, Naïve Bayes networks, linear support vector machine, and ensemble subspace discriminant. Whilst models trained using each feature set on its own only yield above 80% accuracy using these five classifiers, with area-based and distance-based features presenting relatively higher accuracy. The results of this study emphasized the novel contribution of extracting the 24 geometrical features, which successfully trained machine learning classifiers to categorize healthy versus diseased retinal OCT images.
DOI: 10.14457/tu.the.2023.528
title: Performance of time-series forecasting and machine learning techniques to forecast price of agricultural products

description: This paper studies forecasts of agricultural product prices using Trend Analysis method, Decomposition method, Double Exponential Smoothing method, HoltWinter's method, and ANNs method. Collected data from 2005-2021 to forecast and compare the accuracy between the forecast values and actual values with MAPE, which forecasts for the years 2015, 2015-2016, 2020 and 2020-2021 as a guide for making decisions about choosing the appropriate data for forecasting the price of agricultural products in the future accurately. Experimental results reveal that The ANNs methodforecast more accurately in cases where the basic time-series methods were not good at forecasting, and the results obtained were satisfactory. There is no guideline to tell that in which situation a particular time series method will be more accurate than others. Anexperiment on various forecasting methods and adjustment of related parameters must be conducted to obtain the accurate forecast. In real data sets, there may be some unusual events that cause an inaccurate forecast.
DOI: 10.14457/tu.the.2023.529
title: Rice disease detection in UAV images using deep learning-based semantic segmentation

description: Rice is a vital crop globally, with significant economic and employment contributions, especially in Asia. However, rice farming faces challenges from diseases like Bacterial Leaf Blight (BLB), which adversely impact yield and grain quality. This thesis aims to address two critical areas: the accurate classification of paddy fields using satellite imagery and the detection and assessment of BLB severity using UAV imagery and deep learning techniques.To improve paddy field classification, we explore automated machine learning (ML) methods using Sentinel-1 and Sentinel-2 satellite data. The study employs Random Forest (RF) and Classification and Regression Trees (CART) algorithms, enhanced with the Normalized Difference Vegetation Index (NDVI) to improve classification accuracy. Our findings indicate that the RF algorithm applied to Sentinel-2 data achieves the highest classification accuracy, with a model accuracy of 97.19% and overall accuracy (OA) of 93.49%. In contrast, both RF and CART algorithms show lower performance on Sentinel-1 imagery, with an accuracy of approximately 85%. These results highlight the potential of using ML algorithms and satellite imagery for efficient and accurate paddy field classification, reducing false claims in agricultural insurance.For BLB detection and severity assessment, we develop an automated framework using deep learning (DL) techniques and UAV imagery. The study is conducted at the Pathum Thani Rice Research Center, utilizing top-view images captured by a DJI Phantom 4 equipped with multispectral sensors. We implement U-Net and DeepLabV3+ architectures with a ResNet-101 backbone, exploring various band combinations to achieve superior segmentation accuracy. The results demonstrate that the integration of multispectral and NDVI bands with the U-Net network outperforms other configurations, achieving a mean Intersection over Union (IoU) of 96.32%, an F1-score of 98.11%, and an accuracy of 99.05%. This model effectively minimizes classification errors and accurately detects disease boundaries, offering a reliable method for assessing BLB severity.Overall, this research provides significant insights into the application of ML and DL techniques in agricultural remote sensing, offering practical solutions for paddy field classification and disease management. The methodologies developed can be extended to other rice diseases and crops, enhancing agricultural practices through accurate damage mapping and yield loss estimation.
DOI: 10.14457/tu.the.2023.530
title: Text merging algorithm for Thai captioning system

description: The increasing number of Deaf and Hard of Hearing individuals has amplified the need for quality captions, especially in real-time captioning. Previous studies have successfully explored various methods to enhance caption quality, including alignment-based and neural network approaches. While alignment-based methods represent a conventional approach, neural network models are inherently more complex yet offer superior performance. However, these neural models demand large datasets, posing challenges for languages such as Thai with limited datasets available. In this study, we propose two captions improvement methods. The Simple2In1, a simple but effective method to improve the quality of Thai captions on a small-scale Thai dataset. This method utilizes a pre-trained mT5 model to generate a single sequence from two sequences from two different captioning systems. The MASs-ATTEN, this method utilizes multiple aligned sequences to improve the quality of the first method further. Despite a small dataset and limited input sequences, our methods show potential in improving six evaluation metrics, surpassing all baseline models.
DOI: 10.14457/tu.the.2023.531
title: Production scheduling of a parallel machine system with sequence dependent set-up times

description: This study tackles a difficult scheduling problem involving unrelated parallel machines with set-up times that vary with the sequence. Notably, the machines vary in their production rates, resulting in variable processing durations for the same task on different machines. Furthermore, the capacity of these computers to process jobs varies, as they handle different subsets of the whole work set. The set-up time also varies depending on the machine and the jobs that are processed on it.Four mixed-integer programming (MIP) models are developed to reflect distinct parts of the problem. Three of these models are concerned with minimizing makespan, overall tardiness, and the number of tardy jobs. The fourth model is specifically designed to generate compromise solutions, providing a more sophisticated approach to optimization. The study uses the AUGEMEN method to develop a set of Pareto Optimal Solutions, which is then supplemented by the Max-Min approach to select an optimal solution from the compromised set. This study involves an unrelated parallel machine scheduling problem. Set-up times are sequence-dependent. Unrelated machines have different production rates,providing different processing times on the same job on different machines. In addition, they are different regarding the capacity to process jobs, i.e., unrelated machines can process different subsets of all jobs. Moreover, set-up time is different based on the machine and the jobs to be processed on the machine. Four mixed integer programming models are developed to represent the problems and three of them have the objective function of minimizing the makespan, total tardiness, and the number of tardy jobs, respectively. The last model is used to obtain the compromised solutions. Applying the AUGEMEN method, it provides the set of Pareto Optimal Solutions. Along with the Max-Min method to be able to select one of the compromised solutions in the Optimal Solutions.Recognizing the computational constraints given by large-scale problem instances in real systems, the study proposes a dynamic dispatching rule-based heuristic method. This algorithm uses four single dispatching rules that have been deliberately tuned to account for both machine- and sequence-dependent set-up time. These criteria include shortest completion time (SCT), shortest completion time based on longest processing time (SC-LPT), earliest due date (SC-EDD), and minimum slack (SCMinSlack). This novel technique seeks to give effective solutions for addressing the complexities inherent in large-scale scheduling difficulties in actual systems.
DOI: 10.14457/tu.the.2023.533
title: Industry 4.0 project for predictive maintenance and visibility problem with Arduino project

description: In global industries, including those in Thailand within the Industry 4.0 era, machinery plays a important role. There's a focus on examining factory machinery to create affordable equipment for machine inspection. We placed an Arduino device on an air compressor in a factory to collect vibration data and evaluate various hand machines' operational aspects over two months. The differences in vibration values between normal and abnormal states were noticeable. These vibration readings are useful for predictive maintenance, helping assess operational conditions for both typical and unusual machine states. This research is valuable for Small and Medium Enterprises (SMEs) as it supports the development of cost-effective machinery monitoring systems that are practical and economically viable.
DOI: 10.14457/tu.the.2023.534
title: Antiapoptotic proteins as targets for bioactive compounds: structural parameters and molecular design

description: Plant polyphenolics showcase multiple cancer activities, from antioxidant and anti-inflammatory to cytotoxic in different cancer models. Most cancers arise due to the over expression of antiapoptotic protein Bcl-2, which hinders the programmed cell death and lead to uncontrolled cell differentiation. The BH3 domain in Bcl-2 plays a crucial role in suppressing Bcl-2 expression, making BH3 mimetics essential in cancer treatments by promoting apoptosis in malignant cells. However, mutations in the BH3 domain have been discovered to cause resistance to currently available BH3 mimetics. Hence, numerous efforts are underway to develop BH3 mimetics as potential Bcl-2 inhibitors. This work investigates the binding interactions of five potential bioactive compounds with wild type (WT) Bcl-2 and mutant Bcl-2G101V protein, with the aim of elucidating their BH3 mimetic activity. The compounds were subjected to rigid and flexible receptor docking. Venetoclax was employed as the control ligand and literature available BH3 mimetics were docked into these target proteins to find common binding motifs of BH3 mimetics. The docking calculations were resulted procyanidin B2 with good docking scores, -8.30 and -8.80 kcal/mol with Bcl-2WT and Bcl-2G101V, respectively. This suggests its potential as a Bcl-2 inhibitor, warranting further consideration for in-depth investigation.