cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/tu.the.2018.934
title: Use of fly ash and bottom ash to enhance performance of expansive concrete

description: This study focuses on a mechanism of fly ash on expansion of concrete with expansive additive (EA concrete) and a study of bottom ashes with different water retainabilities as a sand replacing material and an internal curing material in mortar with expansive additive (EA mortar) and EA concrete.The mechanism of fly ash on expansion of EA concrete was investigated. There were three hypotheses to explain the effect of fly ash on expansion of EA concrete. First, the expansion enhancement of EA concrete containing fly ash was due to larger amount of expansive products in concrete with fly ash when compared to that without fly ash. Second, smaller stiffness of EA concrete containing fly ash during the early age leads to higher expansion. And third, fly ash delays the hydration of expansive additive causing less expansion to occur before the mixture gets hardened, but more expansion after the mixture hardens. Moreover, the effect of curing temperature on expansion of EA mortar containing high and low CaO fly ashes was also examined. Test results showed that the expansion increased when the curing temperature was increased, especially more obviously for EA-FAA mortar with high CaO fly ash.The effect of water retainability of bottom ash on properties of EA mortar and EA concrete was also studied. The concept to determine water retainability of bottom ash was also modified for being used in mix proportion calculation of bottom ash mortars and concretes. Mortar specimens were controlled a water to binder ratio. Concrete tests included two series, a controlled water to binder ratio concrete series and a controlled initial slump concrete series. Test results showed that flow of EA mortar was improved, the compressive strength decreased in EA mortar and EA concrete with controlled w/b ratios but increased in EA concrete with a controlled initial slump. The decrease of compressive strength of EA mortar containing bottom ash was caused by the high porosity. However, curing sensitivity of EA mortar was reduced by using bottom ash. Bottom ash affected differently on the length changes of EA mortar in different external curing conditions. The internal curing ability of bottom ashes provided enhanced expansion of EA mortar with sealed curing and EA concrete with moist curing, reducing total shrinkage of EA mortar with air curing when compared to EA mixtures without bottom ash. However, the total shrinkage of the EA mortar increased with the use of bottom ashes that had higher water retainability with 7 days of water curing and then air curing. Different bottom ashes also show different effects on the expansion of EA mortar in sodium sulfate solution.XRD-Rietveld, DTG analysis, and SEM analysis were carried out to detect the expansive products and support the explanation of the effect of fly ash and bottom ashes on expansion of EA mortar and EA concrete.
DOI: 10.14457/tu.the.2018.935
title: Forecasting solar PV installation of industrial sector in Thailand using system dynamics model

description: Solar photovoltaic (solar PV) is an environment-friendly technology forrenewable energy, and its price has considerably decreased in the past decade. As atropical country, Thailand can produce electricity from solar PV effectively, due to thegrow primarily in this last decade, especially the Thai industrial sector. REmap,collaborate plan of the Thai government and International Renewable Energy Agency(IRENA), sets a target of solar PV installation to reach 17,200 MW by the end of 2036.The industrial sector is the large electricity consumer in Thailand, and they have manychance and support to install solar PVsector, and industrial sector supported will make rapid growth in the number ofindustrial solar PV installation then it will cause a problem in demand forecasting forelectricity on the grid which old forecasting method cannot use in this situation. Baseon questionnaire and survey, we find out the most important factor, and their numericalrelationship after that use them to forecast solar PV electricity capacity in systemdynamics (SD) model from 2015 to 2036. In 2036, forecasted electricity capacity fromsolar PV is around 4.4 GW and the most affected factors are solar PV price andgovernment support.
DOI: 10.14457/tu.the.2018.936
title: Development of infrared-reducing coating from poly(3, 4-ethylenedioxythiophene) polystyrene sulfonate

description: The infrared- reducing coating is useful for reducing heat transfer from sunlight through windows. Transparent conductive oxides (TCO) such as fluorine tin oxide(FTO) have high optical transparency and NIR reflective properties making it suitablefor window coating. However, TCO is a required complex process to make thin-filmcoating and expensive. In this work, infrared (IR)-reducing glass coating employingpoly(3,4 ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) was tested anddeveloped for heat reducing performance.Heat- insulating PEDOT: PSS thin film was prepared by adding tetraethylorthosilicate (TEOS) as a binder and applied using a wired bar coater. The optical andinfrared shielding performance of the coatings was investigated using an ultraviolet-visible-near-infrared (UV-VIS-NIR) spectrometer. The obtained film showed infraredshielding property with about 25 %reduction in the NIR region ) 750- 2500 nm (whilemaintaining high transparency in the visible region of over 85 .%The film also showedgood scratch resistance upon TEOS addition with the pencil hardness level of 3Hincreased from 6B level in that of the pristine film. Illumination test showed thata window coated with the developed film can attain the temperature reduction by about1.3-3.4 ºC compared to that of the uncoated glass. The wettability of the film was alsoexamined and the water contact angle results indicated that the coated film displayedmore hydrophilicity than that of the uncoated glass which may promote the waterwetting of the coated glass leading to facile cleaning.
DOI: 10.14457/tu.the.2018.937
title: An exploration and assessment of the environmental pollutants from rigid polyurethane foam waste disposal in Thailand

description: Rigid polyurethane foam is a product resulted from the reaction between the polyols and the isocyanates. The production process also added some chemicals such as catalyst, a blowing agent, and a flame retardant. RPUF is widely used as thermal insulation; e.g., refrigerator, ice box, panel, spray, pipe, refrigerated truck. One of the essential applications is for refrigerator insulation. After the refrigerator was discarded, it was disassembled by the dismantler. RPUF was classified into the non-valuable material and disposed at a landfill or burning. The releasing chemicals led to environmental problems and human health issues. This research explores rigid polyurethane foam waste from the cradle to the grave, which was the chemical products to the disposal site and included the energy recovery plant. The results revealed that HCFCs, HFCs, and cyclopentane was added as a blowing agent, an amine group was added as a catalyst, and a flame retardant was not added for RPUF production. The survey information from 5 regions indicated that existing disposal options for RPUW were landfill (47.83%), open burning (21.74%), sanitary landfill (13.04%) incineration (13.04%) and refuse-derived fuel or RDF (4.35%), subsequently. For the environmental aspect, the prediction for the 2018 – 2033 period is that the disposal options with highest global warming impacts will be the incineration, open burning, and RDF. In term of stratospheres ozone depleting, incineration was the highest effect followed by RDF, and sanitary landfill, respectively. The current disposal methods with the highest level of the hydrogen cyanide emission toxicity are open burning, incineration, and RDF. The new scenarios of RDF methods were proposed to induce the waste to energy option. The environmental impacts from the shift of open burning to RDF (Scenario 1) resulted in the reduction of hydrogen cyanide emission. Whereas, the change of landfill to RDF (Scenario 2) increased the impact on global warming, ozone depleting, and hydrogen cyanide emission. However, Scenario 2 also had an advantage as it increases the landfill area for municipal solid waste. For the economic aspect, it was possible to install the shredding machine for RPUWs for both minimum wastes influence (300 tons/year) and maximum wastes influence (720 tons/year). The feasibility assessment results in positive NPV. The obtained IRR calculation presents profitability for both taking the loan and investing by the shareholder. The project investment cost would return within 4 and 1.61 years.
DOI: 10.14457/tu.the.2018.938
title: ATM fraud detection using location of transaction and outlier detection

description: ATM is the one of the most popular financial tools. It is prone to frauds that try to lure money out of customers' bank accounts. New patterns of ATM frauds have been regularly discovered, even though the occurrences are rare. In this way, a binary classification methods such as artificial neural networks and decision tree for predicting a fraud becomes insufficient due to an imbalanced between fraud and normal transaction. The pattern of transactions in each ATM account reflects the customer's behavior. Accounts' behavior features are extracted and applied with an outlier detection methods to detect anomaly transactions. Given a set of transactions, the accounts are grouped according to the location that the transactions took place, i.e., `local-only' and `has-abroad'. A feature is extracted from known legitimate transactions to reflect the normal behavior of the accounts in each group. An unknown transaction is classified either normal or fraud using an outlier detection. The experimental result shows that the proposed feature with an Isolation Forest outlier detection technique is able to detect all fraud transactions with low false detection.
DOI: 10.14457/tu.the.2018.939
title: Text fuzziness classification in thai code of laws

description: Research of Machine understanding aims to build an intelligence of machine. To allow a machine understand a context of human, precise concepts or knowledge are necessary. Numerous domains contain imprecise meanings while making decisions, for example a legal interpretation or a diagnosis. Once, in the future, an artificial intelligence will deal with imprecise data while pretending to be human-like, a vagueness in knowledges must be detected before constructing.This thesis presents the methodology to introduce fuzziness into Thai law texts using deep learning techniques. The experiments are designed to compare the performances of five well-known text classification methods, namely Logistic Regression, Decision Tree, Random Forest, Support Vector Machine, and Convolutional Neural Network. The fuzziness in this study refers to imprecise meaning in law texts which may be ambiguous when interpreted by a machine. We have constructed a labelled corpus from four Thai Law codes; (1) The Criminal Code (2) The Criminal Procedure Code (3) The Civil and Commercial Code, and (4) The Civil Procedure Code. This study defines three types of fuzziness sources as follows. The first type refers to fuzziness caused by a judge’s opinion, the second one points to fuzziness caused the uncertainty of evidence proof, and the last one implies to fuzziness caused by exception or other possible arguments in the legal codes. In this work, we study a classification model to classify whether the texts are fuzzy or not. To use as a dataset in the experiment, 5,888 passages from 2,787 sections of four Thai law codes are tagged as either a fuzzy text or an unfuzzy text. Compared to logistic regression (LR), decision tree (DT), random forest (RF), support vector machine (SVM) classifiers, the experimental results show that a convolutional neural network (CNN) significantly outperforms them with 96.49% of accuracy.
DOI: 10.14457/tu.the.2018.940
title: On design and implementation of service request composition systems using a cooperative multi-agent approach

description: Web service composition is an aggregation of two or more related web services to perform a particular task automatically. Though much attention has been paid on composing the new web service or increasing the efficiency as well as quality of such composition, a closely related but distinct problem of composing requests to existing combination services has been relatively unexplored. Users have a big pool of service combinations, however, they have no idea or it is beyond their capabilities to generate a request for using those. This problem could become so complex that demands a supporting system of their own kind. Therefore, we are motivated to design a supporting system that helps with composing web service request for complex systems. Since very less research has been done on this issue, we believe that our work will contribute a very first and important approach for further development.In the scope of this thesis, we first formalize such systems as logic programs, abstracting away from specific implementation languages. We then develop a communication protocol to combine them into a cooperative multi-agent capable of composing requests that cannot be composed by any individual system. We also discuss the potential advantages that future web service systems could take from our approach.
DOI: 10.18112/openneuro.ds002309.v1.1.0
title: AVLearn
DOI: 10.5281/zenodo.3541661
title: RNASeq de novo - toy dataset - 2 conditions 3 replicates paired-end 100bp 10000 reads

description: Transcriptomes of duck livers (Anas platyrhynchos) with 2 diets: force-feeding (A) or not (B)
DOI: 10.5281/zenodo.3541662
title: RNASeq de novo - toy dataset - 2 conditions 3 replicates paired-end 100bp 10000 reads

description: Transcriptomes of duck livers (Anas platyrhynchos) with 2 diets: force-feeding (A) or not (B)
DOI: 10.21227/h1rd-v757
title: Discriminative Concept Learning Network: Sample Source Code and Supplement (Project Archive)

description: The archive of DCLN project (https://sourceforge.net/projects/dcln/) is provided here. The source code is written in C/C++ and executable on Linux system. Details of hyperparameters tuning, data preprocessing and code compiling are given.
DOI: 10.21227/j3yp-0g03
title: Discriminative Concept Learning Network: Sample Source Code and Supplement (Project Archive)

description: The archive of DCLN project (https://sourceforge.net/projects/dcln/) is provided here. The source code is written in C/C++ and executable on Linux system. Details of hyperparameters tuning, data preprocessing and code compiling are given.
DOI: 10.5281/zenodo.3540896
title: Replication Package for: Scalable and Reliable Multi-Dimensional Aggregation of Sensor Data Streams

description: This repository contains a replication package and experimental results for our study on <em>Scalable and Reliable Multi-Dimensional Aggregation of Sensor Data Streams</em>. It features the presented implementation with Kafka Streams, tools for load generation and data collection, scripts for executing the presented evaluations as well as our raw results and script for analysis. A detailed description is given in the top-level README.md file.
DOI: 10.5281/zenodo.3541676
title: RNASeq de novo - toy dataset - 2 conditions 3 replicates paired-end 100bp 10000 reads

description: Transcriptomes of duck livers (Anas platyrhynchos) with 2 diets: force-feeding (A) or not (B)
DOI: 10.15128/r10v8380575
title: Threshold interface magnetization required to induce magnetic proximity effect [dataset]

description: Proximity-induced magnetization (PIM) has broad implications across interface-driven spintronics applications employing spin currents. We directly determine the scaling between PIM in Pt and the temperature-dependent interface magnetization in an adjacent ferromagnet (FM) using depth-resolved magnetometry. The magnetization due to PIM does not follow the generally expected linear scaling with the FM interface magnetization, as a function of temperature. Instead, it vanishes while the FM interface magnetization remains. The effective magnetic susceptibilities of heavy-metal (HM) layers are shown to give rise to the previously unexplained asymmetric PIM found in HM/FM/HM trilayers.
DOI: 10.17632/225wt23bzf.1
title: Indicadores Económicos Mensuales Seleccionados” de Puerto Rico del 2019.

description: La Junta de Planificación produce y recopila indicadores económicos que sirven para medir y visualizar la actividad económica de Puerto Rico. Los indicadores incluyen datos históricos de variables como (1) grupo trabajador, (2) empleo y desempleo, (3) turismo, (4) construcción, (5) energía eléctrica, (6) ingresos netos al Fondo General, (7) comercio exterior, (8) quiebras por capítulos, (9) ventas al detalle, (10) índice de precios al consumidor y (11) precio promedio mensual de la gasolina al detal. Las tablas que se publican presentan información comparativa de los cambios absolutos y porcentuales de mes a mes y respecto al año anterior (las series se presentan sin ajustes estacionales, para cada año fiscal y para el año natural). Igualmente, se publican documentos y gráficas de series históricas seleccionadas.
DOI: 10.17632/3825wsc396.1
title: VR-based Pedestrian Training Dataset (2018, Wuhan)

description: Objective: China has a high fatality rate for child pedestrians, which highlights the necessity of implementing more effective pedestrian safety training programs in elementary schools. We thus investigated the efficacy of using virtual reality (VR) as an instructional technology to identify and modify risky pedestrian behaviors among Chinese children. Methods: Seventy-nine children (grades 1 through 3) from three elementary schools in Hubei province participated and were categorized into urban (n = 20), migrant (n = 29), or rural (n = 30) students based on the schools’ locations. They completed a VR program comprising three street-crossing challenges to measure five pedestrian behaviors. The participants first attempted to complete the challenges by themselves in the first-time trial (T1) and then engaged in a personalized debriefing session before undertaking the challenges a second time (T2). Pedestrian performance for the two trials was compared by school location and grade level as between-subjects factors, and the rationale behind risky pedestrian behaviors was inductively analyzed. Results: Three risky pedestrian behaviors were observed in the program: dashing into the street, crossing on a blinking green light, and failing to check for traffic. Potential reasons for these behaviors included a lack of knowledge of road signs and traffic rules and the absence of daily adult supervision. The overall pedestrian performance increased from T1 to T2 with a moderate effect size (Ƞp2 = 0.59, P &lt; .001). A significant main effect of the trials was found for the three pedestrian behaviors (for all values, P &lt; .001); however, interactions of trial by location and trial by grade were nonsignificant in all univariate tests (for all values, P ≥ .05). Conclusions: VR is an effective technology to diagnose and correct risky pedestrian behaviors among Chinese children when accompanied with individual debriefing and repetitive practices. School location and grade level had no significant influence on children’s pedestrian performance and learning outcomes, indicating the ubiquity of the pedestrian safety problem and the need for more effective instructional interventions.
DOI: 10.17632/3825wsc396.2
title: VR-based Pedestrian Training Dataset (2018, Wuhan)

description: Objective: China has a high fatality rate for child pedestrians, which highlights the necessity of implementing more effective pedestrian safety training programs in elementary schools. We thus investigated the efficacy of using virtual reality (VR) as an instructional technology to identify and modify risky pedestrian behaviors among Chinese children. Methods: Seventy-nine children (grades 1 through 3) from three elementary schools in Hubei province participated and were categorized into urban (n = 20), migrant (n = 29), or rural (n = 30) students based on the schools’ locations. They completed a VR program comprising three street-crossing challenges to measure five pedestrian behaviors. The participants first attempted to complete the challenges by themselves in the first-time trial (T1) and then engaged in a personalized debriefing session before undertaking the challenges a second time (T2). Pedestrian performance for the two trials was compared by school location and grade level as between-subjects factors, and the rationale behind risky pedestrian behaviors was inductively analyzed. Results: Three risky pedestrian behaviors were observed in the program: dashing into the street, crossing on a blinking green light, and failing to check for traffic. Potential reasons for these behaviors included a lack of knowledge of road signs and traffic rules and the absence of daily adult supervision. The overall pedestrian performance increased from T1 to T2 with a moderate effect size (Ƞp2 = 0.59, P &lt; .001). A significant main effect of the trials was found for the three pedestrian behaviors (for all values, P &lt; .001); however, interactions of trial by location and trial by grade were nonsignificant in all univariate tests (for all values, P ≥ .05). Conclusions: VR is an effective technology to diagnose and correct risky pedestrian behaviors among Chinese children when accompanied with individual debriefing and repetitive practices. School location and grade level had no significant influence on children’s pedestrian performance and learning outcomes, indicating the ubiquity of the pedestrian safety problem and the need for more effective instructional interventions.
DOI: 10.17632/8jjjkkrswp.1
title: Measured Time-energy Performance of Blockchain on Brawny and Wimpy Nodes

description: This repository contains time-energy performance measurements of both brawny (high-performance) and wimpy (low-power) nodes running three blockchains, namely Hyperledger Fabric v0.6, Ethereum v1.8.15, and Parity v2.1.6. Brawny nodes are represented by traditional server systems based on Intel Xeon CPU, and wimpy nodes are represented by (i) a low-power Intel NUC with Intel Core i3 CPU, (ii) an Nvidia Jetson TX2 with 64-bit ARM CPU, and (iii) a Raspberry Pi 3 Model B running 32-bit ARM software. To benchmark the blockchain systems, we use BLOCKBENCH with its micro-benchmarks at single-node-level and macro-benchmarks at cluster-level. These measurements are analyzed in the research paper entitled "Blockchain Goes Green? An Analysis of Blockchain on Low-Power Nodes". In summary, we show that low-end wimpy nodes, such as Raspberry Pi 3, are unable to run full-fledged blockchains due to the limited size and low bandwidth of their main memory. In contrast, wimpy nodes with a balanced performance-to-power profile, such as Jetson TX2, can save significant energy while achieving reasonable performance compared to brawny nodes. In particular, our measured data shows that 8 Jetson TX2 nodes achieve almost 80% and 30% of the throughput of Parity and Fabric, respectively, while using 18 and 23 times less energy compared to 8 Intel Xeon servers.
DOI: 10.17632/r69rjpwwrj.1
title: Sense of Belonging and Grit in E-learning

description: This was collected from 441 postgraduate learners who responded via an online survey to examine the role of sense of belonging and grit toward e-learning usage. Structural Equation Modelling(SEM) via Smart PLS was utilized to analyze the data collected.
DOI: 10.17632/r69rjpwwrj.2
title: Sense of Belonging and Grit in E-learning

description: This was collected from 441 postgraduate learners who responded via an online survey to examine the role of sense of belonging and grit toward e-learning usage. Structural Equation Modelling(SEM) via Smart PLS was utilized to analyze the data collected.