cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.14457/tu.the.2021.552
title: Development of gel electrolyte from agar for using in Ag/AgCl electrode

description: Ag/AgCl reference electrode (Ag/AgCl) is frequently employed among the reference electrodes due to its simplicity, low cost, and environmental-friendly with non-toxic components. Normally, Ag/AgCl reference electrode is filled with liquid electrolyte making it prone to leakage or evaporation loss and is also difficult to maintain. Gel polymer electrolyte (GPE) is an alternative for use as electrolyte in reference electrode that can provide high flexibility, low maintenance, and possibility for miniaturization. In this work, the Ag/AgCl reference electrode was constructed using agar gel for its electrolyte. Agar, glutaraldehyde (GA), and potassium chloride (KCl) were used for preparation of GPE. The prepared gel has low evaporation loss, good mechanical strength and good conductivity. It can be stored without the appearance of salt creep or fungal mold for over 6 months. A prototype reference electrode was also constructed from a pipette tip and silver wire. The silver wire was passivated with a layer of AgCl by passing an electrical current in 0.05M KCl for 10 minutes. Porous PTFE was placed at the end of the pipette tip forming the ion-conductive porous junction. This prototype Ag/AgCl reference electrode was used to test for the potential stability and the potential difference against a standard commercial Ag/AgCl electrode in 0.1M, 1M, 2M and pH 4, 7, 10 solution for the short-time stability of 5-minutes and longer-time stability of 10 hours. The fabricated reference electrode showed good precision and stability. The drift over 5-minutes stability was less than 10 hours stability and was less than 1 mV. The maximum potential difference compared to the standard commercial electrode was less than 16 mV in various solutions.
DOI: 10.14457/tu.the.2021.553
title: Properties of pastes and mortars containing ammonia contaminated fly ash

description: Selective Catalytic Reduction (SCR) and Selective Non-Catalytic Reduction (SNCR) are widely used for NOx emission control in coal-fired power plants. In the SCR and SNCR processes, liquid ammonia (NH3(aq)) or urea is injected into the system or flue gas stream and reacts with NOx in the flue gas to yield diatomic nitrogen (N2) and water (H2O). Unreacted ammonia in the flue gas after the NOx reduction process is defined as slip and it contaminated the fly ash, yielding ammonia-contaminated fly ash. Ammonium sulfate (NH4)2SO4 and ammonium carbonate (NH4)2CO3 are the forms mostly found in ammonia-contaminated fly ash. This study is aimed to investigate the effects of ammonia that contaminate high CaO and low CaO fly ash on the properties of pastes and mortars. (NH4)2SO4 or (NH4)2CO3 solutions are set in a concentration range of 0 to 1000 ppm (mg of NH3 per kg of fly ash). The results confirmed that both (NH4)2SO4 and (NH4)2CO3 reduced the normal consistency and led to less water requirement of fresh pastes. (NH4)2SO4 decreased the compressive strength of the mortars. Oppositely, (NH4)2CO3 increased the compressive strength of the mortars. The addition of (NH4)2SO4 or (NH4)2CO3 increased the autoclave expansion of pastes. Sulfate expansion test results showed that both of (NH4)2SO4 and (NH4)2CO3 increased the sulfate expansion of the mortars, but the expansion was still lower than the OPC-only mortar. The formation of gypsum and ettringite was considered to cause the expansion of the paste and mortar specimens. The results of autogenous shrinkage indicated that (NH4)2SO4 and (NH4)CO3 decreased autogenous shrinkage of the mortars.
DOI: 10.14457/tu.the.2021.554
title: Electrospun nanofibers of polylactide (PLA) stereocomplex with super-hydrophobic surfaces for potential use in facial mask and biomedical applications

description: Polylactide (PLA) is a biodegradable to replace the fossil-based polymers and able for use in many applications. The enantiomeric forms of PLA are poly(L-lactide) (PLLA) and poly(D lactide) (PDLA). The best stereocomplexation are made from a mixture of PLLA and PDLA in ratio 1: 1. A stereocomplex crystal form improves melting temperature and better mechanical properties. Hydrophobicity is a property that shows the wettability at surface of materials. Alkyl ketene dimers (AKD) is organic wax compound in specifically reacting between opening rings of AKD with hydroxyl groups of PLAs. In this work, process of electrospinning and film casting of PLA stereocomplex and AKD blended and coated was investigated. Additional with effect of different types and molecular weights of PLLA and PDLA (low molecular weight PLLA and hyper-branched PDLA), which studies by employing differential scanning calorimetry (DSC), fourier transform infrared (FTIR) spectroscopy, field emission scanning electron microscope (FE-SEM), polarized optical microscope (POM), universal testing machine (UTM), water contact angle (WCA) measurement, and X-Ray diffraction (XRD) machine. Stereocomplexation shows the different diameter size of fibers from different molecular weight, different crystal formation, improves mechanical and thermal properties. The surface treated-nanofibers and films show improvements in crystallinity, mechanical properties, and surface hydrophobicity. In part of stereocomplex from low molecular weight PLLA, showed the low diameter size of electrospun fibers and observed beats feature. HB-PDLA shows the increasing of stereocomplex crystallinity and good contribution of AKD blended. Casting films show the decreasing size of stereocomplex film but increasing after blended with AKD or using HB-PDLA to make a stereocomplexation. The materials have high potential for use in various applications, especially in biomedical applications as facial mask, cell scaffold, or wound dressing materials.
DOI: 10.14457/tu.the.2021.555
title: Development of toughened PLA filaments by blending with alcoholized PLA-cured epoxidized natural rubber for 3D-printing application

description: Polylactide (PLA) has become a promising alternative to petroleum-based polymers. However, this has a major drawback as its inherent brittleness limits its use in certain applications. Toughening of PLA by blending with various elastomers have been widely investigated, pertaining to its eco-friendly and cost-effective benefits. In our lab, a chemical recycling process of PLA wastes has been developed by alcoholysis reaction, which yields glycolyzed PLA oligomers (GPLA). In this study, the GPLA products are employed as curing agents for epoxidized natural rubber (ENR), which were then used as toughening agents for PLA resin for use in 3D-printing applications. ENR with 25% degree of epoxidation was used in the reaction with the OH-capped GPLA by using a reactive melt-blending technique in an internal mixer. The effects of GPLA/ENR25 feed ratio on the structures and properties of the resulting GPLA-cured ENR products (GENR) were examined by varying the ratios from 1:1, 1:2, and 1:4 (referring to GENR14, GENR12 and GENR11, respectively). The resulting GENR samples were then blended with neat PLA resin at different GENR contents from 5 to 30%wt. Mechanical and physical properties, phase compatibility and morphology of the blends were examined. Improvements in the toughness were observed, compared to those blended with neat ENR, due to the ductility of the rubber phase and enhanced compatibility from the GPLA segments. The incorporation of 20%wt GENR12 possessed the smallest rubber domains dispersed in the PLA matrix (1 µm), reflecting enhancements in the phase compatibility.PLA-GENR12 blends was selected for extruding as monofilaments with 1.75mm extruder die at different extrusion speeds of 35 and 50 rpm (referring to PGE35 and PGE50, respectively) in a range of extrusion temperature from 140 – 165 oC. However, the optimization of processing needs to be reconsidered to obtain uniform filament diameter at 1.75 mm of 3D filament standard. Izod impact specimens were printed with different printing orientations to examine the printing performances and toughness of the printed products. The prepared filaments can be successfully printed in the flat and on edge orientations, while the up-right orientation cannot be printed due to shape distortion. It was found that the printed specimens of PGE50 filaments exhibited an acceptable printing performance and higher impact strength than others filaments (p-PLA and c-PLA filament). The printed PGE50 impact specimen showed the highest impact strength at 31.6 ± 1.4 J/m with an on-edge printing orientation, which was highly competitive to injection molded neat PLA specimens (33 ± 1.0 J/m of impact strength). Therefore, the blended PLA/GENR12(80/20) material show high potential as new promising material as monofilaments for 3D-printing applications, pertaining to their minimized raw material consumption and environmentally-friendly aspects.
DOI: 10.14457/tu.the.2021.556
title: Automatic Thai news summarization using deep learning

description: Nowadays, there are a lot of textual data available on the internet, and their number is continuously growing every day. Nevertheless, the data available on internet are redundancy. Therefore, it is time-consuming and laborious to find the information for similar data manually. It is necessary to provide the better mechanism to extract the useful and significant information quickly and effectively. Text summarization is thus one of the methods that can solve such problem.This research proposed automatic Thai news summarization based on a hybrid approach for a single document. We combined both extractive and abstractive summarization approaches to improve the performance of the model. In addition, we simply augmented dataset by using the original documents of the training dataset to augment to be the input documents and summaries. The augmented economic dataset is unlabeled data. We added the unlabeled data in the training dataset because we would like to give the model to learn language model to improve the grammatical structure of the output summary. Besides, we study how the document length and word position affects the performance of the deep learning models.According to the results, we found that our proposed model obtained ROUGE-1 = 0.6456, ROUGE-2 = 0.4108, and ROUGE-L = 0.6372. The model can generate the output summary that is readable and grammatically correct. For studying the document length and word position affects the performance of the deep learning models, we found that the deep learning models can summarize a short document better than a long document. Regrading words position, the deep learning models work well in the original documents that have import words appear in the beginning of the original document.
DOI: 10.14457/tu.the.2021.557
title: Text summarization based on argumentation techniques

description: Automatic Text Summarization is one of the Natural Language Process (NLP) studies that aim to build a model for automatically shortening an input text/document while still retaining the necessary information; thus, a conclusion is the output of that model. A machine of Deep Learning (DL) uses a watch-and-learn strategy to imitate task working by consuming a large learning dataset. With the growth of information, DL has become favored and a new basis for most Artificial Intelligence (AI) applications. They have achieved much improved results, even in automatic text summarization. Unfortunately, the DL-based methods are generally constructed under deep and complicated architecture like a block-box, which is uneasy about interpreting.In another corner of AI research, Formal Argumentation aims to develop a formalism system for evaluating arguments based on human-intuitive logical reasoning. This causes Formal Argumentation to be in the spotlight of many tasks that desire transparency. Specifically, Dung's Abstract Argumentation (AA) framework can prove argumentation semantics from arguments, such as acceptability. As abstractive, it does not pay attention to how to construct arguments and attacks by projecting them as nodes and edges in a directed graph. AA is considered a milestone in computational argumentation studies, saying it inspired many researchers to explore internal argumentative structures such as Assumption-based Argumentation (ABA) and ASPIC+.This research aims to mimic how competent readers perform text summarizing by re-constructing the arguments in the text and then arriving at the summary from conclusions of acceptable arguments using formal argumentation techniques. Assuming the availability of the Argumentative Discourse Unit (ADU) graph of the given text, we build structured argumentation frameworks inherited from AA: simplified ASPIC+ and ABA representing the text. Then we use ABA proof procedures to re-construct arguments in the text and evaluate their acceptabilities. In the final stage, we aggregate the conclusions of acceptable arguments.We implement the proof-of-concept experiment of the proposed approach using a small argumentative dataset called Micro-text dataset and compare results to other text summarization techniques. As a result, our summarizer provides comparable results and reasonable relations between text segments of the generated summary. Additionally, we describe the difference between this approach and similar published studies. This research contributes that a transparent AI engine viz. text summarization based on Argumentation. This approach encourages the development of further applications in that their decisions affect humans, such as an automated judicial review or legal case summarization.
DOI: 10.14457/tu.the.2021.558
title: A study of sensor fusion based vehicle distance estimation for self-driving cars

description: The self-driving car has become attractive and modern. The self-driving car consists of several systems such as navigation, localization, avoidance, and more. LiDAR, Radar, GPS, Inertial Measurement Unit (IMU), Ultrasonic, camera were sensors, which those sensors were used in the self-driving car. The method to integrate those sensors work together is Sensor Fusion. This method uses diverse types of sensors that work similarly to one sensor. This research proposes a method that uses a combination of sensors for distance estimation. Multiple Lidars and a camera contribute to the improvement of data processing for the Kalman filter. The Object detectionmethod will locate and classify the object in the research. This research will help develop driving systems such as emergency braking, velocity calculation, and collision warning system.
DOI: 10.14457/tu.the.2021.559
title: Inventory positioning and optimal cycle service level in a supply chain under stochastic demand and lead time

description: In this research, the inventory positioning problem under stochastic demand and lead time is solved by a mixed-integer programming model. The inventory placements involve a decision that determines where to keep safety stocks within a supply chain network such that the total holding inventory cost is minimized while maintaining an acceptable customer service level (CSL). In this study, the decision variables are theposition, amount of safety stock at each location, and service level while the objective function is the total holding inventory cost. The total holding inventory cost includes the holding cost of raw materials, the holding cost of finished goods, the shortage costof raw materials, and the shortage cost of finished goods. The commercial methodology is used to find the optimal solution for each model. In addition, this study concerns three mathematical models including the basic inventory positioning model, the singleservice level model, and the multiple service levels model. Selected numerical experiments and a case study are presented to examine the applicability of the proposed mathematical model. The findings indicate that the optimal results are easily obtained via a commercial solver and the proposed approach is suitable for various types of supply chain networks.
DOI: 10.14457/tu.the.2021.560
title: Eumelanin encapsulated polymeric particles using poly(D-lactide-CO-caprolactone) block copolymers and their stereocomplex

description: Eumelanin as a natural pigment present several key functional properties that can protect human skin from ultraviolet (UV) light. Photoprotection ability that can absorb most of the UV light as a result of aromatic compounds in its structures has drawn vast interest to harness its excellent properties for various applications. Major drawbacks shown by organic molecules as UV absorber that limits their application includes their short lifespan. Encapsulation of the compound by various shell materials has been extensively studied to further optimize and extend its shielding efficiency fromUV radiation. Polylactide (PLA)-based copolymers are widely used in encapsulation of various active compounds, due to their biocompatibility and biodegradability, promoting the sustained release of the active compounds. In this study, stereocomplexPLA (sc-PLA) formed by blending of poly(D-lactide-caprolactone-D-lactide), P(DLAb-CL-b-DLA), triblock copolymer with linear poly(L-lactide), PLLA, was employed in the encapsulation of eumelanin. An oil in water emulsion (O/W) approach followed bysolvent evaporation was performed in encapsulation process. Effect of eumelanin distribution in PLA’s enantiomers and ultrasonication on physicochemical properties, encapsulation efficiency, and release behavior of nano/microparticles was evaluated. The potential application of the resulting particles for sunscreen was also examined by measuring the UV absorbance and in vitro sun protection factor (SPF) of sunscreen containing particles in the UVA-UVB region. FTIR spectra of the particles show characteristic peaks of sc-PLA with the changes in the intensity of significant peaks that correspond to eumelanin, denoting the success of the encapsulation process.Morphological image analysis reveals that the resulting particles have spherical shaped with the particle size that can be controlled by applying ultrasonication. Distribution of eumelanin in copolymer and ultrasonication process promote the growth of sc-PLAwith highly ordered arrangement and more efficient entrapment of eumelanin. The resulting particles present relatively higher initial burst release and faster release rate than its counterparts. The small particle size provided by ultrasonication also affects thecytotoxic activity of the resulting particles, where the cytotoxic activity increased at relatively high concentration of particles. High content of eumelanin inside the particles and large surface area improves the UV absorbance and sunscreen performance of theparticles. The results of this study suggest that eumelanin-loaded particles can be potentially used as UV shielding material in diverse applications, especially in the cosmetic and pharmaceutical fields.
DOI: 10.5281/zenodo.7060462
title: Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Joint Optimization of Production and Maintenance

description: Using the previous datasets at &lt;https://zenodo.org/record/4106746&gt;, &lt;https://zenodo.org/record/7055698&gt;, &lt;https://zenodo.org/record/7055580&gt;, and &lt;https://zenodo.org/record/7055573&gt; a joint optimization of production and maintenance scenario was formulated which aims at combining all the features from the cited scenarios. For energy selling, it was considered an added sales value corresponding to 50% of the buying. Regarding maintenance activities, it was simulated an announcement of a maintenance activity for MAQ118 from Monday at 07:00 (i.e., period 1) to Monday at 17:00 (i.e., period 120), and another for MAQ120 which can be done at any time. These maintenance activities take 6 hours and 10 minutes to complete and have an associated labor cost of 3,22 EUR/hour in maintenance hours, and a double cost penalty (i.e., 6.44 EUR/hour) if done out of maintenance hours. The scenario was executed in 2 hours, with the corresponding optimization weights of 0.8 and 0.2 for the total cost and machine occupancy deviation, respectively. File Description: Input_JSON_Joint_Optimization_Production_Maintenance - JSON input data for the joint optimization of production and maintenance Output_JSON_Joint_Optimization_Production_Maintenance - JSON output data for the joint optimization of production and maintenance Output_Statistics_Joint_Optimization_Production_Maintenance - Excel output joint optimization of production and maintenance statistics
DOI: 10.5281/zenodo.7060461
title: Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Joint Optimization of Production and Maintenance

description: Using the previous datasets at &lt;https://zenodo.org/record/4106746&gt;, &lt;https://zenodo.org/record/7055698&gt;, &lt;https://zenodo.org/record/7055580&gt;, and &lt;https://zenodo.org/record/7055573&gt; a joint optimization of production and maintenance scenario was formulated which aims at combining all the features from the cited scenarios. For energy selling, it was considered an added sales value corresponding to 50% of the buying. Regarding maintenance activities, it was simulated an announcement of a maintenance activity for MAQ118 from Monday at 07:00 (i.e., period 1) to Monday at 17:00 (i.e., period 120), and another for MAQ120 which can be done at any time. These maintenance activities take 6 hours and 10 minutes to complete and have an associated labor cost of 3,22 EUR/hour in maintenance hours, and a double cost penalty (i.e., 6.44 EUR/hour) if done out of maintenance hours. The scenario was executed in 2 hours, with the corresponding optimization weights of 0.8 and 0.2 for the total cost and machine occupancy deviation, respectively. File Description: Input_JSON_Joint_Optimization_Production_Maintenance - JSON input data for the joint optimization of production and maintenance Output_JSON_Joint_Optimization_Production_Maintenance - JSON output data for the joint optimization of production and maintenance Output_Statistics_Joint_Optimization_Production_Maintenance - Excel output joint optimization of production and maintenance statistics
DOI: 10.20372/aau_rdr/frhc2x/gzursu
title: Raw data compiled for thesis entitled ''External Intervention in the current Ethiopia-Sudan Border Dispute''.doc

description: :unav
DOI: 10.20372/aau_rdr/frhc2x
title: EXTERNAL INTERVENTION IN THE CURRENT ETHIOPIA-SUDAN BORDER DISPUTE

description: This raw data is generated for M.A thesis work under the Center for Regional and Local Development Studies. The raw data is collected through key informant interview
DOI: 10.5281/zenodo.7055573
title: Joint Optimization of Production and Maintenance for Cost-effective Manufacturing and Demand Response Participation Dataset - Maintenance Optimization

description: Using the previous dataset at &lt;https://zenodo.org/record/4106746&gt; a maintenance optimization scenario was formulated to validate the scheduler's ability to schedule tasks as well as maintenance activities while also minimizing the total costs. Accordingly, it was considered an optimization weight of 1 for the total cost and 0 for machine occupancy deviation, as well as a 2-hour execution time for the genetic algorithm. Each maintenance activity, for every machine, has a duration of 6 hours and 10 minutes, with a labor cost of 3,22 EUR/hour during the stipulated maintenance hours and a monetary penalty, that doubles the cost (i.e., 6.44 EUR/hour) if done out of maintenance hours. File Description: Input_JSON_Maintenance_Optimization - JSON input data for the maintenance optimization Output_JSON_Maintenance_Optimization - JSON output data for the maintenance optimization Output_Statistics_Maintenance_Optimization - Excel output maintenance optimization statistics