bluuebunny/crossref_metadata_2025_split huggingface dataset:
Variation of Structural and Hyperfine Parameters of (Fe0.70Al0.30)1-xNbx, with x=0, 0.05, 0.10 and 0.20 System
Authors: Rodríguez R R , Pérez Alcázar G A , Colorado H , Zamora L E 
Published: July 2020

Abstract
Fe0.70Al0.30 alloy is a bcc and ferromagnetic phase, being the Al atoms magnetic dilutor. In this work, we study the effect of the Nb on the structural and hyperfine behavior of the Fe0.70Al0.30 alloy when atoms of Nb substitute atoms of Fe or Al. The nanostructured system of (Fe0.70Al0.30)1-xNbx (x = 0, 0.05, 0.10, 0.20, at. %) was obtained by alloying Fe, Al and Nb powders in a planetary ball mill during 12 h, 24 h and 36 h, and a ball mass to powder mass relation of 10:1. The magnetic and hyperfine properties of the samples were studied by X-ray diffraction (XRD) and Mössbauer Spectrometry (MS) at room temperature, respectively. The X-ray diffraction patterns for x=0 showed the bcc-α FeAl structure and its lattice parameter is approximately constant with milling times (∼ 2.91 Å). For x=0.05, 0.10 and 0.20 the patterns showed the coexistence of the α-FeAl, Nb(Fe,Al)2 structural phases with an amorphous component. The Mössbauer spectra of x=0 samples were fitted using hyperfine magnetic field distributions (HMFDs), and the obtained mean hyperfine fields (MHF) were 23.4, 24.2, and 24.3 T for 12, 24, and 36 h of milling time, respectively, which correspond to the α-FeAl structure. The spectra of the samples with x=0.05 and 0.10 were fitted using a model with two components, the first one is a HMFD attributed to the bcc-FeAlNb structure and the second with two doublets attributed to the Nb(Fe,Al)2 structure. When atomic percentage of Nb increases up to 20 at. % the ferromagnetic behavior is diluted due to substitution of Fe-atoms by Nb and Al atoms in the bcc-FeAlNb structure. The magnetic behavior becomes paramagnetic at x=0.20, the spectra were fitted with three doublets, one of them related with bcc-FeAlNb structure and the others to the Nb(Fe,Al)2 structural phase. The alloying of Nb to the Fe0.70Al0.30 system destroyed the magnetism due the substitution of Fe by Nb atoms and generates an amorphization into the system.
Chemical and morphological analysis of formation of rGO/ZnO composite obtained by microwave-assisted hydrothermal method
Authors: Merlano Aura S , Pérez F R , Cabanzo Rafael , Mejía Enrique , Hoyos Lina M , Salazar Ángel 
Published: July 2020

Abstract
A chemical synthesis route for facile, fast and economical production of reduced graphene oxide/zinc oxide composites (rGO/ZnO) via a microwave-assisted hydrothermal method is presented. For a particular concentration (124 mM) of zinc acetate di-hydrate (Zn(CH3COO)2.2H2O) acting as precursor of Zn, different microwave irradiation times of the order of seconds were tested in order to select the more adequate time. Furthermore, with the selected irradiation time (40 s), different concentrations (31, 62 and 124 mM) were then considered and chemical and morphological properties of the obtained composites were evaluated. For their characterizations SEM, EDS, FTIR, Raman spectroscopy and XRD were employed. Experimental results confirm that the proposed synthesis route for the fabrication of rGO/ZnO is efficient, environmentally friendly and cost-effective.
Electroencephalography based Emotion Recognition using Fisher’s Linear Discriminant Analysis on Support Vector Machine
Authors: Yulita I N , Novita D , Sholahuddin A , Emilliano  
Published: July 2020

Abstract
Emotions as intense feelings for reactions to something affect someone in interacting with others such as in determining choices, actions, and perceptions. The emotional state of an individual can be seen clearly through facial expression and tone of speech. Apart from facial features or voice features, identification of emotions can also be done through brain waves. This study used an electroencephalogram signal as an input to recognize types of emotions. The electroencephalogram signal was chosen because it can record the true emotions of individuals. The recognition of emotions based on Support Vector Machine (SVM). To improve the performance, this method was combined with Fisher’s Linear Discriminant Analysis (FLDA). The experiments showed the SVM performance increased above 30%. As a comparison, this research also implemented Multi-Layer Perceptron (MLP). The results showed that the performances of SVM and FLDA-SVM were higher than MLP or FLDA-MLP. It showed that FLDA-SVM was the best method of this research in recognizing emotions.
Fuzzy Logic System Implementation with Mamdani Method in Computer-Based Intelligence Quotient Test to Determining the Type of Intelligence Dimension
Authors: Putri G N , Dirgantoro B , Aulia P , Setianingsih C 
Published: July 2020

Abstract
A person of a thing can cultivate intelligence in areas of interest, sometimes many people complain because the results of their intelligence quotient test (IQ) show unsatisfactory results. Because they are still looking only lies in those abilities. Intelligence quotient tests are used to explore knowledge about certain individual skills and intelligence. To determine someone’s intelligence, it takes a long time to analyze and get the test output from calculations by certain methods manually. The determination of a person’s dimension intelligence can be done by certain method, this research is one way to make a fuzzy model for the type of intelligence dimension support system based on standardization in psychology The result of this research is expected to explain how to modeling the fuzzy logic system with Mamdani method in a support system to determine the types of intelligence dimensions, namely the festigung / exact or flexibilitat / non-exact.
Detecting the Burned Area in Volcanic Region by Using Multitemporal Landsat-8 OLI (Case Study: Mt. Sumbing, Central Java)
Authors: Prasasti I , Triyono D , Suwarsono  
Published: July 2020

Abstract
Biomass burning is one of the natural agents that most change terrestrial ecosystems and has a key ecological role in a huge piece of the Earth’s surface. Biomass burning has numerous socio-economic implications, particularly in developed countries where the developing urbanization of forested regions tends to increase accidents related with extraordinary fire occasions. Wildland fire mapping has been a subject vital for the international community over the recent two decades. Since fire is a major threat to forests and wooded areas in the tropical environment of Kalimantan, methodical regional fire observing is a need. Remote sensing methods are recognized as the efficient source of information for mapping burned areas from regional-national up to global scale. This study investigated the use of multitemporal Landsat-8 OLI (Operational Land Imager) data, to identify the burned area, in the tropical region of Indonesia, during 2019 fire season. A pair of Landsat-8 OLI, collected before and after fires, has been used to delineate the boundaries of sample location of burned area. Then, the difference of reflectance and Normalized Burn Ratio were analyzed. Fire incident causes landcover changes from vegetated land to bareland. This changes can affect the reflectance detected from Landsat-8 OLI. The result showed that biomass burning on volcanic region has caused high decreasing values on band 5 and there were high increasing on band 7. The NBR was better used to extracted burned area rather than NDVI or single spectral band. This method based on multitemporal optical data, creates a valuable tool for identifying and interpreting burned area following a fire event on volcanic region.
Shallot Quality Classification using HSV Color Models and Size Identification based on Naive Bayes Classifier
Authors: Susanto A , Dewantoro Z H , Sari C A , Setiadi D R I M , Rachmawanto E H , Mulyono I U W 
Published: July 2020

Abstract
This research proposes a method of classification of shallots based on quality using the Naïve Bayes Classifier. The Naïve Bayes classifier is a classifier based on statistics and simple probabilities that are widely used in many sophisticated learning methods today. Shallots are classified into three classes, namely good, medium, and poor quality. To get good classification results, appropriate extraction of features is needed, in this case, color feature extraction is selected with the hue saturation value (HSV) model and to identify the size the area, metric and perimeter calculations are used. To get the right size, some morphological operations such as filling holes and opening are performed. Based on the experimental results on 60 training data and 60 testing data classification shallot quality using Naïve Bayes Classifier produces an accuracy of up to 91.67%.
Securing Text Messages using the Beaufort-Vigenere Hybrid Method
Authors: Sugiarto E , Setiadi D R I M , Fahmi A , Rachmawanto E H , Sari C A , Sarker Md K , Widjajanto B 
Published: July 2020

Abstract
Beaufort and Vigenere are fast and strong substitution encryption methods against brute force attacks if they have good key quality. But both of these methods by default can not produce a good avalanche effect. Avalanche effect is a measuring tool that can determine the strength of encryption from differential attacks. This research proposes hybrid techniques of Beaufort and Vigenere algorithms to optimize the security of text message encryption by modifying key generators. With this method, the encryption process can be done by input text messages and keys. The key is processed with a key generator to produce two new keys that are used for encryption using the Beaufort and Vigenere hybrid methods. Based on the test results, the Avalanche effect value rose significantly compared to the standard method, and the value of the avalanche effect was more stable and close to ideal compared to the previous method. The time required is also relatively very fast for the encryption or decryption process, experimental result shows it takes less than 0.1 seconds for more than 43 thousand of characters in the text message.
Wireless communication design of internet of things based on FPGA and WiFi Module
Authors: Wibowo F W 
Published: July 2020

Abstract
The implementation of the internet of things (IoT) has been many researched. Some applications have their own designs and special uses. Low-cost designs and multi-usage are always targeted on the implementation either using a microcontroller or field programmable gate arrays (FPGAs). The reconfigurable device of FPGA in some cases has advantages in its uses. This paper has designed the communication of the radio frequency (RF) for the IoT using wireless communication based on the FPGA and wireless fidelity (WiFi) of the ESP8266 WiFi module. The research methodology used in this paper was a simulation using Xilinx ISE software for the device of the Xilinx Spartan-3E FPGA that has been configured using Very High Speed Integrated Circuit Hardware Description Language (VHDL). The result of the ESP8266 driver based on the FPGAs is sent to the JSON based website.
Design of Phishing Simulation Dashboard Using Analytic Data Concepts
Authors: Septiana R , Julian R K 
Published: July 2020

Abstract
Security awareness is the main concern of phishing attack prevention. Every internet user will deal with a serious issue. Phishing is the falsification of messages that aims to retrieve important information from the recipient of the message. In a company, phishing becomes a serious problem because it can come to all employees suddenly. Employees who do not understand the dangers of phishing are the most dangerous threats because they are likely to be the main supporters of the success of phishing attacks. Understanding of phishing attack can be seen from the way the worker responds to incoming messages. A company makes a phishing simulation to find out the handling of the employee on a fake message came. One of the phishing simulation tools is web forgery. In this research, phishing simulations attack every employee in a company. The employee will receive a message that contains a field. The result will show a percentage of employee that successfully attacked. The results will be displayed on a dashboard after being processed using an analytic data concept. The processes of data analytic involve business intelligent software called QlikView. The software gives a percentage of the employee who opens the fake message and fills some data in the fields is about 13.9%.
Development of Web-based Research and Community Service Database at Universitas Negeri Surabaya
Authors: Warju  , Cahyaningrum S E , Nurkholis  , Saksono L , Nudin S R , Ariyanto S R 
Published: July 2020

Abstract
One of the data used as a benchmark for determining the progress of a university can be seen from the productivity of research and community service. The research objectives are to (1) analyze Unesa lecturer research based on the distribution of faculties/departments/study programs; (2) analyzing trends in the research focus of Unesa lecturers; (3) analyzing the achievement of Unesa lecturer research outcomes compared with the target research outcomes; and (4) analyzing the profile of the service to the Unesa lecturer community based on the distribution of faculties/departments/study programs. The reference used in analyzing is from 2015-2019. The development model used is the Waterfall model with a linear development system. The research subject used was the procedure of developing Sistem Informasi Riset dan Pengabdian Kepada Masyarakat (SIRIP) in Higher Education. Data analysis techniques were carried out in three stages, namely pre-development, development, and post-development. Based on the results and discussion, the conclusions in this study are as follows. The results of the trial of Sistem Informasi Riset dan Pengabdian Kepada Masyarakat (SIRIP) using the black box testing method in accordance with 18 functional requirements of the system can run successfully. The profile of research in Unesa from 2015-2019 experienced a significant increase and decrease (fluctuation). The number of research titles funded from 2015-2019 was as many as 250 titles, 585 titles, 700 titles, 480 titles, and 447 titles. Meanwhile, the number of community service titles funded from 2015-2019 was 46 titles, 51 titles, 29 titles, 22 titles, and 338 titles, respectively.
Energy Management Methodology for Sustainable Water Development and Servicing, Considering the POET Based Concept
Authors: Ngancha P B , Kusakana K , Markus E D 
Published: July 2020

Abstract
This paper aims at analysing the energy management activities for commercial bulk water development and servicing in South Africa. The energy efficiency, in terms of performance, operation, equipment and technology (POET), is reviewed. The sustainability of a general energy management program is discussed within this POET framework. As an application of this discussion to the commercial bulk water development scenario, the POET efficiency of an energy system is a measure of energy efficiency, which is determined by external but deterministic system indicators, such as production period, energy sources, environmental impact and technical indicators, amongst others. The case study concludes that the POET, based framework does not only cover all major energy management activities, but further identifies energy efficiency improvement opportunities.
IoT Water Monitor Implementation Strategy
Authors: Gericke G A , Kuriakose R B 
Published: July 2020

Abstract
Water scarcity is a serious threat that is directly impacting the lives of over four billion people globally every month. While phenomenon’s like global climate change and pattern droughts contribute to this challenge, they are beyond human control to an extent. However, the challenge of water wastage due to water leaks is one that can and should be controlled. Majority of water leaks are only reported within 4-8 hours of their occurrence and take even longer to be fixed. This paper proposes an implementation strategy for monitoring water leakages in real time by connecting IoT enabled controllers onto the water main lines and automatically/remotely control the water main lines to limit the amount of water wastage. The key results of the study show that with the proposed system, water leaks can be detected and reported within an hour of their occurrence and with timeous intervention can prevent water loss of up to 50000 liters.
The greenhouse gas emissions, water consumption, and heat emissions of global steam-electric power production: a generating unit level analysis and database
Authors: Raptis C E , Oberschelp C , Pfister S 
Published: July 2020

AbstractSteam-electric power dominates global electricity production. Mitigating its environmental burdens relies on quantifying them globally, on a high resolution. Here, with an unprecedented combination of detail and coverage, the Rankine cycle was individually modelled for >21 000 geocoded steam-electric generating units globally. Accounting for different cooling systems and fuels enabled the calculation of three major environmental stressors on a generating unit level. Geographical, chronological, and technological patterns are examined, as are trade-offs and improvement scenarios. Greenhouse gases (GHG) emissions from young (>2000) Chinese coal-fuelled generating units are equal to the sum of GHG emissions from all steam-electric power plants of all ages in the U.S. and Europe, and occupy 5% of all GHG emissions from the entire global economy. Twenty-four per cent of freshwater consumed from steam-electric power originates from nuclear power units from the 1970s/1980s, mainly in the U.S. and Europe. One per cent of steam-electric generating units is responsible for 50% of global heat emissions to freshwater. The median carbon intensity of Indian coal-fired units (≥50 MW) is 7%–16% higher than that in any other region globally. As concerns GHGs, technology-related efficiency differences (Rankine cycle, cooling system) play a small role compared to the fuel, which dominates the carbon intensity (GHGs/GJ el.). With the highest shares of cogeneration, 1 GJ electricity from tower-cooled coal units in Russia consumes on average 8%–49% less freshwater compared to respective units globally. There is a small margin for improvement based on alternative steam-electric technologies: retiring inefficient units and replacing their demand by ramping up more efficient ones with the same fuel, within the same country results in, respectively, ∼1%, 6%, and 11% fewer GHG emissions, freshwater consumption, and heat emissions globally. The full environmental benefits of completely retiring old units (<1970) consist of 9% fewer GHG emissions, 7% less freshwater consumed, and 18% fewer thermal emissions globally.
Effect of WWTP size on grey water footprint—Czech Republic case study
Authors: Ansorge Libor , Stejskalová Lada , Dlabal Jiří 
Published: July 2020

Abstract
The number of wastewater treatment plants (WWTPs) in the Czech Republic is increasing. Wastewater, which was previously disposed of in other ways (e.g. septic tanks, cesspits etc), is now entering the surface water (after treatment at a WWTP). Billions of Czech crowns have been invested in the construction of new WWTPs or reconstruction and intensification of existing ones. This money had been invested to meet discharge standards for individual pollutants. However, the overall level of pollution associated with wastewater discharges has not been assessed. The indicator of grey water footprint was used to assess whether there was an increase in pollution load discharged from WWTPs between 2002 and 2018. Discharged pollution data from 4115 industrial and municipal WWTPs were analysed. The analysis of such a large data set has not been carried out yet and brings new knowledge concerning the effect of WWTP size on the grey water footprint. Overall, the total value of the grey water footprint (and thus of the discharged pollution level) decreased in the monitored period. Grey water footprint caused by the largest WWTPs decreased, while the grey water footprint of small WWTPs increased, due to the increase in their number. The decisive pollutants that determine the value of the grey water footprint are total phosphorus and ammonium nitrogen. Measures targeting these two main pollutants can significantly reduce the overall level of pollution load discharged from WWTPs.
Surface erosion behaviour over NiCrBSi-Al2O3 composite coatings
Authors: Senapati Pragyan , Sutar Harekrushna 
Published: July 2020

Abstract
For hydro turbine components High Velocity Oxy Fuel (HVOF) thermal spraying process was adopted for three different types of coatings i.e NiCrBSi-5%Al2O3 (N5A), NiCrBSi-10%Al2O3 (N10A) and NiCrBSi-15%Al2O3 (N15A) on Grade 420 Stainless steel, the coatings being characterized by Scanning Electron Microscope (SEM), x-ray Diffraction (XRD) and optical microscope. With measurements of surface roughness, thickness, micro hardness and porosity of the coatings, the erosion tests were conducted in a slurry-jet erosion tester at 30°, 60° and 90 ° impingement angles, jet velocity of 20 m s−1 and erodent size of 200 μm. The optical microscopy images of the coated samples exhibited lamella structure of the coatings. The N15A coating exhibits highest micro hardness value of 715 ± 31 HV0.3 followed by N10A (557 ± 22 HV0.3) and N5A (407 ± 15 HV0.3). The grade 420ss shows the lowest micro hardness value (272 ± 5 HV0.3). The surface morphology of the eroded samples was studied using SEM. The mechanisms involved in erosion of all the coated surfaces are removal of splats, lip formation, ploughing action and micro cutting whereas of bare steel, ploughing action, micro cutting and lip formation along with appearance of pores and craters. It was found that amongst the three coatings NiCrBSi-15%Al2O3 exhibited the lowest erosion and all the coatings offered better wear resistance than the uncoated steel.
AmpliCI: a high-resolution model-based approach for denoising Illumina amplicon data
Authors: Peng Xiyu , Dorman Karin S 
Published: July 2020

Abstract

Motivation
Next-generation amplicon sequencing is a powerful tool for investigating microbial communities. A main challenge is to distinguish true biological variants from errors caused by amplification and sequencing. In traditional analyses, such errors are eliminated by clustering reads within a sequence similarity threshold, usually 97%, and constructing operational taxonomic units, but the arbitrary threshold leads to low resolution and high false-positive rates. Recently developed ‘denoising’ methods have proven able to resolve single-nucleotide amplicon variants, but they still miss low-frequency sequences, especially those near more frequent sequences, because they ignore the sequencing quality information.

Results
We introduce AmpliCI, a reference-free, model-based method for rapidly resolving the number, abundance and identity of error-free sequences in massive Illumina amplicon datasets. AmpliCI considers the quality information and allows the data, not an arbitrary threshold or an external database, to drive conclusions. AmpliCI estimates a finite mixture model, using a greedy strategy to gradually select error-free sequences and approximately maximize the likelihood. AmpliCI has better performance than three popular denoising methods, with acceptable computation time and memory usage.

Availability and implementation
Source code is available at https://github.com/DormanLab/AmpliCI.

Supplementary information
Supplementary material are available at Bioinformatics online.