bluuebunny/crossref_metadata_2025_split huggingface dataset:
Recycling Polymer Blend made from Post-used Styrofoam and Polypropylene for Fuse Deposition Modelling
Authors: William L J W , Koay S C , Chan M Y , Pang M M , Ong T K , Tshai K Y 
Published: December 2021

Abstract
Fuse deposition modelling (FDM) has become a revolutionary manufacturing technology as it offers numerous advantages, including freedom of fabrication, mass customisation, fast prototyping, and cost-effectiveness. Thermoplastic material is commonly used as feedstock for FDM process. The current state of material development, the recycled plastic material also can be used as printing material for FDM machine. Expanded polystyrene (EPS) has been extensively used as packaging materials for many industries but rarely be recycled, as its relatively large volume with minimal weight is unconducive for transportation. This research aimed to utilize EPS waste and turn it into FDM feedstock. This research also aims to enhance the properties of recycled polystyrene (rPS) made from EPS waste by blending it with polypropylene (PP). Different ratios of rPS/PP blends were prepared and extruded into FDM filament using filament extruder. The formulated filaments were printed into specimen using FDM machine. This research found the filament made from rPS/PP blends can be printed into specimen with good printing quality if the nozzle temperature controlled at 240° C with 120 % extrusion rate. With this printing parameter, the specimen printed with rPS/PP blend filament exhibit the greatest adhesion between the deposited layers without any visible voids or gaps. Besides, the printed specimen with rPS/PP blends possess lower tensile strength, but higher tensile modulus as compared to the printed specimen with neat rPS. The addition of more PP decreased both tensile strength and modulus of rPS/PP blends. On the other hand, the rPS/PP blends have higher thermal stability as the PP content increased. Overall, the rPS/PP blends filament shows a great potential as a feedstock material for FDM fabrication.
Reference Current Generation for Active Power Filtering in Single-Phase Power System
Authors: Chew Siew Ting , Hoon Yap , Ahmad Hafisoh 
Published: December 2021

Abstract
The study presents a new proposed reference current generation algorithm based on the synchronous reference frame (SRF) conventional algorithm in single-phase power system for an active power filtering. Shunt active power filter (SAPF) is often used as it can mitigate harmonic currents in the AC networks due to its superiority in dynamic-state conditions. The reference current generation algorithm is the most important control algorithms to control SAPF as it has the simplest implementation features. A proposed STF-based fundamental component identifier (STF-FCI) algorithm is implemented for the major improvements such as the removal of the unnecessary cosine function to reduce complexity of algorithm, employment of self-tuning filter (STF) to extract accurate fundamental component and to generate a sinusoidal reference current. The purpose of developing STF-FCI algorithm is to replace low pass filter (LPF) with a mean as it can generate a fast and accurate fundamental reference current to operate the SAPF in reducing the harmonics content of the power system and provide a fast response time in the dynamic-state conditions. This paper is presented under both steady-state which is capacitive (RC) load or inductive (RL) load as well as dynamic condition where capacitive load change to inductive load. The performance of steady-state condition will be evaluated in terms of THD values, ripple factor, power factor and phase difference. Under dynamic-state condition, the dynamic speed will be evaluated to capture the speed of the amplitude change in nonlinear load in a period of time. MATLAB-Simulink is used to design and evaluate the proposed STF-FCI algorithm with mean algorithm and LPF algorithm for comparison purpose. The simulation results had shown the major improvement when THD values, ripple factor, power factor and phase difference are reduced. The response time of the changing load is shorter by using mean algorithm compare to LPF algorithm. The simulation results obtained proved success when the proposed STF-FCI algorithm using mean algorithm are much better than LPF algorithm in steady-state and dynamic conditions under two voltage conditions i.e. ideal and distorted voltage.
The application of image processing for monitoring student’s attention level during online class
Authors: Ong J W , Chew W J , Phang S K 
Published: December 2021

Abstract
With the COVID-19 pandemic still causing the world to be quarantined in their house to prevent the spread of the virus, this means online classes are still the main method of conducting classes. This project aims to help lecturers monitor the students during class as they are having problems checking whether the students are paying attention or not. This project uses the student’s facial features to determine their attention level using two different coding algorithm Viola-Jones and Sobel edge. These two algorithms help to determine what kind of facial expression that the students are making. The Viola-Jones algorithm detects and captures the student’s facial features such as eyes and mouth while the Sobel edge algorithm detects the edges of the facial features to determine whether the eyes and mouth are open or closed. With the data collected it will run through the database to determine the student’s attention level and inform the lecturer.
Analysis of physics learning media needs based on mobile augmented reality (AR) on global warming for high school students
Authors: Nor M. , Halim Lilia 
Published: December 2021

AbstractThe rapid progress of the times requires an educational approach to be innovative and adaptive to changes in technology and information. Mobile Augmented Reality (MAR) is a system that incorporates technology in education. This method facilitates learning to be interesting, effective, and easily accessible to everyone. This survey research was an initial step in developing Augmented Reality based Modules for high school students on global warming. The importance of this research is that educational media using Augmented Reality is relatively new in the field of educational media. Analysis of learning problems and analysis of students are the two indicators used in the analysis of this need. Based on this research survey, it was found that augmented reality based educational media is viewed as important and necessary as learning materials in schools especially for students of high ability. The next phase is the development of MAR-based learning media that meets these requirements.
Identifying students’ difficulty in the basic of thermodynamics
Authors: Sutarja M C , Wulandari A Y R 
Published: December 2021

Abstract
Conceptual understanding is one of the main topics in physics educational research. It is important as the basic of other ability in education, such as argumentation, making scientific explanation and problem solving. This survey study aims to identify students’ difficulty to understand the basic of thermodynamics. There are 128 first year undergraduate students as the participants of the study. The data collection method is test. Result of the study shows that isobaric process of ideal gas and mechanical equilibrium state concepts are the most difficult concepts. Some difficulties are found in understanding the basic of thermodynamics: (1) because of the presence of higher cognitive load while solving conceptual problems, (2) when the question demands other ability, especially mathematical ability, to solve the conceptual problem, (3) because of students’ disability to integrate the knowledge. This study could be used to develop learning instruction or media in basic physics or introduction of thermodynamics course.
Development of Thermal Energy Conversion Devices into Electrical Energy as Physics Learning Teaching Aids
Authors: Umam D K , Saehana S , Kade A , Yunanli  
Published: December 2021

Abstract
This research aimed to produce a device for converting heat energy into electrical energy as a teaching aid for physics. This research process is development research, which refers to the Research and Development (R&D) model. The instrument used was a questionnaire with a five Likert scale, which addressed media experts, material experts, physics teachers in SMA Negeri 2 Sigi, and class XII MIA SMA Negeri 2 Sigi students. The product quality data obtained were analyzed using descriptive analysis. Based on the analysis of the media expert’s assessment, the quality of the product obtained a percentage value of 87.69% with the interpretation of “Very Good”. Based on the analysis of the assessment by material experts, the quality of the product obtained a percentage value of 84.44% with the interpretation “Very Good”. For the results of the physics teacher’s response, a percentage value of 86.00% was obtained with the interpretation “Strongly Agree”. For the results of the responses of class XII MIA students in the limited test, a percentage value of 83.56% was obtained with the interpretation “Strongly Agree”. The test results and questionnaire analysis showed that the heat energy conversion device developed into electrical energy was feasible to use.
What we can learn from 2018 liquefaction in Central Sulawesi: Stories from the survivors
Authors: Wahyono U , Astuti N M Wiwik 
Published: December 2021

Abstract
This paper provides the stories of the liquefaction survivors about their experiences during and after the disaster. It is a phenomenological study that used the semi-structured interview to obtain the data. The data were acquired from 30 participants. There are some important points that can be summarised from the stories of the survivors. During the disaster, local people inclined to underestimate the quake at the beginning of the shaking. It could indicate the level of their risk perception and awareness on disaster. In addition, a unique finding from this study was that the survivors had conducted the initial intervention priority as basic resources for survival such as shelter and information of the victims’ identity. Also, regarding the post-disaster data, the results indicated that the survivors experienced the symptoms of trauma due to the disaster. It indicates that the psychological aspect of the survivors was neglected during the recovery process. On that regard, long-term traumatic recovery activities should be put into accounted during the recovery processes for all the victims of a disaster regardless of their ages and genders. Another implication of this study is the opportunity to use these stories into learning activities, both in learning about science or disaster mitigation.
Design and Simulation of Electro-hydraulic Control Valve Based on AMESim
Authors: Li Bin , Li Guyang , Wu Wangyang , Zhang Xue , Guo Song , Wang Nei , Mao Xuyao 
Published: December 2021

Abstract
In this paper, the electro-hydraulic control valve commonly used in ships is taken as the research object, the working principle of the valve is introduced, the model of the valve is established by AMESim software, the model parameters are set and the simulation analysis is carried out. By changing the relevant parameters of the valve, the response speed of the valve can be improved. The simulation results show that the pressure area of load sensitive cavity and the diameter of damping hole have obvious influence on the response speed of valve.
Study on Optimization of Operating Parameters of Contact Mechanical Seal Based on Orthogonal Test
Authors: Dai LuLing 
Published: December 2021

Abstract
The working condition parameters of common contact mechanical seals are experimentally studied by orthogonal experimental design. The effects of working condition parameters on mechanical seal performance are compared by variance and range analysis, and the optimal sealing working condition is put forward. The results show that the spring specific pressure has a great influence on the leakage of mechanical seal, and the leakage decreases rapidly with the increase of spring specific pressure; With the increase of spring specific pressure, the friction power consumption increases. According to the test results, considering the requirements of mechanical seal performance and service life, the optimal spring specific pressure is 0.028 MPa under the condition of medium pressure ps
=0.60 MPa and motor speed n =2960 r/min. At this time, the leakage is 6.120 ml/h and the friction power consumption is 0.648 kW.
Simulation analysis and experiment of sampling process of wheel brush sampler based on discrete element method
Authors: Wei Qiming , Liu Ran , Zhang Hua , Wu Xingyuan , Luo Haitao 
Published: December 2021

Abstract
In order to study the brush sweep sampling process through simulation analysis, the structure of the asteroid sampler is simplified on the basis of retaining the wheel brush. Soybean particles are selected as the verification sampling particles, and the physical and contact parameters of calibrated soybean particles are applied to the discrete element simulation software EDEM and the relationship between the sampling wheel brush speed and torque is analysed. At the same time, a set of wheel brush asteroid sampler ground torque test system is built to verify the accuracy of the discrete element simulation results. The results show that the driving torque of the sampling wheel brush is mutational in the process of sampling, and the faster the rotation speed of the sampling wheel brush, the more the mass of the collected particles, and the greater the driving torque required for the sampling wheel brush. This research provides a method basis for the structure selection and parameter optimization design of the asteroid sampler.
Cluster analysis of time series K-Means line loss based on DWT distance
Authors: Song Liming , Chen Zhimin , Meng XinXin , Kang Shuai 
Published: December 2021

Abstract
This paper constructs an indicator system composed of inherent attributes and time characteristics of the line based on the line loss, and proposes a K-Means line loss cluster analysis model based on this indicator system. The line is classified according to the clustering results. The result is 314.51 on the CH index (Calinski Harabasz Index), 0.19 on the Silhouette Cofficient (Silhouette Cofficient), and a running time of 0.508s. Compared with the traditional algorithm, it is greatly improved. The field of line loss analysis has guiding significance.
Data Security Protection Mechanism of Video and Image Feature Modeling Based on Domestic Crypto Algorithm
Authors: Tu Yueqiang 
Published: December 2021

Abstract
Video and image monitoring is increasingly appearing in our home, travel and other aspects. Through video and image analysis and comparison of video and image monitoring data, it can provide strong analysis support capabilities for social security prevention and control, traffic command, safety production and so on. Video and image feature modeling is a necessary prerequisite for video and image analysis and comparison. Video and image feature modeling forms video and image feature data. Video and image feature data reflects the most essential information of various elements such as people, vehicles and objects. However, video and image data is easy to be damaged, changed and leaked in the process of collection, aggregation, analysis, modeling and storage, Facing data security risks. This paper proposes a set of video and image feature modeling data security protection mechanism based on domestic algorithm to realize the whole process encryption protection of data acquisition, transmission and storage.
A Graph Neural Network gas concentration prediction model based on Spatio-Temporal data
Authors: Zhang Zhaozhao , Ye Yuhao , Dong Lihong 
Published: December 2021

Abstract
For the problem of low prediction accuracy caused by traditional neural network gas concentration prediction models which did not consider temporal and spatial characteristics of gas data, this paper proposed a Spatial-Temporal graph neural network gas prediction model based on Spatial-Temporal data. Its essence was the integration of graph convolutional network and WaveNet network. In spatial dimension, graph convolutional network was used to aggregate the information of neighbor nodes, and adaptively adjusts the spatial association strength of each node according to the attention mechanism to captured the spatial characteristics of gas data. In temporal dimension, WaveNet network model was introduced, Dilated Causal Convolution was used to extract the temporal characteristics of gas data on temporal dimensions. According to the distance between gas sensors in the mine, the gas data spatial structure was constructed by Thresholded Gaussian kernel function. Experiment with the measured gas temporal and spatial data, using Mean Absolute Error (MAE) as an indicator of predictive accuracy. The experimental results show that the prediction model mentioned in this paper is significantly improved compared with the prediction accuracy of other predictive models.
Advanced NIR ratiometric probes for intravital biomedical imaging
Authors: Huang Haoying , Qiu Ruijuan , Yang Hongchao , Ren Feng , Wu Feng , Zhang Yejun , Zhang Hong , Li Chunyan 
Published: December 2021

Abstract
Near-infrared (NIR) fluorescence imaging technology (NIR-I region, 650–950 nm and NIR-II region, 1000–1700 nm), with deeper tissue penetration and less disturbance from auto-fluorescence than that in visible region (400–650 nm), is playing a more and more extensive role in the field of biomedical imaging. With the development of precise medicine, intelligent NIR fluorescent probes have been meticulously designed to provide more sensitive, specific and accurate feedback on detection. Especially, recently developed ratiometric fluorescent probes have been devoted to quantify physiological and pathological parameters with a combination of responsive fluorescence changes and self-calibration. Herein, we systemically introduced the construction strategies of NIR ratiometric fluorescent probes and their applications in biological imaging in vivo, such as molecular detection, pH and temperature measurement, drug delivery monitoring and treatment evaluation. We further summarized possible optimization on the design of ratiometric probes for quantitative analysis with NIR fluorescence, and prospected the broader optical applications of ratiometric probes in life science and clinical translation.
Landscape resource management for sustainable crop intensification
Authors: Anantha K H , Garg Kaushal K , Singh Ramesh , Akuraju Venkataradha , Dev Inder , Petrie Cameron A , Whitbread Anthony M , Dixit Sreenath 
Published: December 2021

Abstract
Crop intensification is required to meet the food demands of an increasing population. This paper presents data from three paired scaling-up initiatives to compare the benefits of landscape-based interventions over individual plot-level interventions using evidence generated in the Indian semi-arid tropics. A range of soil and water conservation interventions were implemented in a decentralized manner following the landscape-based approach. The plot-level approach focused only on balanced fertilizer application and improved crop cultivars while the landscape-based interventions primarily addressed moisture availability, which was the key to reducing risks of crop failure besides aiding productivity gain and enhanced land and water-use efficiency. These interventions have additionally harvested 50–150 mm of surface runoff and facilitated groundwater recharge in 550–800 mm rainfall zones. Individual plot-level interventions also improved the crop yield significantly over the control plots. However, crop intensification was not achieved due to limited moisture availability. Landscape-based interventions produced 100%–300% higher crop production per year, greater income generation (>100%), and improved water productivity. Landscape-based interventions were also found to be beneficial in terms of reducing soil loss by 75%–90% and improving base flow availability additionally by 20–75 d in a year compared to untreated watersheds. With increased moisture availability, fallow lands in respective watersheds have been utilized for cultivation, thereby enhancing crop intensification. The findings of the study provide critical insights into the design of approaches suitable for scaling-up projects in order to both create impact and target the United Nations Sustainable Development Goals.
The cyber-consciousness of environmental assessment: how environmental assessments evaluate the impacts of smart, connected, and digital technology
Authors: Mulrow John , Gali Manasi , Grubert Emily 
Published: December 2021

Abstract
Digitally enabled technologies are increasingly cyber-physical systems (CPSs). They are networked in nature and made up of geographically dispersed components that manage and control data received from humans, equipment, and the environment. Researchers evaluating such technologies are thus challenged to include CPS subsystems and dynamics that might not be obvious components of a product system. Although analysts might assume CPS have negligible or purely beneficial impact on environmental outcomes, such assumptions require justification. As the physical environmental impacts of digital processes (e.g. cryptocurrency mining) gain attention, the need for explicit attention to CPS in environmental assessment becomes more salient. This review investigates how the peer-reviewed environmental assessment literature treats environmental implications of CPS, with a focus on journal articles published in English between 2010 and 2020. We identify nine CPS subsystems and dynamics addressed in this literature: energy system, digital equipment, non-digital equipment, automation and management, network infrastructure, direct costs, social and health effects, feedbacks, and cybersecurity. Based on these categories, we develop a ‘cyber-consciousness score’ reflecting the extent to which the 115 studies that met our evaluation criteria address CPS, then summarize analytical methods and modeling techniques drawn from reviewed literature to facilitate routine inclusion of CPS in environmental assessment. We find that, given challenges in establishing system boundaries, limited standardization of how to evaluate CPS dynamics, and failure to recognize the role of CPS in a product system under evaluation, the extant environmental assessment literature in peer-reviewed journals largely ignores CPS subsystems and dynamics when evaluating digital or digitally-enabled technologies.
Native BK virus nephropathy in lung transplant: a case report and literature review
Authors: Albasha Waseem , Vahdani Golnaz , Ashoka Ankita , Bracamonte Erika , Yau Amy A 
Published: December 2021

ABSTRACT
Classically described in renal allografts, BK virus nephropathy is increasingly recognized in native kidneys of other non-renal solid organ transplants. We discuss a 68-year-old woman with a history of bilateral lung transplant referred for worsening renal function, confirmed to have BK virus nephropathy by biopsy with a serum BK virus polymerase chain reaction of over 59 million copies/mL. She was managed with a reduction in immunosuppression and intravenous cidofovir with no improvement in her clinical parameters. The seven prior reported cases of polyoma virus nephropathy in lung transplant recipients are reviewed, and the challenges of screening and management are discussed.