bluuebunny/crossref_metadata_2025 huggingface dataset:
SURFACE DEFORMATION MONITORING AND DRIVING FORCE ANALYSIS IN THE YELLOW RIVER DELTA BASED ON PS-INSAR TECHNOLOGY
Authors: Zhang Q. , Zhao Z. , Jia L. , Huo W. , Gao R.
Published: October 2022

Abstract. Aiming at the land subsidence in the Yellow River Delta region, based on the Sentinel-1A data of 52 scenes from 2020 to February 2022, Persistent Scatterer Interferometric Synthetic Aperture Radar (PS-InSAR) were adopted to extract the surface deformation information of the Yellow River Delta region. Firstly, the deformation characteristics of typical subsidence feature points are analyzed, and then the correlation between groundwater, precipitation and land subsidence are analyzed. The result show that the settlement area distribution of the Yellow River Delta is not uniform, mainly distributed in underground brine mining area and oil extraction area, the maximum settlement center is located in Yongan Town, the settlement amount reaches −302.7 mm, the main reason of the settlement is excessive exploitation of underground brine salt. By analyzing the correlation between groundwater, precipitation and land subsidence in the Yellow River Delta, it can be seen that the effect of groundwater content change on land subsidence was the most serious, and the correlation coefficient is 0.875. In general, the subsidence of the Yellow River Delta is mainly caused by the over-exploitation of underground fluids such as fresh water, brine and oil without timely compensation.
RISK ASSESSMENT OF HIGH VOLTAGE POWER LINES CROSSING FOREST AREAS – A CASE STUDY OF WILDFIRES
Authors: Zhang R. , Zhong R. , Pang Y. , Yang B. , Shu H.
Published: October 2022

Abstract. This study aims to introduce new methods for assessing risk of wildfires around power transmission line corridors (PTCs) using multiple sourced active monitoring data. The proposed approach starts from fire analysis using interpretative structural modeling (ISM) from historical data of fire-caused transmission line (TL) fault, which emphasizes on the fire regimes and the fire factors. The ISM illustrates the sequence and relationships among fire factors. The main influencing factors are then ranking using analytic hierarchy process (AHP) to distinguish each relative importance. FRP, a high-resolution fire risk index conducting fire risk around PTCs, was constructed considering these factors as a series of assessment criterion. Variable meteorological-type factors such as maximum temperature and minimum relative humidity, less variable basic elements such as surface conditions, and human activity elements are all weighed and considered in FRP. The risk of this line can be obtained by calculating the collected monitoring data from TLC. Moreover, the safety risk level can be analyzed based on this assessment and the risk map of the power corridor can be used to help the power department to improve the maintenance plan of the power corridor.
SUSCEPTIBILITY ASSESSMENT OF RAINFALL-INDUCED DEBRIS FLOW IN THE LOWER REACHES OF YAJIANG RIVER BASED ON GIS AND CF COUPLING MODEL
Authors: Huang Y. , Guo Y. , Su L. , Lin Q.
Published: October 2022

Abstract. The lower reaches of the Yajiang River are high in the east and low in the west, with abundant rainfall, and contain a large amount of hydropower resources that have not been exploited and utilized. Nonetheless, due to the unique geographical environment in southeast Tibet, rainfall debris flow is one of the frequent geological disasters in this area. In this research, 42 debris flow points were collected, ten disaster-causing factors were selected, and satellite elevation data were analyzed to evaluate the disaster susceptibility of the study area. The disaster-causing factors information is extracted from Arcgis. The certainty factor model (CF) was used to calculate the coefficient of certainty of 10 factors including fault distance, elevation, normalized difference vegetation index (NDVI), average annual rainfall, profile curvature, relief, silt content, TWI, SPI, and slope aspect. The Analytic Hierarchy Process (AHP), Binary Logistic Regression (LR), Random Forest (RF) and CF model were used to analyze and predict the possibility of debris flow occurrence. The results show that the accuracy of the CF-LR model is the highest under the verification of the ROC curve. In the prediction model, the high-risk areas of debris flow are mainly concentrated in the first half of the lower reaches of the Yajiang River and distributed along both sides of the river bank. After bringing the data of different annual rainfall into the model, it is found that the saturation critical value of debris flow water source in the study area is within the range of 600–700mm annual rainfall.
3D SCENE RECONSTRUCTION AND PATH PLANNING METHOD FOR UAV IN GNSS-DENIED ENVIRONMENT
Authors: Jin Q. , Zhao P. , Hu Q. , Duan X. , Ai M.
Published: October 2022

Abstract. Today, natural disasters have a huge impact all over the world, while GNSS plays an important role in disaster relief and rescue. However, when the ground surface is severely damaged and covered, satellite positioning means are denied. In addition, disaster site conditions are often very complex and may require unmanned robots such as UAVs for pre-surveying. To address the raised problem, we reconstructed the 3D scene by laser SLAM; improved PRM path planning method for better computational efficiency while solving feasible path results; and realized UAV autonomous flight along the planned path in GNSS-denied environment. The experiments prove that the reconstructed scene map provides a feasible means for UAV autonomous navigation in GNSS-denied environment, and the proposed path planning method has a significant improvement in computational efficiency.
EPIDEMIOLOGICAL-SURVEY-BASED STUDY FOR UNDERSTANDING DAILY MOBILITY OF ELDERLY IN SOUTHEAST CHINA
Authors: Dai Z. , Zhang W. , Fu C. , Zhao F.
Published: October 2022

Abstract. China's aging population has brought both opportunities and challenges to the society and economy. Promoting healthy aging is crucial to sustainable social and economic development. Learning the daily mobility pattern and health status of the elderly can provide references for the formulation and implementation of policies such as urban planning and social welfare. We derived key mobility indicators from the epidemiological survey data and then applied exploratory factor analysis to identify latent factors that can significantly affect mobility of the elderly in Southeast China. The study found that: quantity of out of home activities, extent of life space and stability of life space are three important factors that affect elder’s mobility; gender gap is small in elders’ mobility while the urban-rural differences in extent of life space and stability of life space are significant. The maximum distance from home for the rural elderly is significantly higher than urban elderly, while rural elder’s extent of activities is narrower and longer, and the repetition is low. There were significant differences in both the quantity of out of home activities and the extent of living space between elderly in China and Switzerland, and the activities of the elderly in China are more consistent, while the mobility pattern of the elderly in Switzerland are extremely divergent. Epidemiological survey data can be used as a data source for the elder’s daily mobility studying, and the results of this paper provide references for the policy formulation of policies to cope with aging, such as building an elderly-friendly community and caring for the physical and mental health of the elderly.
CANOPY STRUCTURAL EFFECTS ON BIDIRECTIONAL REFLECTANCE SIMULATED BY THE LESS MODEL: A CASE STUDY OF PICEA CRASSIFOLIA FORESTS
Authors: Wu Q. , Yang S. , Jiang J.
Published: October 2022

Abstract. Surface albedo is a dominant factor affecting the earth energy balance. Bidirectional reflectance distribution function (BRDF) describes the anisotropic surface reflection of solar radiation. Bidirectional effect is especially noticeable in the forest canopies with three-dimensional canopy structure. Thus, it is challenging to evaluate the canopy structural effects on BRDF using traditional radiative transfer modelling methods, where leaf in canopies is generally assumed to be homogeneous. LESS, a ray-tracing-based three-dimensional (3D) radiative transfer model can effectively simulate bidirectional reflectance factor while fully considering multi-component spectral and structural characteristics of vegetation. In this study, we applied the LESS model to evaluate the impacts of changes in leaf area index (LAI) on canopy reflectance in a Picea crassifolia forest. First, canopy structural parameters obtained from forest inventory were used to construct forest scenes and drive the LESS model. Then, we validated the simulation accuracy of the LESS model against BRDF calculated from MODIS BRDF parameter product using kernel-driven Ross-Li bi-directional reflectance function. Finally, we constructed forest scenes with different LAI to investigate the canopy structural effects on BRDF. We found that the BRDF simulated by the LESS model is in good accordance with the MODIS BRDF data in the red (R2 = 0.97, RMSE = 0.03) and NIR (R2 = 0.94, RMSE = 0.05) bands. The simulated canopy reflectance in the red band displayed ‘dome’ shape and decreased with increasing LAI. In contrast, canopy reflectance in the NIR band displayed ‘bowl’ shape and increased with increasing LAI. Our study highlighted the sensitivity of canopy BRDF to changes in canopy structure and have implications for retrieving LAI from BRDF data.
LONG-TERM ECOLOGICAL ENVIRONMENT CHANGE MONITORING IN SCALE OF CITY ALONG CHINA-EUROPE RAILWAY EXPRESS WITH A REMOTE SENSING-BASED ECOLOGICAL INDEX (RSEI): A CASE STUDY IN WARSAW, POLAND
Authors: Yang M. , Guo X. , Jiang J.
Published: October 2022

Abstract. The China-Europe Railway Express (CER-Express) has developed rapidly since its opening, but little attention has been paid to the long-term ecological environment changes along its route, especially in scale of city. This paper studies the long-term changes of cities along the route before and after the opening of CER-Express. Based on the Google Earth Engine platform, we apply the RSEI model for the cities along the route before and after the opening of the CER-Express from 2010 to 2020. Taking Warsaw, Poland as an example, quantitative analysis is carried out regarding its ecological environment changes and the reasons for these changes are discussed. Experimental results show that the mean values of RSEI between 0.6 and 0.8 before the opening, but declined significantly after the opening, and changed steadily in the later stage. This preliminary research can provide theoretical basis for cities along the CER-Express, protect to the sustainable development of CER-Express and response to the call of Goal 15 of the Sustainable Development Goals (SDGs).
MULTI-USER COLLABORATIVE VIRTUAL EMERGENCY DRILL SYSTEM FOR URBAN ROAD EMERGENCIES
Authors: Gao X. , Zhang J. , Zou R. , Li J. , Cao Z.
Published: October 2022

Abstract. In order to comprehensively improve the coordination and emergency response ability of road emergency commanders and rescuers to various road emergencies, analyze the problems faced by road emergency personnel in rescue training, and propose a simulation drill method combining virtual reality visualization technology with emergency rescue training content to form an interactive drill system.This paper elaborates the key technologies, architecture system and functional design of the system in detail, introduces and implements a complete set of virtual emergency drill disposal process based on the case of landslides blocking urban roads in flood season. The Internet and virtual reality technology are applied to build road emergency scenes. The emergency drill personnel carry out remote interactive virtual collaborative emergency drills in the same virtual environment, so as to realize the repeated deduction drills of road emergencies, and design the emergency disposition of scientific assessment system for drill personnel to evaluate objectively the disposal process, It effectively improves the emergency response and rescue ability of emergency personnel, and solve the problems faced by the current road emergency practice drills, such as less times, high cost, single scene and subject, etc.
OPTIMAL LOCATION OF WASTEWATER TREATMENT PLANTS CONSIDERING MULTIPLE FACTORS: A CASE STUDY OF PHNOM PENH
Authors: Zhou Y. , Song Y. , Qin W. , Sun J.
Published: October 2022

Abstract. Urban wastewater treatment plants (WWTPs) as an important engineering facility for urban water pollution prevention and control, the appropriate location selection for the WWTPs is the most important stage in the process of wastewater treatment. Improper site selection can lead to degradation of the water environment. Phnom Penh is located in the delta between the Mekong River and Tonle Sap River, with dense population, and most residents are religious. There are no sufficient and proper WWTPs available in many areas resulting in the environmental degradation and human health issues, so it is used as the study area. In the article, we proposed a new indicator system to select the location for WWTPs. The indicator system is established from RS/GIS data, which integrates social-cultural and multiple others factors, and more comprehensively analyzes the spatial distribution of suitable and demand areas for WWTPs. Finally, the minimize facilities and maximize coverage model are further used for spatial location selection of WWTPs, which can supply scientific plan and technological support for location selection of the WWTPs.
APPLICATION OF DIGITAL TWINS IN HIGH PRECISION GEOLOGICAL HAZARD SURVEY AND PREVENTION IN BEIJING
Authors: Peng B. , Xiao X. , Zhao B. , Li H.
Published: October 2022

Abstract. Beijing is located in the northwest corner of the North China Plain, with a total area of 16410 km2, of which mountainous area accounts for about 61.3 % of the total area. Due to the complex geological and geomorphological conditions, the development of fault structures, the spatial-temporal uneven distribution of rainfall and the influence of human engineering activities, there are many sudden geological hazards in Beijing, such as collapse, landslide, debris flow and mining collapse. As is known, Beijing is one of the capital cities with most developed sudden geological hazard in the world. With the continuous development of economy and tourism in mountainous and shallow mountain valleys and the further enhancement of human activities, the threat of sudden geological hazard to Beijing's social and economic development will continue to exist. This paper explores the application of digital twin technology in the survey and prevention of geological hazard in Beijing, mainly using tilt aerial photogrammetry, 3D model production, remote sensing interpretation, ground analysis, database management and other methods to carry out high precision survey, mapping and investigation research. Furthermore, we analyze the relevant features of geological hazard hidden danger points, deeply study their dangers, and establish a two-dimensional and three-dimensional information management system for geological hazard in Beijing's mountainous areas. It is proved that the information management system can effectively improve the management and prevention of geological hazard.
A NOVEL QUADRATIC ERROR METRIC MESH SIMPLIFICATION ALGORITHM FOR 3D BUILDING MODELS BASED ON ‘LOCAL-VERTEX’ TEXTURE FEATURES
Authors: Zhao T. , Jiang J. , Guo X.
Published: October 2022

Abstract. 3D building model is an important part of 3D GIS. However, with the rapid development of data acquisition technology, the data volume of the 3D building model has increased dramatically. Levels of detail (LOD) technology determines the resource allocation for object rendering based on the position (Screen Size) and importance of the nodes of the model in the display environment, reducing the model’s volume and thus obtaining efficient rendering computations. To ensure the smooth rendering and efficient loading of 3D building models, it is essential to simplify the 3D building models to generate LOD. By taking the texture discontinuity and topological complexity into account, this paper proposes a quadratic error metric mesh simplification algorithm based on "local-vertex" texture features for 3D building models simplification. Using the texture features of the model texture map and the vertex curvature at local vertices, we increase the edge collapse cost of the model in the rich texture areas. After each simplification operation, we use centre of gravity coordinate method to optimize the texture coordinates to preserve the model’s detailed features and topological relationships. A series of experimental comparisons with other state-of-the-art methods verify the effectiveness of the proposed method for simplifying 3D building models. The method in this paper helps to maintain the detailed features and topological relationships of 3D building models while reducing the volume of model and better generating LOD for application in 3D GIS.
URBAN DESIGN STRATEGIES FOR THE UPCYCLING OF URBAN INFRASTRUCTURE RESIDUAL POCKETS: 3D CITY MODELLING FROM OPEN DATA AND LOW-COST RAPID MAPPING TOOLS
Authors: Stendardo L. , Spera R. , Campi M. , Cera V. , di Luggo A.
Published: October 2022

Abstract. This paper deals with the 3D City Modelling specific procedure developed as a tool to support strategies for urban regeneration, within the framework of the B-ROAD research project.The B-ROAD research project, whose acronym stands for Below the Road, is developing urban design strategies for upcycling urban infrastructure residual pockets.The B-ROAD’s methodology is conceived as research by design as it is carried out by creating pilot scenarios, disclosing the latent and still unexpressed potential of these wasted areas and displaying their potential transformations, to turn them into precious resources for the contemporary city.The 3D City Modelling of the study area has proved to be essential and strategic yet often complex and critical as most of the spatial and architectural features of B-ROAD spaces, as well as their potential, cannot be detected nor represented through the traditional means of representation of urbanised land, as aerial survey-based representations, or GIS. Likewise, traditional, or even cutting-edge, survey techniques that can be used to acquire missing data are often costly and time-consuming, thus making it hardly impossible to achieve the purpose of extensive and deep knowledge of such a vast area. Thus, 3D City Modelling aimed at examining spaces and providing a final representation of pilot scenarios has been a crucial stage requiring a specific in-depth study.
Surface melt on the Shackleton Ice Shelf, East Antarctica (2003–2021)
Authors: Saunderson Dominic , Mackintosh Andrew , McCormack Felicity , Jones Richard Selwyn , Picard Ghislain
Published: October 2022

Abstract. Melt on the surface of Antarctic ice shelves can potentially lead to
their disintegration, accelerating the flow of grounded ice to the ocean
and raising global sea levels. However, the current understanding of the
processes driving surface melt is incomplete, increasing uncertainty in
predictions of ice shelf stability and thus of Antarctica's contribution
to sea-level rise. Previous studies of surface melt in Antarctica have
usually focused on either a process-level understanding of melt through
energy-balance investigations or used metrics such as the annual number
of melt days to quantify spatiotemporal variability in satellite
observations of surface melt. Here, we help bridge the gap between work
at these two scales. Using daily passive microwave observations from the
AMSR-E and AMSR-2 sensors and the machine learning approach of a
self-organising map, we identify nine representative spatial
distributions (“patterns”) of surface melt on the Shackleton Ice Shelf
in East Antarctica from 2002/03–2020/21. Combined with output from
the RACMO2.3p3 regional climate model and surface topography from the
REMA digital elevation model, our results point to a significant role
for surface air temperatures in controlling the interannual variability
in summer melt and also reveal the influence of localised controls on
melt. In particular, prolonged melt along the grounding line shows the
importance of katabatic winds and surface albedo. Our approach
highlights the necessity of understanding both local and large-scale
controls on surface melt and demonstrates that self-organising maps can
be used to investigate the variability in surface melt on Antarctic ice
shelves.
Predictive Analysis on Sensor Data Using Distributed Machine Learning
Authors: Shargunam S. , Rajakumar G.
Published: October 2022

The science of getting computers to act without being explicitly programmed is known as machine learning. Machine learning is comparable to data mining in terms of how it works. Both systems sift through data in order to find patterns. Machine learning, on the other hand, instead of extracting data for human comprehension as in data mining applications, uses that data to increase the program's own understanding. Data patterns are detected by machine learning programmes, which then alter Programme behaviours accordingly. This research is based on real-world data obtained from sensors in an oil and Gas Corporation that monitor drilling procedures and equipment. The sensor data is streamed in at a one-second period, resulting in 86400 rows of data per day. Ox data's H2O has chosen for this problem after researching state-of-the-art Big Data analytics tools such as Mahout, RHadoop, and Spark because of its rapid in-memory processing, robust machine learning engine, and ease of use. Missed values can be estimated using accurate predictive analytics of massive sensor data, or wrong readings can be replaced owing to malfunctioning sensors or a broken communication line. It can also be used to predict circumstances to aid in various decision-making processes, such as maintenance planning and operation. In this project, sensor data has been evaluated and anticipate output using the H2O tool. The machine learning techniques has been employed in distributed systems, such as connecting five nodes to accomplish parallel processing.
Analysis of Muscular Paralysis using EMG Signal with Wavelet Decomposition Approach
Authors: Patel Shubha V. , Sunitha S. L.
Published: October 2022

Paralysis refers to temporary or permanent loss of voluntary muscle movement in a body part or region. The degree of muscle function loss determines the severity of paralysis. The muscle function is represented by electrical activity of the muscles. Electromyography is a technique concerned with the analysis of myoelectric signals. EMG allows the determination of muscular activity. EMG signal analysis is performed using the features extracted in time domain, frequency domain and time frequency domain. In this work, the EMG of Amyotrophic Lateral Sclerosis (ALS), Myopathy, and Normal conditions are considered, and the time frequency analysis has been carried out to extract the features using wavelet decomposition approach. The classification of normal and paralyzed condition is carried by four classifier models. The classifier models used are Multi-layer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), and Nearest Neighbor (NN) models. The standard data set has been used for the purpose. The classification accuracy obtained for MLP is 80%, for RF is 75%, for GB is 79%, and for NN is 69%. MLP show better classification performance over RF, GB, and NN Classifiers.
Performance Analysis of Muscular Paralysis Disease Using Machine Learning
Authors: Patel Shubha V. , Sunitha S. L.
Published: October 2022

Electromyography has been used for many years in regulating paralyzed limb. Captured and Processed EMG is an indication of human movements. EMG signal (called as Mayo signal) will be recorded by surface electrodes and needle electrodes. In this work, the combined time and frequency analysis has been carried out to extract the required features using Wavelet Transform tools. Further the classification has been carried by 2 different Machine Learning based algorithms, Random Forest (RF), and Multilayer Perceptron (MLP). The standard data set has been used for the purpose. The classifier model has used 80% data as a training set and the remaining 20% of data as the test set. The result shows that Random Forest and MLP perform better with an accuracy of 98 %. This classification model can serves as a promising candidate for analysis of muscular paralysis.
Techniques for Diabetes Care Using Artificial Intelligence and Machine Learning: A Review
Authors: Patil Ajit R. , Ingole Avinash M.
Published: October 2022

All aspects of our lives, including healthcare, are being reshaped by AI/ML (Artificial Intelligence/Machine Learning). Diabetic treatment might benefit greatly from the use of AI and ML, which could make it more effective and less time-consuming. In terms of data availability, the large number of diabetics in India brings a unique set of challenges, but it also gives an opportunity. With the use of electronic medical records, India may become a world leader in this field. The use of AI/ML might shed light on our issues and help us come up with solutions that are unique to each.
Twin K-Shuffle Based Audio Steganography
Authors: Alhassan Salamudeen , Daabo Mohammed Ibrahim , Armah Gabriel Kofi
Published: October 2022

Secure communication is most effective when it is covert. In the realm of covert communication, steganography conceals secret message within a cover medium. This ensures that adversaries who have access to this carrier medium are unaware of the existence of the secret message. This paper proposes a novel twin K-Shuffling and embedding technique that scrambles and hides secret message inside audio samples. The scrambling phase of the proposed technique consists of bit and character shuffling. The bit-shuffling scrambles the bit-string of each character in the secret message into cipher-text via K-Shuffle. The characters of the resulting cipher-text are then shuffled by another K-Shuffle technique to yield chaotic cipher-text. At the embedding phase, the scrambled cipher-text is randomly planted into the carrier audio samples. The novelty in this proposed technique is the provision of a three-layer protection for secret messages; bit, character, and encoding layers. Results and analyses show that this technique satisfied both embedding and encryption requirements of steganographic systems.
Crypto Currency: An Analysis with Financial Literacy as Moderator
Authors: Sharma Hemendra
Published: October 2022

This research paper provides a comprehensive overview on investment intention of subjects towards crypto currency. We hypothesise that trust, electronic word of mouth, perceived risk and moderator financial literacy are the primary reasons for the increased interest in crypto currencies. An online questionnaire was framed and data was collected from 247 respondents who are well aware about digital investments, possess basic knowledge of internet and are keen in exploring more digital avenues of investments. Data analysis was carried out through two stage structural equation modelling. The findings suggested that investment intentions are significantly influenced by trust, electronic word of mouth and perceived risk. Further, financial literacy moderated the effect of electronic word of mouth and trust on investment intention. The current paper is unique and first of its kind in India where it reflects the investment intentions of subjects towards crypto currency along with the linking of trust, electronic word of mouth, perceived risk and financial literacy as moderator. Particularly, the finding of this study is one of a unique attempt to make aware about the investor intention towards crypto currency for the market and the economy.
An Overview on Cyber Crime and Cyber Security
Authors: Tuli Bhumika , Kumar Santosh , Gautam Neha
Published: October 2022

Loss of information through online services is called a “footprint of cybercrime”. So the topic that we will discuss is Cyber Crime and Cyber Security. It is an important part of the information technology field. We all know that cyber crime is increasing day by day, and the government also takes measures to stop this, but it’s not dying from it’s root. In this research paper, we will discuss about the different phases of cyber crime in today’s time and the negative effects tolerated by people due to cybercrime. There are so many financial loses hanging over from heavy engagement in cyber crimes that have been discussed below. This paper also consists of topics related to cyber security, which provides safety to users. Overall, this article gives an intensive overview regarding cyber crime, the work of criminals and the cyber security and because of it how to prevent the cybercrime and make it secure, as new technology is there that comes up with new ideas to protect human life.
Experimental Investigation of the Influence of Sand and Binder Composition on the Mold Properties of Alkyd Type No-Bake Chemically Bonded Sand-Casting System
Authors: Keerthana J.
Published: October 2022

In comparison to green sand moulds, chemically bonded resin sand moulds have better dimensional accuracy, surface quality, and sand mould qualities. To survive sand drops when pouring molten metal, the mould cavity formed using a chemically bonded sand mould technique must have appropriate permeability, strength, and hardness. The desire for better permeability, strength, and mould hardness is based on a thorough investigation and analysis of the affecting parameters, such as resin percentage, hardener, and catalyst. The influence of binder content on the moulding qualities of silica sand bound with Alkyd oil urethane binder was investigated. Using a sieve shaker, the experimental materials were sieved and manually blended with the binders. AFS standard test specimens (50 mm diameter by 50 mm height) were prepared using a sand rammer, and four key moulding parameters were determined using a universal sand strength machine, permeability meter, and mould hardness tester: green compression strength (GCS), green shear strength (GSS), permeability, and mould hardness. For the minimal experiments, Box-Behnken experimental matrices were used, and the statistical significance of influencing factors and their interactions will be identified to manage the process. To statistically validate the model, an analysis of variance (ANOVA) test was performed using Minitab. Mold hardness, strength, and permeability will each have their own mathematical equation, which was stated as a nonlinear function of input factors based on experimental input-output data. To optimize the process parameters, a response optimizer (using Minitab) has been used. The results revealed that increasing the resin concentration from 1% to 2% enhances permeability and GSS while decreasing GCS and mould hardness. Hardener was increased from 18 to 20%, which resulted in a drop in permeability and GSS but an increase in GCS and mould hardness. Similarly, increasing the catalyst concentration from 2% to 10% reduces permeability and mould hardness while increasing GCS and GSS.
Sensor and Process Noises Reduction using a Luenberger State Estimator with a Stability Augmentation System for a Hypersonic Transport Aircraft
Authors: Zaludin Zairil A.
Published: October 2022

This paper firstly, presents an autopilot strategy for a Hypersonic Transport Aircraft (HST) using a Stability Augmentation System (SAS) with a Luenberger estimator. The SAS is designed using Linear Quadratic Regulator (LQR) theory which, for HST, benefits the guaranteed robust dynamic stability provided three theoretical requirements are met. The Luenberger estimator is incorporated into the autopilot design to estimate the state variables of the aircraft for the SAS. In the dynamic response simulation, sensor and process noises are inserted into the mathematical model. However, to date, knowledge of the sensor and process noises at the speeds and heights where the aircraft will be flying is limited. The simulation shows that the Luenberger estimator significantly filters the noise. This is an advantage for the HST as prior knowledge of the noises is not necessary when designing the Luenberger estimator.
Economic Valuation on Conservation of Rainforest in Eastern Sinharaja, Sri Lanka
Authors: Wattage Premachandra , Olugala Hasintha
Published: October 2022

The value for goods and services is noticeable as the price is paid for those goods and services, but in environmental goods and services the real price or value is misrepresent in ordinary markets. Especially the forest benefits or non-market values are not normally exchange in markets and generally ignored in decision making.  Benefits obtained from environmental elements cannot be estimated and it causes for the continuous damages which can be reason for long term worldwide effects. Therefore such values and damages need to be justified at least by ensuring that they can be identified and conserved for future generations. But conserving forest features, improving or managing is costly.  Eastern Sinharaja – Sri Lanka is a world heritage rainforest which represented with valuable resources for all living beings. However, the resources in Eastern Sinharaja is under continuous degradation and requires conservation measures.  The research problem focuses on what is the economic value on conservation of Eastern Sinharaja rainforest environment. This research is attempt to estimate the total value of conservation of Eastern Sinharaja rainforest environment using Contingent Valuation method (CVM). The information was gathered from a questionnaire survey under random sampling method using 234 of sample size. The results has discovered, respectively socio economic variables, general environmental attitudes and willingness to pay sections designed have identified as key sections which derived the main features which are affecting to the economic value of the conservation of the rainforest environment. Gender, employment, voter, income are socio economic features which affect to the economic value. In general environment attitudes for willingness to pay (WTP) and the respondents attitudes are positive when consider about the significance values of the features for Mean WTP of Rs. 257.30 from a household. This study indicated that despite Sri Lanka is a developing country, people are willing to contribute for conservation of the resource. Those derived values may significantly contribute in conservation of rainforest environment and deliver materials to design applicable policies for future rainforest environment management.
The Creation and Validation of a Digital Pedagogical Game for the Teaching of Probability in the Early Years of Elementary School
Authors:   Federal University of ABC, Oliveira Júnior Ailton Paulo , Datori Barbosa Nilceia ,   Federal University of ABC, Simão de Souza Natália Galvão ,   Federal University of ABC, Oliveira Lozada Anneliese ,   Federal University of ABC
Published: October 2022

We consider teaching probabilistic concepts using an educational digital game. In particular, we seek to validate the game’s usefulness through the evaluation of basic education teachers who teach this probabilistic content in their classrooms. We believe that, in addition to creating, developing, and organizing resources and materials for teaching, it is essential that the materials are evaluated to validate their effectiveness for teaching and learning. We seek to offer teachers and students greater possibilities for didactic work by offering digital educational activities for student learning.
E-status, A Web Platform That Strengthens Probability and Statistical Learning
Authors:   Universidad Nacional de La Matanza, Pérez Silvia , Giuliano Mónica ,   Universidad Nacional del Oeste
Published: October 2022

The results of using the e-status platform, a virtual learning environment that favors active learning and metacognition in students are presented. The platform provides the teacher with several indicators and allows the creation of others that allow the characterization of the student's activity. This paper presents the evaluation of the influence of the use of e-status in the approval condition of the subject Probability and Statistics, statistically comparing indicators from 2015 to 2019. The results show that active work in the platform makes the difference in academic performance, and that it is also enhanced when metacognition is favored. Se presentan los resultados de la utilización de la plataforma e-status, un entorno virtual de aprendizaje que favorece en los estudiantes el aprendizaje activo y la metacognición. La plataforma brinda al docente varios indicadores y posibilita la creación de otros que permiten caracterizar la actividad del estudiante. Aquí se presenta la evaluación de la influencia de la utilización de e-status en la condición de aprobación de la asignatura Probabilidad y Estadística, comparando estadísticamente indicadores desde 2015 a 2019. Los resultados muestran que el trabajo activo en la plataforma marca la diferencia en el desempeño académico, y que además este se potencia cuando se favorece la metacognición.
Teaching and Learning Statistics in Multilingual Classrooms: A Collaborative Study
Authors:   The University of Waikato, Sharma Sashi
Published: October 2022

The purpose of this collaborative study was to explore what language practices appear to enhance the statistical understanding of Year-12 multilingual students. Data was collected from audio recordings of teacher reflections while students were carrying out an investigation of existing data sets. The teachers in the study demonstrated a range of specific strategies consistent with research-based effective language learning practice. Whether this was by virtue of prior learning in teacher education or by experience in the collaborative setting cannot be determined here, but this could be an area for future investigation. The paper will generate more interest in language challenges and strategies in statistics education and collaborative research where teachers are regarded as key stakeholders in all aspects of the research process.
Revision Beyond the Copyedit: Encouraging Students to Reorganize, Restructure, and Refocus in Writing Assignments
Authors:   Bucknell University, Stoudt Sara , Nolan Deborah ,   University of California, Berkeley
Published: October 2022

Effective writing rarely appears in the first draft. Scaffolding a project with intermediate checkpoints for instructor or peer feedback can help students experience the revision process, but students may still struggle with the idea of a “serious” revision that goes beyond copyediting. Just like the writing process, the revision process can be daunting. By helping students through a sequence of targeted revision strategies, they can tackle different parts at a time and catch different weaknesses on different passes through a document. This paper provides targeted revision strategies that can support students as they write final reports that have gone through meaningful revision including reorganization, a restructure or further development of a statistical argument, and a refocusing based on intended audience.
Exploring Interdisciplinarity in Project-Based Learning: Choosing the Research Theme
Authors:   Universidade Federal do Rio Grande, Pereira Fernanda Angelo , Gautério Tiago da Silva ,   Universidade Federal do Rio Grande, Cavalcante Hosana Crisostomo ,   Universidade Federal do Rio Grande, Giordano Cassio Cristiano ,   Universidade Federal do Rio Grande
Published: October 2022

This article discusses interdisciplinarity in the teaching of statistics through Project-Based Learning. We share the discussion that arose after publication of the Common National Curriculum Base in 2018, which suggests the inclusion of projects whose level of complexity and broadness increases gradually throughout basic education (from six to seventeen years old). Our goal is to highlight the initial moment that is paramount to the success of this approach: the selection of the theme to be investigated. We describe a qualitative research study that analyses official documents, recent studies in the area, and recordings of the sessions in which teachers and students discuss the theme to be chosen before presenting a few considerations that may contribute to promoting statistics literacy.
A New Survey of Student Attitudes Toward Statistics: The S-SOMAS
Authors:   Mount Saint Vincent University, Whitaker Douglas , Unfried Alana ,   California State University, Batakci Leyla ,   Elizabethtown College, Bolon Wendine ,   RSM US, Bond Marjorie ,   The Pennsylvania State University, Kerby-Helm April ,   Winona State University, Posner Michael ,   Villanova University
Published: October 2022

The Student Survey of Motivational Attitudes toward Statistics is a new instrument designed to measure affective outcomes in statistics education. This instrument is grounded in the established Expectancy-Value Theory of motivation and is being developed using a rigorous process. This paper provides an overview of the four pilot studies that have been conducted during the survey development process. Additionally, a description of the methods used for analyzing the data and the way the results are used to holistically make decisions about revisions to the survey is included. Brief confirmatory factor analysis results are included from two pilot studies to demonstrate that substantial progress has been made on the development. Once finalized (Spring 2023), the survey will be made freely available.
Student Perceptions on Overall Quality of Education of Statistics: A 12-Year Retrospective Study
Authors:   UCL, Institute of Child Health, Bagkeris Emmanouil , Koutoumanou Eirini ,   UCL, Institute of Child Health, Langan Dean ,   UCL, Institute of Child Health, Ogbonnaya Chibueze ,   UCL, Institute of Child Health, Suarez-Rivera Catalina ,   UCL, Institute of Child Health, Wade Angie ,   UCL, Institute of Child Health
Published: October 2022

Several factors may affect the quality of education (QoE). The challenges have intensified over the past 20 months of COVID-19. Our goal is to understand the effect of transitioning to online-learning on QoE amongst those undertaking statistical courses. A total of 714 evaluation forms were collected from students over a period of 12 years. Students were asked to rate the overall QoE of the research methods course. More than 90% of the students agreed that the overall QoE was very good/excellent over the past 12 years. Despite the online delivery of the course since 2020, more than 90% reported a very good/excellent QoE. A synergy of factors may contribute to the retention of an overall good QoE. Further studies could assess the effectiveness of online learning.
Curriculum Guidelines for Probability Teaching and Learning and Statistics in Basic Education in Brazil and Portugal: Advances, Backlashes, and Challenges
Authors:   Universidade Cruzeiro do Sul, Almeida João Luis , dos Santos Anne Karoline ,   Universidade Cruzeiro do Sul, Alves Maria Joseane ,   Universidade Cruzeiro do Sul
Published: October 2022

This work is part of the master's research (in development) of the authors, in the scope of the Graduate Program in Science Teaching, Universidade Cruzeiro do Sul (Brazil). We seek to understand how teaching and learning of probability and statistics are treated in the Mathematics curriculum documents (in effect) of basic education in Brazil and Portugal. We chose to carry out a research of a qualitative approach, of the kind of documentary analysis. Throughout the analysis of the curricular documents it was possible to list advances, setbacks and challenges to the teaching process and learning of probability and statistics in basic education in both countries, which we share in this work. Aiming to contribute to discussions about the curriculum guidelines for teaching and learning probability and statistics. Este trabalho é parte das pesquisas de Mestrado (em desenvolvimento) dos autores, no âmbito do Programa de Pós-Graduação em Ensino de Ciências, da Universidade Cruzeiro do Sul (Brasil). Buscamos compreender como o ensino e aprendizagem de Probabilidade e Estatística são tratados nos documentos curriculares de Matemática (em vigência) da Educação Básica no Brasil e em Portugal. Optamos por realizar uma pesquisa de abordagem qualitativa, do tipo análise documental. Ao longo das análises dos documentos curriculares foi possível elencar avanços, retrocessos e desafios ao processo de ensino e aprendizagem de probabilidade e estatística na Educação Básica em ambos os países, o que compartilhamos neste trabalho. Tendo por objetivo contribuir com as discussões acerca das diretrizes curriculares para o ensino e aprendizagem de probabilidade e estatística.
Data and Data Science: Making Sense of the World
Authors:   Michigan State University, Burrill Gail , Brown Curtis ,   Texas Instruments Education Technology, Dick Thomas ,   Oregon State University
Published: October 2022

Data and data science are becoming increasingly important, and initiatives related to data science at the school level are emerging in countries across the world. This paper considers what data science means, considers its connections to statistics and critical literacies, and suggests a framework for introducing students to the data science process. The framework can provide a structure to inform the development of materials for better understanding of data science and its role in making sense of the world. Several examples aligned with the framework are given and are appropriate for use in the secondary curriculum to maximize learning opportunities for all students. The discussion ends by considering some implications for the school mathematics curriculum.
Promoting Critical Citizenship in Professional Development of Mathematics Teachers via Statistical Investigations
Authors:   Universidad de Antioquia, Zapata-Cardona Lucia , Escobar-Franco Diana Milena ,   Universidad de Antioquia, Santa-Ramírez Zaida ,   Universidad de Antioquia; Tecnológico de Antioquia, García-Barco Liliana ,   Universidad Colegio Mayor de Cundinamarca, Riascos Forero Yilton ,   Universidad del Cauca
Published: October 2022

This proposal studies statistical investigations as tools to promote statistical thinking and critical citizenship in the process of professional development for mathematics teachers. A qualitative methodology with a critical dialectical approach was followed. The information was produced within a professional development for in-service teachers from a public school in the northwest of Colombia. A statistical investigation that addressed CO2 emissions was implemented, and teachers of different teaching levels explored real data from the World Bank by using CODAP software. The units of analysis were the interactions of the teachers with their colleagues during the professional development. The main results exhibit evidence of statistical thinking and critical citizenship in mathematics teachers during the course of the empirical inquiry.