bluuebunny/crossref_metadata_2025 huggingface dataset:
Real-Time Office Seat Allocation System using Spring MVC framework
Authors:   Dept. of Electronics and Communication Engineering, R.V. College of Engineering, Karnataka, India., N Bhargav , P N Dr. Jayanthi ,   Dept. of Electronics and Communication Engineering, R.V. College of Engineering, Karnataka, India.
Published: June 2021

Real-time Seat Allocation System is a web application that assists employees and employers in handling modern-day seating issues at work. Currently, seats are assigned to employees manually, which is a time-consuming process. This might cause issues if seats were not assigned or if none were available for some employees. Furthermore, during pandemics, social distance rules must be followed, making it difficult to manage the workforce. The proportion of individuals allowed in the workplace must adhere properly. As the firm grows, so does the number of employees, which necessitates the expansion of infrastructure, which costs money and time. These issues can be addressed to some extent by a shared office concept, in which employees have access to a desk and can work as needed. This article presents a responsive web application through which company employees can registerusingtheircompanyIDandreserveaseatifoneisavailableonaspecified day and time. Admins can add or remove offices, floors, and seats with certain permissions. To implement the business logic, the application uses Java, Spring MVC web framework with Tomcat server, renders the views using Java Server Pages, and uses front-end technologies like HTML, CSS, and JavaScript for the front-end design of the User Interface. The web application built promotes the concept of using a shared workspace to maximize resource use. It also aids in increasing employee productivity by providing them with workplace seating and schedule flexibility.
Boundary Scan Architecture for a Double Precision Floating Point Subtractor
Authors:   Student, R.V. College of Engineering, Bengaluru., Kashyap Anirudh , Keerthi Kusuma ,   Head of Skill Development, Silival Pvt. Ltd., Bengaluru., D.R. Dr. Shilpa ,   Associate Professor, R.V. College of Engineering, Bengaluru.
Published: June 2021

The boundary scan logic for testing was developed in order to make the process of testing easier for System-on-Chip (SoC) [1] architectures. The proposed work focuses on designing a boundary scan logic for a 64-bit floating-point subtractor unit. The TAP controller designed is capable of executing the three mandatory Joint Test Action Group (JTAG) instructions of the IEEE 1149 standard. The testing architecture has the potential to not only test the functionality of the core logic but also to test single stuck-at faults for all the inputs and outputs of the core logic. A provision for bypassing the core logic was made in order to skip the IC while testing numerous ICs together. A simulation was also performed to demonstrate the above procedures. The designed module can further be used in a larger circuit with other ICs [2]containing a similar boundary scan structure with individual TAP controllers.
Technologies for Traceability in Inventory Management System
Authors:   Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India., Jamkhedkar Mayuri , Sanghavi Parth ,   Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India., Gajera Pooja ,   Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India., Mishra Prof. V. A. ,   Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India., Wanjale Prof. K. H. ,   Department of Computer Engineering, Vishwakarma Institute of Information Technology, Pune, India.
Published: June 2021

Our main aim in this paper is to show that traceability has become more than a way to guarantee the stock details but also useful after the delivery of the orders. In this paper, we are trying to illustrate this idea where how companies can implement traceability using modern technologies. After researching with the various industrial company about how traceability works, we came up the technologies which can help the company to implement traceability with ease. The companies need traceability in order to track the products while packaging, before and after delivery of orders. With coherent traceability, it becomes easier to locate the missing products in the orders after the delivery and provides credibility of the orders. We are going to review three technologies used in the inventory management systems and how can we use these technologies in traceability is Barcode Technology, Radio Frequency Identification(RFID), and Near Field Communication(NFC).
Design of a Start-Up Sequence Controller for a Mammography Machine
Authors:   Dept of Electronics and Communication, RV College of Engineering, India., Udupa T S Rakshak , K Holla Shashank ,   Dept of Electronics and Communication, RV College of Engineering, India., Palecha Namita ,   Dept of Electronics and Communication, RV College of Engineering, India.
Published: June 2021

Mammography, which is also calledMastography, is the process of using low-energy X-rays to inspect the human breast for screening and diagnostics. The purpose of mammography is to detect breast cancer early, usually by looking for specific lumps or microcalcifications. The X-rays used are usually around 30 kVp. Excessive voltage to such a machine would be harmful to the patient. Proper monitoring of temperature and pressure needs to be ensured. To ensure this, a start-up sequence module is developed. The start-up sequence module reads the digitized voltage, pressure, and temperature reading from the sensor and asserts all the outputs to ensure that the machine is ready. The scan chain is formed of 13 scan flip-flops in this configuration. The synthesis mapped the design to 484 instances of cells in the open-source PDK technology. The design had a total area of 594 μm2, with a cell width of 0.297 μm, and a height of 0.99 μm.
Implementation of a Parallel Fault Simulation System using PODEM in a Hardware Accelerator using Python
Authors:   Department of Electronics and Communication Engineering, RV College of Engineering, Bangalore., Bhat K Mahesh , Palecha Namita ,   Department of Electronics and Communication Engineering, RV College of Engineering, Bangalore.
Published: June 2021

VLSI Testing is one of the essential domains in recent times. With the channel length of the transistor decreasing continually, the number of transistors in a chip increases, thus increasing the probability of defects or faults. Automatic Test Pattern Generator is one way to find such input test vectors to the circuit, which will help identify the faults if present. PODEM algorithm is one such algorithm used in this regard. This paper helps in reducing the runtime of this algorithm by the parallelism approach. Different stuck-at faults in the gate level circuit are simulated parallelly.
Test Automation Framework for Embedded Linux Testing
Authors:   RV College of Engineering, Bengaluru, India., K S Sahana , M D Maanas ,   RV College of Engineering, Bengaluru, India., Raju M Govinda ,   RV College of Engineering, Bengaluru, India.
Published: June 2021

Software testing is one of the most important steps before its official roll–out to the market. Testing of embedded software is a very complex, tedious, and time–consuming process. Manual execution of the test cases can pose a huge challenge to the test engineers in terms of the time consumed to execute and compile the results of hundreds of test cases. This paper presents a solution to automate the entire process of build and install of Board Support Package (BSP) using Jenkins, along with the automation of the testing process using Linaro Automation and Validation Architecture (LAVA). The proposed design is validated in a BSP testing environment to show the ease of testing using the framework mentioned in this paper.
SysMon GUI
Authors:   RV College of Engineering, Bengaluru, India., Rajesh Lalage Snehal , Kumar Varganti Naveen ,   Qualcomm Inc., Hyderabad., Rao Doddi R.V. Jagannadha ,   Qualcomm Inc., Hyderabad., Kumar Konda Satya Venkata Pramod ,   Qualcomm Inc., Hyderabad.
Published: June 2021

The goal of this project is to make SysMonApp a graphical user interface. SysMonApp is an Android program that interfaces with Q6s on (Application DSP)ADSP/(Computational DSP)CDSP/(Sensor DSP)SDSP subsystems over FastRPC and supports different user functions such as profiling Q6 workload, getting clock information, setting/removing clocks, and getting software thread information, among other things. SysMonApp offers a variety of features, each with its own set of parameters. Users have a hard time remembering many arguments. The user interface will make it easy for users to access all of the functions in one location.
The sliding wear behavior of CrCuFeNi on alloying with cobalt with varying combination
Authors:   Department of Mechanical Engineering, Kongu Engineering College, Erode, Tamilnadu, India., R Kamalakannan , A Somasundram ,   Department of Mechanical Engineering, Kongu Engineering College, Erode, Tamilnadu, India.
Published: June 2021

Chromium (Cr), Copper (Cu), Cobalt (Co), Ferrous (Fe) and Nickel (Ni), the HighEntropy Alloys were mixed to form analloy. A die was created using OHNS (OilHardenedNickelSteel).Thealloyed powderwasloadedintothedieandaloadof13KNwas applied. Universal Testing Machine (UTM) was used for the load application. Afterpressing, the specimen was kept inside the Muffle Furnace for heating at 600°C for sintering. After heating, the surface of the specimen was smoothened byroughing. The weight of the specimen was noted, before and after the wear test.The specimen was subjected to wear test in Pin on Disc Machine. Wear rate of thespecimen was calculated. This specimen was used to coat the Single Point Cuttingtool. This coating of tool was done to decrease the wear rate and increase the lifeofthe tool.
Review of Image Security approaches: Concepts, Issues, Challenges and Applications
Authors:   Department of Computer Engineering, MPSTME, Mumbai, NMIMS University., S. Radke Shashikant , S. Mishra Dhirendra ,   Department of Computer Engineering, MPSTME, Mumbai, NMIMS University.
Published: June 2021

Currently, digital images are widely used in different applications to represent distinguishable contents. Also, diagnosing diseases using medical images became vital and crucial and if the data in these images are liable for unauthorized usage, this may lead to severe problems. The security of these data has become an urgent and serious problem and needs immediate attention. Traditional encryption and decryption algorithms are not sufficient to secure digital images. Especially, image encryption and decryption algorithms are needed. Securing image data with effective encryption approaches can be more useful for applications. This article aims to comparatively study the different digital image encryption algorithms. In the current Pandemic scenario of COVID-19, the variety of research work can be communicated through the encrypted images among researchers to avoid the leakage of information. These image encryption algorithms are having applications to secure image data and store and share them in the network environments.
Unsupervised Learning for Pairs Trading in the National Stock Exchange of India
Authors:   R.V College of Engineering, India., Tayal Chetan , V.P Lalitha ,   R.V College of Engineering, India.
Published: June 2021

Pairs Trading is a widely known and used market-neutral trading strategy that utilizes the concept of statistical arbitrage. It is based on the idea of mean-reverting time series and relies on the spread between two assets to demonstrate that property to buy an asset at a relatively undervalued price and an asset at a relatively overvalued price. This allows investors to manage risk if the market moves strongly in only one direction by making money on one side of the bet. The main challenge of pairs trading is selecting pairs that have an actual underlying relationship and their spread has real statistical significance. In this paper, we present the use of machine learning, specifically unsupervised clustering to construct our search space for pair selection and compare it against a traditional way of selecting pairs. We see that not only are we able to pick out more profitable pairs, these pairs are also less volatile and have less exposure to the market.
EDUCATIONAL QUALITY ASSURANCE MANAGEMENT IN IMPROVING AND DEVELOPING THE MIDDLE SCHOOL PROFESSIONALISM TEACHERS
Authors: Setiawan Deny
Published: June 2021

This article discusses the management of educator quality assurance in improving and developing teacher professionalism conceptually which includes the implementation of recruitment, the development of teacher professions and termination of employment as an important function in ensuring quality education quality. This article is made by reviewing and gathering information from various references to books, articles and journals that are used as material in conceptually studying and adding insight related to educator quality assurance. The management of educator quality assurance is a good step to support the improvement and acceleration of the improvement of the quality of human resources in the field of education in accordance with the need to improve educator standards and quality, but in implementing educator quality assurance management is expected to be balanced between recruitment, professional development, welfare development and termination of employment. There is still a lot of implementation in the field that causes workload and professional development for senior educators, mediators and juniors and creates new problems in education.
Distribution Channel Analysis of Logistics in Supply Chain Management at the Outlet IAP With VSM in Agricultural Sector Industrial Companies
Authors: Hanum Bethriza
Published: June 2021

PP London Sumatra Indonesia Tbk is a company engaged in agribusiness, which tried to become a retail company in 2016 with Kahuripan Tea products, namely teabags processed from their factories and gardens in the Bandung, West Java area. With marketing areas in West Java and East Java, the focused area is the Jabodetabek area in this research. The problem faced by the company is the delay in the transport order process, which results in delays in the delivery of Kahuripan Tea products to customers. The data on delays used are data from October to December 2019. The problem occurs because there are still many activities that are not value-added which are classified as waste. This research aims to analyze improvements in the transport order process that occurs in the business development and procurement department at PT. PP London Sumatra Indonesia Tbk, with a lean manufacturing approach with the value stream mapping (VSM) method, analyzes the dominant waste in the transport ordering process. Based on the analysis results, there were three improvements, namely the approval process, the price bidding process, and the vendor selection process. The results of the improvement evaluation obtained a decrease in lead time by 560 minutes and an increase in the value of Process Cycle Efficiency by 46%. So, this improvement will increase the practical value in the transport ordering process: that way, PT. PP London Sumatra Indonesia Tbk can increase customer value with fast service time and good quality.
Factors that Needs Improvement in Participatory Budgeting Projects to Achieve Community Development Goals in Port Loko District and City Council
Authors: Lavalie D.E.M. , Subadra S. , Sreekala S. P.
Published: June 2021

The purpose of the study is to find out and recommend the factors that need improvement in the future implementation of participatory budgeting in Port Loko District and City Council in order to achieve community development goals. As our study is based on primary data, we collected 420 questionnaires to analyse our findings. A lot of factors were identified and analysed using Garret Ranking Techniques.
GAGAUZ ÇALGILARINDAN KAUŞ
Authors: DELİGÖZ Atakan
Published: June 2021

Bu makalede; Balkanlarda yaşayan Gagauzların kullandığı müzik aletlerinden biri olan kauş çalgısı ele alınmıştır. Üç telli olan ve icrası bir yay vasıtasıyla yapılan bu çalgı, fiziki yapı bakımından küçük ebatlı olmakla birlikte armudi şekillidir.
Kauş çalgısının genel durumunu tespit etmek için, 2012 yılında Moldova’nın Gagauz Özerk Yeri’nde saha çalışması yapılmış ve bu kapsamda farklı alanlardaki uzmanlar ve müzisyenler ile görüşülmüştür. Öte yandan müzelerde ve şahıslarda bulunan kauş çalgıları detaylı olarak incelenmiştir. Tespit edilen çalgıların üretiminde kullanılan malzemeleri, ebatları, formları ve icra biçimleri hakkında bilgiler edinilmiştir. Ayrıca elde edilen bilgiler doğrultusunda bu çalgının iki boyutlu genel teknik çizimi yapılmıştır. Böylece çalışmada kauşun ifade edilen bölümlerinin daha rahat anlaşılması sağlanmıştır.
Çalışmada, kauş çalgısının geçmişte yaygın olarak icra edildiği, 20. yüzyılda kullanımının giderek azaldığı ve günümüzde ise kaybolmaya yüz tuttuğu anlaşılmıştır. Öte yandan bu çalgının çoğunlukla müzelerde yer aldığı görülmüştür. Böylece tarihsel ve kültürel açıdan ele alınarak incelenen kauş, yapısal özellikleri ve icra tarzı açısından belgelenmeye çalışılmıştır. Ayrıca çalgının yeniden kullanılır hale getirilmesi ve yaygınlaştırılması hususanda somut öneriler sunulmuştur.
Consumer Purchasing Behaviour and Neuromarketing in The Context of Gender Differences
Authors: STEFKO Robert , TOMKOVA Anna , KOVALOVA Jana , ONDRIJOVA Ivana
Published: June 2021

The paper, in the theoretical part, deals with the issue of neuromarketing and gender differences in the context of shopping behavior. The main goal is to identify statistically significant differences in the evaluation of consumer shopping behavior and neuromarketing in the context of gender equality.
Karmaşık Soyut Ötesi Düşünme Ölçeğini Uyarlama Çalışması
Authors: BAŞARAN Mehmet , ÖĞRETİR ÖZÇELİK Ayşe Dilek
Published: June 2021

Soyut işlem döneminden sonra ortaya çıktığı kabul edilen soyut ötesi düşünme, yetişkinlerin soyut işlemler döneminden farklı olarak düşündüğünü ifade etmektedir. Soyut işlemler dönemiyle karşılaştırıldığında bu düşünme türünün daha karmaşık, dinamik, esnek ve bağlamsal temelli olduğu bulunmuştur. Bu doğrultuda araştırmanın amacı son zamanlarda kavramsallaştırılan soyut ötesi düşünmeyi ölçmek için Karmaşık Soyut Ötesi Düşünme Ölçeğini Türkçeye uyarlamaktır. Araştırmanın çalışma grubu 161 lisans öğrencisinden oluşmaktadır. Yapılan analiz sonucunda ölçeğin kabul edilebilir güvenilirlik katsayısına sahip olduğu (α =.88); madde toplam korelasyonlarının ise .35 ile .71 arasında değiştiği görülmüştür. Karmaşık Soyut Ötesi Düşünme Ölçeğinin ölçüt geçerliliği için kullanılan Biliş İhtiyacı Ölçeği ile pozitif yönde anlamlı bir korelasyona sahip olduğu bulunmuştur. Sonuç olarak ölçeğinin geçerli ve güvenilir olduğu görülmüştür.
Okul Öncesi Öğretmen Adaylarının Meslek Tercih Nedenleri: İçsel ve Dışsal Faktörler
Authors: BULDUR Aycan , KESKİN Meryem Ezgi , BÖREKÇİ Esma
Published: June 2021

Öğretmen adaylarının öğretmenlik mesleğini tercih etme nedenleri, mesleki performansları ve gelecek beklentileri üzerinde etkili olması nedeniyle önem taşımaktadır. Bu bağlamda bu araştırmanın amacı da okul öncesi öğretmen adaylarının öğretmenlik mesleğini tercih etme nedenlerini incelemektir. Araştırmanın çalışma grubunu bir devlet üniversitesinin Okul Öncesi Öğretmenliği Anabilim dalında öğrenim görmekte olan 90 öğretmen adayı oluşturmaktadır. Görüşme formu aracılığıyla toplanan veriler kategorisel içerik analizi yöntemiyle analiz edilmiştir. Analizler sonucunda öğretmen adaylarının öğretmenlik mesleğini hem içsel hem de dışsal faktörlerle tercih ettikleri ortaya çıkmıştır. Ancak tercih nedenlerinde içsel faktörlerin dışsal faktörlere kıyasla daha etkili olduğu tespit edilmiştir. Diğer taraftan elde edilen bulgulara göre katılımcıların büyük bir kısmı üniversiteye yerleşme aşamasında okudukları bölümü ilk sıralarda tercih ettiklerini ve tekrar tercih şansları olsa okul öncesi öğretmenliği programını yeniden tercih edeceklerini ifade etmişlerdir.
A TRADE WAR BETWEEN CHINA AND THE USA: WHAT WILL HAPPEN IN THE RELATIONS OF THE USA AND CHINA IN 2020
Authors:   PhD student, Eurasian National University named after L.N. Gumilyova, Nur-Sultan, Kazakhstan, Ibragimova А.Т.
Published: June 2021

In 2018, a bipartisan consensus finally emerged in the United States, which is based on the policy of containing China in the military and technological spheres, as well as avoiding the dependence of the American economy on the PRC. The main geopolitical event of 2018-2019 was the escalation of the confrontation between the two most powerful powers of our time - the United States and China. The most notable episodes of this confrontation were the Washington-declared trade war, as well as the October speech by US Vice President Michael Pence at the Hudson Institute, which is already being compared to Churchill's Fulton speech. 2019 has become no less difficult for the relations of the two superpowers.
PROFESSIONAL AND PEDAGOGICAL TRAINING OF THE FUTURE TEACHER IN THE LIGHT OF THE HISTORICAL AND CULTURAL APPROACH
Authors:   PhD, associate Professor at the University, Shyngyshbaev B. , Akramova А. ,   Ph. D., associate Professor of the University of Almaty, Ziyabekova B. ,   the master of pedagogical Sciences at the University
Published: June 2021

The article deals with the issues of professional and pedagogical training of the future teacher in the light of the historical and cultural approach. The authors revealed the essence of the concepts "culture"," culture intensity " and touched upon the problems of the historical-genetic method when considering culture-oriented learning. The article presents the principles of cultural - oriented content of pedagogical education, pedagogical conditions for the implementation of the cultural approach in the course of professional and pedagogical training of teachers. The article is aimed at the implementation of pedagogical education, which makes it necessary to implement a historical and cultural approach to the selection of content.
FORMAÇÃO DE PROFESSORES E O USO DE TECNOLOGIA DIGITAIS NO ENSINO DE LI PARA CRIANÇAS
Authors: Schweikart Juliana Freitag
Published: June 2021

Este trabalho apresenta resultados parciais de um projeto de extensão universitária que culminou em uma tese de doutorado. Na tese não foi possível fazer uso de todos os dados levantados, dessa forma, trago aqui demais aspectos sobre a formação de professores de língua inglesa para crianças e o uso das tecnologias digitais. Os participantes da pesquisa eram acadêmicos do curso de Letras da Universidade do Estado de Mato Grosso, no município de Sinop que, após participarem de formação por meio de um projeto de extensão com o tema, título deste artigo, ofertaram oficinas de inglês por meio de tecnologias digitais à crianças do Programa Mais Educação em escolas municipais. O trabalho foi baseado em autores que tratam da formação docente (GIMENEZ, 2013; IMBERNÓN, 2005; entre outros), tecnologias digitais na educação (MAYRINK e ALBUQUERUE-COSTA, 2013; MAYRINK, RODRIGUES e BINHOLO, 2013; para citar alguns), e Língua Inglesa para Crianças (CAMERON, 2001; SANTOS, 2009; ROCHA, 2009). Os resultados apresentaram a importância do tempo de exposição dos professores em formação inicial ao estudo do assunto, ao contato com as crianças durante as experiências e os momentos de reflexão em grupo, bem como aprendizado significativo por parte das crianças.
Full flowering phenology of apple tree (Malus domestica) in Pūre orchard, Latvia from 1959 to 2019
Authors: Kalvāne Gunta , Gribuste Zane , Kalvāns Andis
Published: June 2021

Abstract. The Pūre orchard is one of the oldest apple orchards
in the Baltic, where thousands of varieties of fruit trees from throughout
the world are grown and tested. Over time, a huge knowledge base has been
accumulated, but most of the observational data are stored in archives in
paper format. We have digitized a small part of the full flowering
phenological data of apple trees (Malus domestica) over the period of 1959 to 2019 for 17
varieties of apple trees, a significant step for horticulture and
agricultural economics in Latvia. Climate change has led to significant
changes in the phenology of apple trees as all varieties, autumn, summer and
winter, have begun to flower earlier: from 2002 to 2019, on average full
flowering was recorded to have taken place around 21 May, whereas for the
period 1959–1967 it occurred around 27–28 May. To develop better-quality phenological predictions and to take account of
the fragmentary nature of phenological data, in our study we assessed the
performance of three meteorological data sets – gridded observation data
from E-OBS, ERA5-Land reanalysis data and direct observations from a distant
meteorological station – in simple phenological degree-day models. In the
first approximation, the gridded E-OBS data set performs best in our
phenological model.
Persistent effects of sand extraction on habitats and associated benthic communities in the German Bight
Authors: Mielck Finn , Michaelis Rune , Hass H. Christian , Hertel Sarah , Ganal Caroline , Armonies Werner
Published: June 2021

Abstract. Sea-level rise demands for protection measures of endangered
coastlines crucial for the local population. At the island of Sylt in the SE
North Sea, shoreline erosion is compensated by replenishment with sand
dredged from an offshore extraction site. We studied the long-term effects
of sand extraction on bathymetry, geomorphology, habitats and benthic
fauna. Sand extraction created dredging holes about 1 km in diameter and up
to 20 m below the ambient seafloor level. Directly after dredging the
superficial sediment layer, inside the pits was dominated by coarse sand and
stones. Hydroacoustic surveys revealed only minor changes of bathymetry
> 35 years after sand extraction. Obviously, backfill of the
dredging pits was very slow, at a rate of a few millimeters per year, presumably
resulting from low ambient sediment availability and relatively calm
hydrodynamic conditions despite high wave energy during storms. Thus, a
complete backfill of the deep extraction sites is likely to take centuries
in this area. Hydroacoustic surveys and ground truthing showed that the
backfilled material is mainly very fine sand and mud, turning the previously
coarse sand surface into a muddy habitat. Accordingly, grab samples revealed
significant differences in macrozoobenthos community composition, abundance
and species density between recently dredged areas (< 10 years ago),
recovery sites (dredging activity > 10 years ago) and undisturbed
sites (control sites). Overall, dredging turned the original association of
sand-dwelling species into a muddy sediment association. Since
re-establishment of disturbed benthic communities depends on previous
re-establishment of habitat characteristics, the low sedimentation rates
indicate that a return to a pre-dredging habitat type with its former
benthic community and habitat characteristics is unlikely. Since coarse sand
is virtually immobile in this area, a regeneration towards pre-dredging
conditions is also unlikely without human interference (e.g., mitigation
measures like depositing coarse material on the seafloor to restore the
sessile epifauna).
Revised fractional abundances and warm-season temperatures substantially improve brGDGT calibrations in lake sediments
Authors: Raberg Jonathan H. , Harning David J. , Crump Sarah E. , de Wet Greg , Blumm Aria , Kopf Sebastian , Geirsdóttir Áslaug , Miller Gifford H. , Sepúlveda Julio
Published: June 2021

Abstract. Distributions of branched glycerol dialkyl glycerol tetraethers (brGDGTs) are frequently employed for reconstructing terrestrial paleotemperatures
from lake sediment archives. Although brGDGTs are globally ubiquitous, the microbial producers of these membrane lipids remain unknown, precluding a
full understanding of the ways in which environmental parameters control their production and distribution. Here, we advance this understanding in
three ways. First, we present 43 new high-latitude lake sites characterized by low mean annual air temperatures (MATs) and high seasonality, filling
an important gap in the global dataset. Second, we introduce a new approach for analyzing brGDGT data in which compound fractional abundances (FAs)
are calculated within structural groups based on methylation number, methylation position, and cyclization number. Finally, we perform linear and
nonlinear regressions of the resulting FAs against a suite of environmental parameters in a compiled global lake sediment dataset
(n = 182). We find that our approach deconvolves temperature, conductivity, and pH trends in brGDGTs without increasing calibration errors
from the standard approach. We also find that it reveals novel patterns in brGDGT distributions and provides a methodology for investigating the
biological underpinnings of their structural diversity. Warm-season temperature indices outperformed MAT in our regressions, with the mean temperature of months above
freezing yielding the highest-performing model (adjusted R2 = 0.91, RMSE = 1.97 ∘C, n = 182). The natural
logarithm of conductivity had the second-strongest relationship to brGDGT distributions (adjusted R2 = 0.83, RMSE = 0.66,
n = 143), notably outperforming pH in our dataset (adjusted R2 = 0.73, RMSE = 0.57, n = 154) and providing a potential new
proxy for paleohydrology applications. We recommend these calibrations for use in lake sediments globally, including at high latitudes, and detail
the advantages and disadvantages of each.
Changes in China's anthropogenic emissions and air quality during the COVID-19 pandemic in 2020
Authors: Zheng Bo , Zhang Qiang , Geng Guannan , Chen Cuihong , Shi Qinren , Cui Mengshi , Lei Yu , He Kebin
Published: June 2021

Abstract. The COVID-19 pandemic lockdowns led to a sharp drop in
socio-economic activities in China in 2020, including reductions in fossil
fuel use, industry productions, and traffic volumes. The short-term impacts
of lockdowns on China's air quality have been measured and reported,
however, the changes in anthropogenic emissions have not yet been assessed
quantitatively, which hinders our understanding of the causes of the air
quality changes during COVID-19. Here, for the first time, we report the
anthropogenic air pollutant emissions from mainland China by using a
bottom-up approach based on the near-real-time data in 2020 and use the
estimated emissions to simulate air quality changes with a chemical
transport model. The COVID-19 lockdown was estimated to have reduced China's
anthropogenic emissions substantially between January and March in 2020,
with the largest reductions in February. Emissions of SO2, NOx,
CO, non-methane volatile organic compounds (NMVOCs), and primary PM2.5 were estimated to have decreased by
27 %, 36 %, 28 %, 31 %, and 24 %, respectively, in February 2020
compared to the same month in 2019. The reductions in anthropogenic
emissions were dominated by the industry sector for SO2 and PM2.5
and were contributed to approximately equally by the industry and
transportation sectors for NOx, CO, and NMVOCs. With the spread of
coronavirus controlled, China's anthropogenic emissions rebounded in April
and since then returned to the comparable levels of 2019 in the second half
of 2020. The provinces in China have presented nearly synchronous decline
and rebound in anthropogenic emissions, while Hubei and the provinces
surrounding Beijing recovered more slowly due to the extension of lockdown
measures. The ambient air pollution presented much lower concentrations
during the first 3 months in 2020 than in 2019 while rapidly returning to comparable levels afterward, which have been reproduced by the air
quality model simulation driven by our estimated emissions. China's monthly
anthropogenic emissions in 2020 can be accessed from
https://doi.org/10.6084/m9.figshare.c.5214920.v2 (Zheng et al., 2021) by
species, month, sector, and province.
Glacier changes in the Chhombo Chhu Watershed of the Tista basin between 1975 and 2018, the Sikkim Himalaya, India
Authors: Chowdhury Arindam , Sharma Milap Chand , Kumar De Sunil , Debnath Manasi
Published: June 2021

Abstract. Glaciers of the Tista basin represent an important water source
for mountain communities and a large population downstream. The article
presents observable changes in the Chhombo Chhu Watershed (CCW) glacier area
of the Tista basin, the Sikkim Himalaya. The CCW contains 74 glaciers
(> 0.02 km2) with a mean glacier size of 0.61 km2. We
determined changes in glaciers from the declassified Hexagon Keyhole-9 (KH-9) (1975),
Landsat 5 Thematic Mapper (TM) (1989), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) (2000), Landsat 5 TM (2010), and
Sentinel-2A (2018) images. The total glacier area in 1975 was 62.6 ± 0.7 km2; and by 2018, the area had decreased to 44.8 ± 1.5 km2, an area loss of 17.9 ± 1.7 km2 (0.42 ± 0.04 km2 a−1). Clean glaciers exhibited more area loss of 11.8 ± 1.2 km2 (0.27 ± 0.03 km2 a−1) than partially
debris-covered and maximally debris-covered glaciers. The area loss is 5.0 ± 0.4 km2 (0.12 ± 0.01 km2 a−1) for partially
covered glaciers and 1.0 ± 0.1 km2 (−0.02 ± 0.002 km2 a−1) for maximally covered glaciers. The glacier area loss in the CCW of
the Sikkim Himalaya is 0.62 ± 0.5 km2 a−1 during 2000–2010,
and it is 0.77 ± 0.6 km2 a−1 during 2010–2018. Field
investigations of selected glaciers and climatic records also support the
glacier recession in the CCW due to a significant increase in temperature
(0.25 ∘C a−1) and more or less static precipitation since
1995. The dataset is now available from the Zenodo web portal:
https://doi.org/10.5281/zenodo.4457183 (Chowdhury et al., 2021).
INDIVIDUAL TREE EXTRACTION FROM UAV LIDAR POINT CLOUDS BASED ON SELF-ADAPTIVE MEAN SHIFT SEGMENTATION
Authors: Hui Z. , Li N. , Xia Y. , Cheng P. , He Y.
Published: June 2021

Abstract. Unman aerial vehicle (UAV) LiDAR has been widely used in the field of forestry. Individual tree extraction is a key step for forest inventory. Although many individual tree extraction methods have been proposed, the individual tree extraction accuracy is still low due to the complex forest environments. Moreover, many parameters in these methods generally need to be set. Thus, the degree of automation of the methods is generally low. To solve these problems, this paper proposed an automatic mean shift segmentation method, in which the kernel bandwidths can be calculated self-adaptively. Meanwhile, a hierarchy mean shift segmentation technique was proposed to extract individual tree gradually. A plot-level UAV LiDAR tree dataset was adopted for testing the performance of the proposed method. Experimental results showed that the proposed method can achieve better individual tree extraction result without any parameter setting. Compared with the traditional mean shift segmentation method, both the completeness and mean accuracy of the proposed method are higher.
A REVIEW OF THE ONE-PARAMETER DIVISION UNDISTORTION MODEL
Authors: Erdnüß B.
Published: June 2021

Abstract. The one-parameter division undistortion model by (Lenz, 1987) and (Fitzgibbon, 2001) is a simple radial distortion model with beneficial algebraic properties that allows to reason about some problems analytically that can only be handled numerically in other distortion models. One property of this distortion model is that straight lines in the undistorted image correspond to circles in the distorted image. These circles are fully described by their center point, as the radius can be calculated from the position of the center and the distortion parameter only. This publication collects the properties of this distortion model from several sources and reviews them. Moreover, we show in this publication that the space of this center is projectively isomorphic to the dual space of the undistorted image plane, i.e. its line space. Therefore, projective invariant measurements on the undistorted lines are possible by the according measurements on the centers of the distorted circles. As an example of application, we use this to find the metric distance of two parallel straight rails with known track gauge in a single uncalibrated camera image with significant radial distortion.
REMOTE SENSING IMAGE CLASSIFICATION WITH THE SEN12MS DATASET
Authors: Schmitt M. , Wu Y.-L.
Published: June 2021

Abstract. Image classification is one of the main drivers of the rapid developments in deep learning with convolutional neural networks for computer vision. So is the analogous task of scene classification in remote sensing. However, in contrast to the computer vision community that has long been using well-established, large-scale standard datasets to train and benchmark high-capacity models, the remote sensing community still largely relies on relatively small and often application-dependend datasets, thus lacking comparability. With this paper, we present a classification-oriented conversion of the SEN12MS dataset. Using that, we provide results for several baseline models based on two standard CNN architectures and different input data configurations. Our results support the benchmarking of remote sensing image classification and provide insights to the benefit of multi-spectral data and multi-sensor data fusion over conventional RGB imagery.
INFLUENCE OF SPATIAL AND TEMPORAL RESOLUTION ON TIME SERIES-BASED COASTAL SURFACE CHANGE ANALYSIS USING HOURLY TERRESTRIAL LASER SCANS
Authors: Anders K. , Winiwarter L. , Mara H. , Lindenbergh R. C. , Vos S. E. , Höfle B.
Published: June 2021

Abstract. Near-continuously acquired terrestrial laser scanning (TLS) data contains valuable information on natural surface dynamics. An important step in geographic analyses is to detect different types of changes that can be observed in a scene. For this, spatiotemporal segmentation is a time series-based method of surface change analysis that removes the need to select analysis periods, providing so-called 4D objects-by-change (4D-OBCs). This involves higher computational effort than pairwise change detection, and efforts scale with (i) the temporal density of input data and (ii) the (variable) spatial extent of delineated changes. These two factors determine the cost and number of Dynamic Time Warping distance calculations to be performed for deriving the metric of time series similarity. We investigate how a reduction of the spatial and temporal resolution of input data influences the delineation of twelve erosion and accumulation forms, using an hourly five-month TLS time series of a sandy beach. We compare the spatial extent of 4D-OBCs obtained at reduced spatial (1.0 m to 15.0 m with 0.5 m steps) and temporal (2 h to 96 h with 2 h steps) resolution to the result from highest-resolution data. Many change delineations achieve acceptable performance with ranges of ±10 % to ±100 % in delineated object area, depending on the spatial extent of the respective change form. We suggest a locally adaptive approach to identify poor performance at certain resolution levels for the integration in a hierarchical approach. Consequently, the spatial delineation could be performed at high accuracy for specific target changes in a second iteration. This will allow more efficient 3D change analysis towards near-realtime, online TLS-based observation of natural surface changes.
DETECTING CRACKS AND SPALLING AUTOMATICALLY IN EXTREME EVENTS BY END-TO-END DEEP LEARNING FRAMEWORKS
Authors: Bai Y. , Sezen H. , Yilmaz A.
Published: June 2021

Abstract. In this paper, we develop and implement end-to-end deep learning approaches to automatically detect two important types of structural failures, cracks and spalling, of buildings and bridges in extreme events such as major earthquakes. A total of 2,229 images were annotated, and are used to train and validate three newly developed Mask Regional Convolutional Neural Networks (Mask R-CNNs). In addition, three sets of public images for different disasters were used to test the accuracy of these models. For detecting and marking these two types of structural failures, one of proposed methods can achieve an accuracy of 67.6% and 81.1%, respectively, on low- and high-resolution images collected from field investigations. The results demonstrate that it is feasible to use the proposed end-to-end method for automatically locating and segmenting the damage using 2D images which can help human experts in cases of disasters.
WEAKLY SUPERVISED PSEUDO-LABEL ASSISTED LEARNING FOR ALS POINT CLOUD SEMANTIC SEGMENTATION
Authors: Wang P. , Yao W.
Published: June 2021

Abstract. Competitive point cloud semantic segmentation results usually rely on a large amount of labeled data. However, data annotation is a time-consuming and labor-intensive task, particularly for three-dimensional point cloud data. Thus, obtaining accurate results with limited ground truth as training data is considerably important. As a simple and effective method, pseudo labels can use information from unlabeled data for training neural networks. In this study, we propose a pseudo-label-assisted point cloud segmentation method with very few sparsely sampled labels that are normally randomly selected for each class. An adaptive thresholding strategy was proposed to generate a pseudo-label based on the prediction probability. Pseudo-label learning is an iterative process, and pseudo labels were updated solely on ground-truth weak labels as the model converged to improve the training efficiency. Experiments using the ISPRS 3D sematic labeling benchmark dataset indicated that our proposed method achieved an equally competitive result compared to that using a full supervision scheme with only up to 2‰ of labeled points from the original training set, with an overall accuracy of 83.7% and an average F1 score of 70.2%.
TOWARDS MESH-BASED DEEP LEARNING FOR SEMANTIC SEGMENTATION IN PHOTOGRAMMETRY
Authors: Knott M. , Groenendijk R.
Published: June 2021

Abstract. This research is the first to apply MeshCNN – a deep learning model that is specifically designed for 3D triangular meshes – in the photogrammetry domain. We highlight the challenges that arise when applying a mesh-based deep learning model to a photogrammetric mesh, especially w.r.t. data set properties. We provide solutions on how to prepare a remotely sensed mesh for a machine learning task. The most notable pre-processing step proposed is a novel application of the Breadth-First Search algorithm for chunking a large mesh into computable pieces. Furthermore, this work extends MeshCNN such that photometric features based on the mesh texture are considered in addition to the geometric information. Experiments show that including color information improves the predictive performance of the model by a large margin. Besides, experimental results indicate that segmentation performance could be advanced substantially with the introduction of a high-quality benchmark for semantic segmentation on meshes.
MAXIMUM CONSENSUS LOCALIZATION USING LIDAR SENSORS
Authors: Axmann J. , Brenner C.
Published: June 2021

Abstract. Real world localization tasks based on LiDAR usually face a high proportion of outliers arising from erroneous measurements and changing environments. However, applications such as autonomous driving require a high integrity in all of their components, including localization. Standard localization approaches are often based on (recursive) least squares estimation, for example, using Kalman filters. Since least squares minimization shows a strong susceptibility to outliers, it is not robust.In this paper, we focus on high integrity vehicle localization and investigate a maximum consensus localization strategy. For our work, we use 2975 epochs from a Velodyne VLP-16 scanner (representing the vehicle scan data), and map data obtained using a Riegl VMX-250 mobile mapping system. We investigate the effects of varying scene geometry on the maximum consensus result by exhaustively computing the consensus values for the entire search space. We analyze the deviations in position and heading for a circular course in a downtown area by comparing the estimation results to a reference trajectory, and show the robustness of the maximum consensus localization.
EELGRASS MAPPING WITH SENTINEL-2 AND UAV DATA IN PRINCE EDWARD ISLAND (CANADA)
Authors: Gallant E. , LaRocque A. , Leblon B. , Douglas A.
Published: June 2021

Abstract. Eelgrass (Zostera marina L.) is a marine angiosperm that grows throughout coastal regions in Atlantic Canada. Eelgrass beds provide a variety of important ecosystem services, and while it is considered an important marine species, little research has been done to understand its distribution and location within Atlantic Canada. The purpose of this study was to assess the capability of Sentinel-2 and UAV imagery to map the presence of eelgrass beds within the Souris River in Prince Edward Island. Both imageries were classified using the non-parametric Random Forests (RF) supervised classifier and the resulting classification was validated using sonar data. The Sentinel-2 classified image had a lower validation accuracy at 77.7%, while the UAV classified image had a validation accuracy of 90.9%. The limitations of the study and recommendations for future work are also presented.
GERMANYS FIRST CLOUD-BASED WEB SERVICE FOR LAND MONITORING USING COPERNICUS SENTINEL-2 DATA
Authors: Knoefel P. , Herrmann D. , Sindram M. , Hovenbitzer M.
Published: June 2021

Abstract. The research and development project named Landscape Change Detection Service (German abbreviation: LaVerDi) was initiated by the German Federal Agency for Cartography and Geodesy (BKG). Within the scope of the project a monitoring service for landscape changes was developed and implemented using free Copernicus satellite data for an automated derivation of potential land cover change. This change indication is meant to be used to update or continue BKG in-house products, such as the Digital Land Cover Model Germany (LBM-DE), in a comprehensive and uniform quality. The results can be further used for numerous applications or as change information for administration and planning, and for the compilation of spatial statistics. It satisfies the users' need for a national service for open data on land cover changes and thus represents the first automatic and verified national satellite product for land cover changes in Germany. As input data the service uses pre-processed Sentinel-2 data from the European Copernicus satellite program, as well as an image segmentation approach to extract change objects. Using an improved cloud mask algorithm, Sentinel-2 tiles with up to maximum cloud coverage of 60% can be used for analysis. The service (data processing, change detection, visualisation) runs on the German “Copernicus Data and Utilization Platform” (CODE-DE). As of December 2020, the INSPIRE-compliant LaVerDi web service is operational. The thematic accuracy of the generated change layers is above the given requirements (minimum of 80%), considering the 95% confidence interval for all relevant land cover classes in certain test areas. The transferability of the methodology has been successfully shown by a prototypic nationwide demonstrator in early 2020 and is therefore expected to reliably detect both long-term and seasonal changes.