bluuebunny/crossref_metadata_2025_split huggingface dataset:
DograNet – a comprehensive offline dogra handwriting character dataset
Authors: Kumar J , Roy A 
Published: May 2022

Abstract
Handwritten Text Recognition is an important area of research because of growing demand to process and convert a huge data and information available in handwritten form to Digital form. The digital data instead of handwritten form can prove to be highly useful in different fields. Handwritten text recognition plays an important role in applications involved in, postal services, banks for cheque processing, searching of information and organization dealing with such applications. In text recognition application dataset of the specified script is required for training purpose. Datasets of the different languages could be found online but dataset of dogra script characters is still not available. This paper presents a Dogra handwriting character dataset which contains around 38690 character images etc grouped in 73 character classes extracted from 530 one-page handwritings of 265 individuals of having variable age, sex, qualification, location. The dogra character dataset would be freely accessible by scholars and researchers which could also be used for further recognition improvement and updating with more characters and word, Identification of writer, dogra word segmentation. Dogra dataset could also be used for extracting variation of handwriting according to age and gender.
Mathematical Model for Field Data Based for Productivity Enhancement of Cylinder Head Moulding Operation
Authors: Zakiuddin Kazi Syed , Bachute Rahul , Zahiruddin Quazi Syed 
Published: May 2022

Abstract
The paper illustrates with an approach for formulation of generalized field data based model for cylinder head moulding operation. The aim of field data based modeling for cylinder head moulding operation is to evaluate variable responsible for productivity enhancement & with minimum human energy expenditure. The study identifies important ergonomic and other work environment related parameters which affect the productivity. The identified parameters are properties of sand, physical dimensions of tools, energy outflow of workers, workers anthropometric data, working environment. Out of all the variables responses and causes are identified.
After dimensional analysis relationship between the dependent and independent parameters, a mathematical model is established having relationship between output parameters and input. To get the optimized values model is optimized using the optimization technique. Sensitivity analysis is a tool which can be used to find out the effect of input one parameter over the other. The model will be useful for an industrialist to select optimized inputs so as to get targeted responses.
Measurement of high-pressure xenon gas absorption in acrylic
Authors: Lin H. , Ni K. , Du H. , Han K. , Ji X. , Li T. , Luo L. , Wang S. , Yan X. , Zeng X. , Zhang W. 
Published: May 2022

Abstract
Acrylic is a popular structural material in experiments
requiring low background because of its radio-purity, machinability,
and mechanical strength. However, its porosity may cause
significant gas absorption and influence the detector stability in
the long term. The interaction between acrylic and other detector
materials becomes one of the key concerns in the detector design.
In this paper, we carry out an experiment to measure quantitatively
the absorption process of high-pressure xenon gas into acrylic. A
specific setup is designed for the measurement, and systematic
measurements are done to obtain a result of the absorption amount:
0.98 g xenon into 332 g of acrylic.
Evaluation of the Constant Fraction Time-Over-Threshold (CF-TOT) method for neutron-gamma pulse shape discrimination
Authors: Roy A. , Vartsky D. , Mor I. , O. Cohen E. , Yehuda-Zada Y. , Beck A. , Arazi L. 
Published: May 2022

Abstract
The use of Time-over-Threshold (TOT) for the discrimination
between fast neutrons and gamma-rays is advantageous when large
number of detection channels are required due to the simplicity of
its implementation. However, the results obtained using the
standard, Constant Threshold TOT (CT-TOT) are usually inferior to
those obtained using other pulse shape discrimination (PSD) methods,
such as Charge Comparison or Zero-Crossing approaches, especially
for low amplitude neutron/gamma-ray pulses. We evaluate another TOT
approach for fast neutron/gamma-ray PSD using Constant-Fraction
Time-over-Threshold (CF-TOT) pulse shape analysis. The CT-TOT and
CF-TOT methods were compared quantitatively using digitized
waveforms from a liquid scintillator coupled to a photomultiplier
tube as well as from a stilbene scintillator coupled to a
photomultiplier tube and a silicon photomultiplier. The quality of
CF-TOT neutron/gamma-ray discrimination was evaluated using Receiver
Operator Characteristics curves and the results obtained with this
approach were compared to that of the standard CT-TOT method. The
CF-TOT PSD method results in > 99.9% rejection of gamma-rays with
> 80% neutron acceptance, much better than CT-TOT.
Estimating curvilinear self-motion from optic flow with a biologically inspired neural system*
Authors: Layton Oliver W , Powell Nathaniel , Steinmetz Scott T , Fajen Brett R 
Published: May 2022

Abstract
Optic flow provides rich information about world-relative self-motion and is used by many animals to guide movement. For example, self-motion along linear, straight paths without eye movements, generates optic flow that radiates from a singularity that specifies the direction of travel (heading). Many neural models of optic flow processing contain heading detectors that are tuned to the position of the singularity, the design of which is informed by brain area MSTd of primate visual cortex that has been linked to heading perception. Such biologically inspired models could be useful for efficient self-motion estimation in robots, but existing systems are tailored to the limited scenario of linear self-motion and neglect sensitivity to self-motion along more natural curvilinear paths. The observer in this case experiences more complex motion patterns, the appearance of which depends on the radius of the curved path (path curvature) and the direction of gaze. Indeed, MSTd neurons have been shown to exhibit tuning to optic flow patterns other than radial expansion, a property that is rarely captured in neural models. We investigated in a computational model whether a population of MSTd-like sensors tuned to radial, spiral, ground, and other optic flow patterns could support the accurate estimation of parameters describing both linear and curvilinear self-motion. We used deep learning to decode self-motion parameters from the signals produced by the diverse population of MSTd-like units. We demonstrate that this system is capable of accurately estimating curvilinear path curvature, clockwise/counterclockwise sign, and gaze direction relative to the path tangent in both synthetic and naturalistic videos of simulated self-motion. Estimates remained stable over time while rapidly adapting to dynamic changes in the observer’s curvilinear self-motion. Our results show that coupled biologically inspired and artificial neural network systems hold promise as a solution for robust vision-based self-motion estimation in robots.
The roles of global warming and Arctic Oscillation in the winter 2020 extremes in East Asia
Authors: Kim So-Hee , Kryjov Vladimir N , Ahn Joong-Bae 
Published: May 2022

Abstract
The 2019/20 winter was extremely warm globally and in the Northern Hemisphere extratropics. The main cause of climate extremes particularly in East Asia, was the extreme positive Arctic Oscillation (AO) event superimposed on steady global warming. The negligible trend in the AO over the preceding 41 years makes it possible to distinguish the roles of AO and global warming in the observed extremes. We estimate and compare contributions to January–March 2020 climate extremes by the AO and global warming represented by local temperature trends using the ERA5 reanalysis data. Based on results from a preliminary study, we estimate the contribution by global warming using linear regression while that by the AO using cubic regression, which is more restrained for the high AO index values than linear. The results show that the temperature extremes were mainly caused by the extreme positive AO event which accounts for approximately 3/4 of the observed temperature anomalies in northern East Asia and 2/3 in eastern East Asia. In southern East Asia, the AO contributes negligibly and positive temperature anomalies are related to global warming and local and regional impacts, particularly extreme sea surface temperature, enhance south-westerlies and local radiative forcing. General conclusion is that the observed strong positive temperature anomalies including extreme anomalies over East Asia could have been achieved only as a combined effect of the extreme positive AO event and global warming. Quantification of the roles of the AO and global warming in climate extremes helps to estimate future anomalies caused by extreme AO events as well as assess uncertainties in climate model projections.
Enhanced monitoring of atmospheric methane from space over the Permian basin with hierarchical Bayesian inference
Authors: Roberts Clayton , Shorttle Oliver , Mandel Kaisey , Jones Matthew , Ijzermans Rutger , Hirst Bill , Jonathan Philip 
Published: May 2022

Abstract
Methane is a strong greenhouse gas, with a higher radiative forcing per unit mass and shorter atmospheric lifetime than carbon dioxide. The remote sensing of methane in regions of industrial activity is a key step toward the accurate monitoring of emissions that drive climate change. Whilst the TROPOspheric Monitoring Instrument (TROPOMI) on board the Sentinal-5P satellite is capable of providing daily global measurement of methane columns, data are often compromised by cloud cover. Here, we develop a statistical model which uses nitrogen dioxide concentration data from TROPOMI to efficiently predict values of methane columns, expanding the average daily spatial coverage of observations of the Permian basin from 16% to 88% in the year 2019. The addition of predicted methane abundances at locations where direct observations are not available will support inversion methods for estimating methane emission rates at shorter timescales than is currently possible.
Grassy–herbaceous land moderates regional climate effects on honey bee colonies in the Northcentral US
Authors: Quinlan Gabriela M , Sponsler Douglas , Gaines-Day Hannah R , McMinn-Sauder Harper B G , Otto Clint R V , Smart Autumn H , Colin Théotime , Gratton Claudio , Isaacs Rufus , Johnson Reed , Milbrath Meghan O , Grozinger Christina M 
Published: May 2022

Abstract
The lack of seasonally sustained floral resources (i.e. pollen and nectar) is considered a primary global threat to pollinator health. However, the ability to predict the abundance of flowering resources for pollinators based upon climate, weather, and land cover is difficult due to insufficient monitoring over adequate spatial and temporal scales. Here we use spatiotemporally distributed honey bee hive scales that continuously measure hive weights as a standardized method to assess nectar intake. We analyze late summer colony weight gain as the response variable in a random forest regression model to determine the importance of climate, weather, and land cover on honey bee colony productivity. Our random forest model predicted resource acquisition by honey bee colonies with 71% accuracy, highlighting the detrimental effects of warm, wet regions in the Northcentral United States on nectar intake, as well as the detrimental effect of years with high growing degree day accumulation. Our model also predicted that grassy–herbaceous natural land had a positive effect on the summer nectar flow and that large areas of natural grassy–herbaceous land around apiaries can moderate the detrimental effects of warm, wet climates. These patterns characterize multi-scale ecological processes that constrain the quantity and quality of pollinator nutritional resources. That is, broad climate conditions constrain regional floral communities, while land use and weather act to further modify the quantity and quality of pollinator nutritional resources. Observing such broad-scale trends demonstrates the potential for utilizing hive scales to monitor the effects of climate change on landscape-level floral resources for pollinators. The interaction of climate and land use also present an opportunity to manage for climate-resilient landscapes that support pollinators through abundant floral resources under climate change.
Operator spreading in the memory matrix formalism
Authors: McCulloch Ewan , von Keyserlingk C W 
Published: May 2022

Abstract
The spread and scrambling of quantum information is a topic of considerable current interest. Numerous studies suggest that quantum information evolves according to hydrodynamical equations of motion, even though it is a starkly different quantity to better-known hydrodynamical variables such as charge and energy. In this work we show that the well-known memory matrix formalism for traditional hydrodynamics can be applied, with relatively little modification, to the question of operator growth in many-body quantum systems. On a conceptual level, this shores up the connection between information scrambling and hydrodynamics. At a practical level, it provides a framework for calculating quantities related to operator growth like the butterfly velocity and front diffusion constant, and for understanding how these quantities are constrained by microscopic symmetries. We apply this formalism to calculate operator-hydrodynamical coefficients perturbatively in a family of Floquet models. Our formalism allows us to identify the processes affecting information transport that arise from the spatiotemporal symmetries of the model.
Responsive Design Approach towards the Sustainable Mosque Architecture
Authors: Syaheera Aziz Nurul , Sabrina Ismail Alice , Siraj Suhailah 
Published: May 2022

Abstract
This paper’s primary purpose is to design a sustainable mosque for communal development that adapts to the surrounding area. The National Mosque and The Mizan Mosque were selected as prominent case studies emphasizing the study of form and space. Thus, this study summaries new ways of describing mosque design, using structural and semiotic paradigms as a methodological approach to studying the relationship between mosque design and sustainable aspects. The guidelines developed from this study are helpful for designers, builders, developers and relevant authorities to build mosques as sustainable community development in the future.
Community Perception on ‘Third Place’ Generation and Planning for Enhanced Neighbourhood Interaction at Pengkalan Kubor, Malaysia
Authors: Iqmal Mohd Azamli Muhammad , Sabil Azmal , Abdul Rahim Asiah , Asif Nayeem , Ismail Jamail Maliza 
Published: May 2022

Abstract
Pengkalan Kubor at the east coast of Peninsular Malaysia is affected by limited neighbourhood interaction and liveability. A proper and good place is essential for neighbourhood interaction. There is a lack of places for social interaction, and the existing places are in poor condition and maintenance. This research aims to evaluate the impact of generating the “Third Place” to enhance neighbourhood interaction at Pengkalan Kubor. This paper seeks to identify the factors that obstruct neighbourhood interaction and evaluate the effectiveness of third place to resolve the neighbourhood interaction and improve the study context’s liveability. The questionnaire survey used for this research evaluates neighbourhood interaction. Since the study area is in Pengkalan Kubor, the respondents selected for this study were within the community. In addition to defining the neighbourhood, the survey defined the third places within the study context. The findings from the public perception of neighbourhood interaction and third place at Pengkalan Kubor may be useful for many stakeholders for public places’ future planning.
Economic Model of Green Building Construction: A Conceptual Model
Authors: Ahmad Zaini Afzan , Khairina Khairul Hisham Nur , Rashid Abdul Aziz Abdul , Nadia Abd Aziz Nurul 
Published: May 2022

Abstract
The current research shows that green building received inadequate support from industry parties due to its high up-front cost. There are no existing guidelines focussing on how to minimize the issues of high up-front cost and for that reason, not all clients willing to get involved in green building construction. Hence, to increase their interest in investing in the green building, this research aims at formulating an economic model of green building construction using Structural Equation Modelling (SEM). The objectives of this research are to identify the green buildings elements, examine the most expensive elements, recommend the strategies in minimizing the cost of green building construction and to formulate and validate an economic model of green building construction. The model is one of the strategies to minimize the total cost, increase the client’s interest to invest in green building as well as facilitate construction stakeholders from inception to completion stage; in line with the Twelve Malaysia Plan “Economic Empowerment and Environmental Sustainability”.
A systematic review of studies examining the relationship between resilience and physical asset management for water system
Authors: Rozman AT , Jiram W R A , Rahman M S A , Ismail A , Azmi N A 
Published: May 2022

Abstract
The resilience in the water system can produce great benefits; one of the ideal ways to achieve resilience is through asset management. The purpose of this study is to systematically review the literature that presents the relationship between asset management and resilience. We searched multiple databases such as Emerald Insight, Sage Publication, Science Direct, Scopus, Taylor and Francis, and Wiley Online Library ranging from the year 2000 until the year 2020. The papers are written in English. A total of 7845 articles have been successfully identified and only 6 papers met the inclusion criteria of the study. The study has concluded that most of the previous research that discusses asset management and resilience are in groups dating 5 years back (2015-2019). Several features of physical asset management require further investigation that can enhance the resilience of the water system. The topic is relatively new and hopes to open a huge gap for research.
Reliability of 15-minute drone footage volume for estimating urban traffic flow rates: A preliminary study
Authors: Abdullah M S , Sanik M E , Mat Nor A H , Salim S , Abdul Malek K Z , Razali N F , Mohd Nasir A Z 
Published: May 2022

Abstract
This study discusses the reliability of 15-minute data collection from the drone footage as an alternative for conventional 1-hour data collection for traffic analysis. The selected study locations are five urban intersections along Jalan Bakri, Muar, Johor. The 12-hour data was obtained from a manual commuter counting to identify the peak hour along Jalan Bakri. Based on the time series analysis, the peak hour was identified which is from 5.30 to 6.30 p.m. with a peak hour factor of 0.94. The actual flow rate during peak hour and the volume from 15-minute drone footage multiply by 4 and peak hour factor value were compared using the t-test. The P-value obtained is 0.732 which is greater than 0.05 for 95 percent confidence Therefore, the difference between the means is not statistically significant. In summary, there is evident to prove that the outcome from the drone footage data during the peakiest 15-minute interval has no significant difference with the outcome from 1-hour data collection during peak hour. This verification result shows that the 15-minute data collection during peak hour can be applied to facilitate the intersection performance analysis besides can enhance the use of drone in traffic study.
Numerical analysis of embankment resting on floating bottom ash columns improved soft soil
Authors: Abbil A , Kassim A , Ullah A , Rashid A S A , Roshan M. J. 
Published: May 2022

Abstract
The construction of embankment over soft clay is quite a challenging job for the geotechnical engineer, which may results in a large settlement, bearing failure and stability issues. Stone columns can be used to minimize the settlement and increase the bearing capacity in such conditions. This study was carried out to investigate the behaviour of bottom ash columns underneath embankments using numerical modelling. The soft soil improved with bottom ash columns under the embankment subjected to traffic-induced loading was simulated in Plaxis 3D foundation software. The study variables include three area replacement ratios (Ar) of 10%, 15% and 20% and two columns length of 5m and 7.5m. The results indicated that enlarging the Ar and length of columns significantly reduced the final settlement and consolidation time. The maximum settlement reduction of 58% was reported for the Ar of 20% with 7.5m column depth. The study suggests that bottom ash columns can be used to improve soft soil underneath the embankment.
Investigating the Properties of Asphalt Mixes Containing Recycled Polyethylene Terephthalate Fiber
Authors: Aman M Y , Taher M N M , Shahadan Z , Rohani M M , Daniel D B 
Published: May 2022

Abstract
A large volume of traffic loading on asphalt pavement at high temperature frequently resulted in pavement deterioration due to reduction in strength and loss of structural integrity. This paper presents the effects of recycled polyethylene terephthalate fiber used in the ranges of 1.18 mm to 2.36 mm prepared for 0%, 0.5% and 1.0% by the weight of mineral aggregates. Conventional bitumen 60/70 penetration grade was used as the base binder. The compacted specimens were tested for dynamic creep, resilient modulus and resistance to rutting. It was found that the creep stiffness specimens prepared with 0.5% recycled polyethylene terephthalate fiber tested at 1800 and 3600 load cycles has increased by 11.7% and 23.8%, moreover permanent deformation has reduced by 8.7% and 8.4%, respectively. Furthermore, specimens containing 0.5% recycled polyethylene terephthalate fiber also has increased the resilient modulus by 10.0% and 55.1% while the rutting values decreased by 13.7% and 13.9%, correspondingly. Interestingly, specimens containing 0.5% recycled polyethylene terephthalate fiber exhibits higher mixes stiffness, low rutting and permanent deformation irrespective of test temperature. It can be concluded that specimen containing 0.5% recycled polyethylene terephthalate fiber contributes higher resistance to rutting, promotes better performance compared to conventional mix.