Miracle-dz/UniFAR-FTUs huggingface dataset:
Estimating the ride quality characteristics of vehicles with random decrement analysis of on-the-road vibration response data

ABSTRACT This paper describes the application of a practical analytical technique based on the random decrement method to estimate the rigid sprung mass dynamic characteristics (frequency response function) of road vehicles using only vibration response data during constant-speed operation. A brief history and development of the random decrement technique is presented, along with a summary of work undertaken on optimal parameter selection to establish the random decrement signature. Two approaches to estimate the dynamic characteristics from the random decrement signature are described and evaluated. A custom, single-wheeled vehicle (physical quarter car) was commissioned to undertake a series of on-the-road experiments at various nominally constant operating speeds. The vehicle, also instrumented as an inertial profilometer, simultaneously measured the longitudinal pavement profile to establish the vehicle's actual dynamic characteristics during operation. The main outcome of the paper is that the random decrement technique can be used to provide accurate estimates of the sprung mass mode of the vehicle's dynamic characteristics for both linear and nonlinear suspension systems of an idealised vehicle.
The complete chloroplast genome of Ficus pumila, a functional plant in East Asia

Abstract Ficus pumila L. is a climbing fig commonly used as an ornamental plant. In this study, we sequenced and assembled the complete chloroplast genome of F. pumila. The complete chloroplast genome of F. pumila is 160,248 bp in length which includes a pair of inverted repeats (IRs) of 25,871 bp separated by a large single-copy (LSC) region of 88,405 bp and a small single-copy (SSC) region of 20,101 bp. The overall guanine–cytosine (GC) content of F. pumila cp genome is 35.98%, while the corresponding values of LSC, SSC, and IR sequences are 33.65, 29.05, and 42.65%, respectively. The phylogenetic tree was shown to be consistent with the traditional morphology-based taxonomy of Moraceae. Five plants from the genus Ficus formed a well-supported monophyletic clade with 100% bootstrap value, and F. pumila is closely related to F. hirta, F. carica, and F. racemosa, with a support value of 97%. The complete chloroplast of F. pumila contributes to the growing number of chloroplast genomes for phylogenetic and evolutionary studies in Moraceae.
Addressing complex state constraints in the integral barrier Lyapunov function-based adaptive tracking control

For the state-constrained control problem with complex constrained regions, this paper presents an Integral Barrier Lyapunov Function-based adaptive backstepping scheme for the tracking control. The Barrier Lyapunov Function approach provides an effective tool to embed the barrier terms into the Lyapunov function, enabling the integration of barrier avoidance and closed-loop stabilisation. In the literature, previous works in the area of Barrier Lyapunov Function mostly considered a simple hyperrectangle shape of the constrained region. In this study, the complex barrier region is for the first time introduced to the Barrier Lyapunov Function framework. A novel recursive design procedure is constructed for a class of uncertain nonlinear parametric systems, ensuring the closed-loop signals are all bounded and the tracking errors are convergent. Finally, the proposed method is applied to a numerical example, illustrating the efficacy of this work.
Environmental impacts of construction material production

Buildings are crucial to the development of a city and the well-being of its citizens. When designing a building facility, it is imperative to minimise the environmental burdens caused by buildings, particularly in terms of natural resource consumption as well as pollutants and waste generation due to the use of construction materials. Despite that, it is difficult for decision makers to ascertain the environmental impacts embedded in or emitted from new buildings, as there is no agreed upon approach to assess the environmental impacts of construction materials. In this paper, a midpoint life cycle impact assessment method is employed to assess the environmental impacts of construction materials. Four institutional buildings in Hong Kong that serve different social functions are examined. The type and the amount of materials used in those projects along with their environmental impacts are delineated. The results reveal that steel reinforcement, aluminium, copper, ceramic tile and concrete are the five mo.
Novel approach for the study of coherent elastic neutrino-nucleus scattering

We propose the use of isotopically highly enriched detectors for the precise study of coherentelastic neutrino-nucleus scattering (CEvNS). CEvNS has been measured for the first time in CsI and recently confirmed with a liquid argon detector. It is expected that several new experimental setups will measure this process with increasing accuracy. Taking Ge detectors as a working example, we demonstrate that a combination of different isotopes is an excellent option to do precision neutrino physics with CEvNS, test Standard Model predictions, and probe new physics scenarios. Experiments based on this new idea can make simultaneous differential CEvNS measurements with detectors of different isotopic composition. Particular combination of observables could be used to cancel systematic errors. While many applications are possible, we illustrate the idea with three examples: testing the dominant quadratic dependence on the number of neutrons, N , that is predicted by the theoretical models; constraining the average neutron root mean square (rms) radius; and testing the weak mixing angle and the sensitivity to new physics. In all three cases we find that the extra sensitivity provided by this method will potentially allow high-precision robust measurements with CEvNS and particularly, will resolve the characteristic degeneracies appearing in new physics scenarios.
The Virtual Laboratory to Achieve Dynamic Simulation Using Proteus

Proteus is a kind of powerful EDA simulation software,whose simulating device library has an incomparable advan-tage over other simulation software on the dynamic simulation of the electronic devices,and the virtual instrument brings great conve-nience to the simulation test.This paper,taking the simulation of SCM of 89C51 for example,analyzes the unique function of Proteus in the simulation of micro processors and shows its application outlook in various fields.
An analysis of public opinions regarding Internet-famous food: a 2016–2019 case study on Dianping

PurposeInternet-famous food (also known as “online celebrity” food) is very popular in the digital age. This study aims to investigate consumer attitudes and understand consumer behavior towards Internet-famous food.Design/methodology/approachThe authors collected 136,835 online comments regarding “Internet-famous food” from Dianping platform between 2016 and 2019 using a web scraper. A sentiment lexicon for Internet-famous food was constructed, and sentiment analysis is further conducted to understand consumer attitudes. Additionally, the authors use topic analysis and time series analysis to study consumer behavior.FindingsSentiment analysis showed that the number of consumers' comments decreased over time with the attitudes being overall positive, and the Internet-famous food industry has a positive prospect; time series analysis showed that the consumption of Internet-famous food was not affected by the season; topic analysis showed that consumers' comments on Internet-famous food were rich with a large variety, covering food categories, brand, quality, service, environment and price.Originality/valueTo the authors’ knowledge, limited research has focused on public opinions regarding “Internet-famous food”. This is the first study on consumer behavior towards Internet-famous food. This article provides a unique insight into the purchasing behavior and attitude of Chinese Internet-famous food consumers through text mining.
MEASURING YOUTH PERCEPTIONS IN THE DIRECTION OF BRANDS ON DIGITAL MEDIA USING NETNOGRAPHY

This study explores and observe the motivations of youth in digital culture which influence them to follow and interact with brands on digital media through netnography. This technique tries to adopt patron notion of youth in digital culture which influence them for youth follow brands official pages for the purpose of being up to date with brands offerings for purchase and repurchase. This studies cram changed into qualitative in nature, primary and secondary source of codes selected examined and interpreted. The data by using structured interviews (open- ended questionnaire) has been supported by relevant secondary literature that will support for conducting qualitative research based on netnography. The online digital media in Pakistan Karachi has on its significance, it’s evolving everyday but with quite difficulties like time comments youth targeted food brands pages were found to be highly interactive, quite extensive amount of likes and even comments were seen on various posts. Comments included people suggesting others for the products and deals, also people actively shared their feedbacks for the products. This studies study thoughtful beneath the parameters of online digital media, changing time era and great supported belongings writer controlled to provide a reason behind the comprehensive functionality of the study. Keywords: youth, digital culture, social media platform, qualitative research, Netnography
Packet Scheduling Algorithm Considering Maximum Delay Tolerance for HSDPA System

In this paper, we consider a new packet scheduling algorithm for real-time traffic in the HSDPA system that has been introduced for the WCDMA system, in order to provide high transmission rates. The objective of the design is to meet the maximum tolerable delay and consider channel assignment based on the received SIR for real-time traffic users. The proposed scheduling algorithm shows that the users are ranked by the ratios of the bits in the buffer to the residual time for transmission as priority order; then the ranked users are assigned certain number of channels based on the SIR value table. The simulation results show that the proposed algorithm can provide a lower packet drop rate, and satisfy real time quality of service (QoS) requirements.
Single image reflection removal using meta-learning

Abstract. In recent years, reflection is a kind of noise in images that is frequently generated by reflections from windows, glasses, and so on, when you take pictures or movies. The reflection does not only degrade the image quality but also affects computer vision tasks, such as the accuracy of object detection and segmentation. In the task of single image reflection removal (SIRR), deep learning models play a key role for solving the problems of various patterns and the versatility. The challenge of SIRR is the influence of image quality and low precision of the method. We propose a deep learning model for the task of SIRR. The assumed scenes of reflection are varying, and there is little training data because it is difficult to obtain true values. We focus on the latter and propose an SIRR based on meta-learning. We adopt model agnostic meta-learning (MAML), and we propose an SIRR using a deep learning model with MAML, both of which are methods of meta-learning. The deep learning model includes the iterative boost convolutional long short-term memory network, which is adopted as the deep learning model. Experimental results show that the proposed method improves accuracy compared with conventional state-of-the-art methods.
Visual Localization and Mapping Leveraging the Constraints of Local Ground Manifolds

In order to improve the accuracy of simultaneous localization and mapping problem, plane motion assumption is often used for advanced ground vehicle SLAM system. However, such an assumption is not always suitable to complex and changable road scenes. In this paper, we propose a stereo-vision SLAM framework that tightly couples the local ground manifold constraints into accurate camera trajectory estimation. Instead of considering a planar manifold assumption, we model the road as a sequence of local planes with different slopes named local ground manifolds (LGM). The impact region of the LGM is represented as a spherical area in the map, where the vehicles motion is constrained by the corresponding local plane model. ORB features and road segmentations are utilized to perform the environmental reconstruction and ground manifold representation. The structures of surroundings and the plane normals of LGMs are jointly optimized with the trajectory of the vehicle within a novel point-LGM tightly-coupled bundle adjustment framework. The experiments on KITTI datasets demonstrate that the proposed ground manifold representation can greatly benifit the camera trajectory estimation.
Battle of the water networks ii: Combining engineering judgement with genetic algorithm optimisation

This paper details a proposed solution for the Battle of the Water Networks II problem, in which a large scale water distribution system is to be optimised considering the objectives of economic costs, GHG emissions and water age. The proposed method of optimisation uses a combination engineering judgement and the use of an optimisation algorithm. An advance multi-objective genetic algorithm, NSGA-II is used to optimise both the network design and operational management. A multi-objective optimisation algorithm outputs multiple optimal solutions which represent a tradeoff between the objectives being optimised for. As such, a single final solution is selected using engineering judgement and a weighted sum method. From the optimisation process, seven different optimal network designs and 511 optimal operational management scenarios are found. The final solution, chosen from these optimal solutions, has an annualized total cost of $1.0M, annualized GHG emissions of 3620 tonnes CO2-e and a water age of 0.12 hours.
Decision Making and Risk Propensity in Individuals with Tendencies towards Specific Internet-Use Disorders

The uncontrolled use of specific Internet applications is increasingly recognized as a mental health issue. Gaming disorder, which is one subtype of specific Internet-use disorders (sIUDs), has been included in the ICD-11 as disorder due to addictive behaviors. Addictive disorders are assumed to be accompanied by cognitive deficits as indicated by weaker performance in executive function and risky decision-making tasks. This study investigates risky decision-making in individuals with tendencies towards sIUDs including gaming, online buying-shopping, and social-networks-use disorders. A total of 293 individuals participated in the study. Based on specific screening instruments, the participants were assigned to a group with tendencies towards sIUD or a control group. Participants completed a risky decision-making task and questionnaires assessing risk-taking propensity, impulsivity, psychopathology, and perceived stress. The group with sIUD tendencies showed higher attentional impulsivity and higher levels of depression and anxiety compared to the control group. The groups did not differ in decision making and risk propensity. Decision making did not have significant effects on sIUD symptoms. Risk for developing sIUDs does not appear to be accompanied by altered general decision-making tendencies. Rather, psychological (pre-)load and attentional deficits appear to be relevant features in uncontrolled use of the Internet.
Late-Holocene vegetation and fire history in Western Putorana Plateau (subarctic Siberia, Russia)

We present a reconstruction of vegetation dynamics and fire history from the western part of the Putorana Plateau during the Late-Holocene. The study area is located in the remote and poorly investigated region of Central Siberia, which represents an important area for understanding climate and environmental changes in the Russian Subarctic. Pollen and macroscopic charcoal data from three closely located lakes along an altitudinal transect in the Khantaika River basin show no major changes in vegetation in the study area during the last 3.9 ka BP. However, a detailed analysis of the data reveals an extension of forest coverage in lake catchments at about 3.1 ka BP followed by a gradual degradation of woodlands, and an expansion of shrubs and tundra vegetation at around 2.7–2.5 ka BP. Fire activity was relatively high between 3.0 and 2.0 ka BP compared to all but the most modern part of the record, while macroscopic charcoal accumulation reaches a maximum in the most recent surface sediments. This suggests an increase in the frequency and area of fires in the region since the end of the 19th century, which has no analog during the Late-Holocene.
An intervention to facilitate 'high quality' physical education - from gymnastics to athletics

The summer edition of Research Matters included a short article on facilitating ‘high quality’ physical education and ‘high quality’ gymnastics in a city school (see Cale et al., 2011). The article provided a summary of the first phase of a research project which aimed to: i) facilitate high quality teaching and learning in physical education, and ii) identify key principles that contribute to high quality outcomes and which could be applied across the physical education curriculum. This article follows on and presents a summary of phase 2 of the research, which focused on athletics, as well as of the key findings and recommendations from the project overall.
Study on Spot Welding Quality Monitoring Models by Linear Regression Theory

By means of linear regression analysis technique,the single regression model and multiple regression model between dynamic resistance information in spot welding process of mild steel and quality parameters are studied systematically.Results show as follows: (1) The total linear relations of all models are obvious by statistic test,which shows that the regression models can be used for monitoring and controlling spot weld quality. (2) The determination coefficients of the single regression model are only from 0.15 to 0.33,and the determination coefficients of the multiple regression model can be raised from 0.59 to 0.79,which show that developing multi variable synthetical monitor is an effective way to raise monitoring accuracy. (3) The relations between monitoring information and quality factors are substantially non linear,it will make model more error to describe such relations by linear model.
MTM Parameters Optimization for 64-FFT Cognitive Radio Spectrum Sensing using Monte Carlo Simulation

This paper presents parameter optimization of the multi taper spectrum estimation method (MTM) for 64-FFT based cognitive radio (CR) spectrum sensing. The design problem is formulated to determine the MTM parameters pair; the half time bandwidth product, and the number of tapers that maximize the performance at a fixed number of data samples. Maximum performance is defined by the highest probability of detection at a fixed false alarm probability. A Monte Carlo simulation is implemented to find the optimal parameters. The binary hypothesis test is developed to insure that the effect of choosing optimum MTM parameters is based upon performance evaluation. The whole band under sensing is divided into subbands, some contain primary user signal (PR), and the other does not. Consequentially, in addition to the variance of the estimate, the spectral leakage outside the PR subband is included in the performance evaluation. We found that the half time bandwidth product of 4 and 5 tapers gives the highest performance. We examined both MTM and periodogram (i.e., energy detector) methods in Gaussian (AWGN) and Rayleigh flat fading environments. The CR system performance using the MTM technique outperforms the performance of the same system that uses periodogram in all the cases we examined. Keywords-cognitive radio; spectrum sensing; multitaper spectrum estimation. I. INTRODUCTION High data rate applications in the emerging wireless technologies are faced with the problem of the ever-increasing scarcity of spectrum, coupled with the underutilization of the current licensed spectrum. Cognitive radio's basic idea is the opportunistic use of the unused spectrum of a licensed PR user. Consequently, CR technology is expected to become an increasingly popular part of future wireless networking technologies.
CHARACTERIZING IMAGE CLASSIFICATION DIFFICULTIES THROUGH REDUCED-DIMENSION CLASS CONVEX HULL ANALYSIS

The classiﬁcation of natural terrain ahead of an autonomous rover can help it make decisions regarding the traversability of various paths, but remains an open research problem. Recent promise shown by deep learning algorithms in general image classi-ﬁcation has seeded research aimed at transferring these successes to visual terrain classiﬁcation. Despite the popularity of deep learning networks, there is still little work available on informed neural network design procedures for speciﬁc tasks such as terrain image classiﬁcation. This work presents an algorithm that can be used to quantify the difﬁculty of speciﬁc image classiﬁcation tasks and to investigate the characteristics of particular difﬁculties and trends in a way that is interpretable by humans. An accompanying analytical procedure characterizes such image clas-siﬁcation difﬁculties; identifying what makes some images easily distinguishable exemplars of their class and what makes others readily confused with other classes.
3D stability analysis of landslides based on strength reduction (II): evaluation of reinforcing factor of safety

Taking the No. 1 landslide at Hongjiadu Hydroelectric Project for example, a 3D stability analysis method is discussed for landslides with known slip surface. Firstly simulation is made for its sliding directions and calculation is completed for its three-dimensional factor of safety by a stress-based method, assuming the landslide is in critical state under natural conditions; secondly a method is proposed for its 3D evaluation of reinforcing factor of safety, which is based on the strength reduction technique; and finally measures are proposed for further optimizing the reinforcing design. Results show that sliding directions are nearly perpendicular to the local contour lines; the major sliding direction changes drastically from NE15? in the rear to NS in the middle, and finally to NE30? in the tongue, making it difficult to draw a longitudinal geological profile, which can represent the major sliding directions. The stress-based method can neither fully utilize the anti-sliding potentials of the slide, nor represent its overall sliding directions, leading to over-estimation of its factor of safety. The proposed method, having the merits of finite element method, etc., can overcome the above drawbacks and rationally evaluate its reinforcing factor of safety.
Website Quality in Asia: Testing a Measurement Instrument in a Chinese Context

In this study we investigate the psychometric properties of a Chinese version of a perceived website quality (PWQ) measurement instrument. The results of our study confirmed the four-factor structure of the scale scores and that the scale has good internal consistency. CFA results support the convergent and discriminant validity of the scales scores for the first factor measurement model. Our findings also showed that a single higher-order factor accounts for the variance among the four lower-order factors. In view of its sound psychometric properties, the Chinese version of the PWQ scale is a useful instrument to evaluate website quality in a Chinese context