bluuebunny/crossref_metadata_2025 huggingface dataset:
Observations on the behaviour and ecology of the Common Wombat Vombatus ursinus in northeast Tasmania.
Authors: Taylor R.J.
Published: September 2021

Aspects of the behaviour and ecology of Vombatus ursinus were studied in largely cleared agricultural land in a coastal area in northeast Tasmania. The average density of V. ursinus was 20 individuals.km-2 over the whole study area but around 60.km-2 in an intensively studied section. Burrows were concentrated in areas of sandy soil where a dense cover of native vegetation had been maintained. Only short, shallow burrows were present in areas of dolerite, probably because of the difficulty of digging. Home-ranges of different individuals overlapped. Wombats were not active continually through the night and varied in time of emergence from their burrow and the time spent above ground. Often more than one burrow was used on the same night, with more than one individual making use of a burrow, but usually not at the same time. Disputes over the use of burrows occurred. Individuals frequently sniffed around burrows and investigated for the presence of occupants. Males may use this as a strategy for finding females in oestrus. Mating behaviour was observed once. Wombats are solitary and actively avoid the presence of others.
Odour in faecal pellets and from scent marking probably plays an important social role by providing
information on the individuals sharing a home-range and the occurrence of strangers. Dominant animals
may be intolerant of the presence of certain individuals within their home-range.
Observations on the behaviour of the Rufous Hare-wallaby, Lagorchestes hirsutus Gould (Macropodidae: Marsupialia) in captivity.
Authors: Lundie-Jenkins G.
Published: September 2021

Observations on the behaviour of the Rufous Hare-wallaby Lagorchestes hirsutus were obtained from a captive colony maintained in Alice Springs. This information was used to interpret observations of animals made during field studies in the Tanami Desert. Aspects of the species' behavioural repertoire which were recorded included activity patterns, postures, gaits, interactions, nesting habits and vocalisations. Lagorchestes hirsutus is predominantly nocturnal and its activity patterns and body postures resemble those recorded for other species of small macropods. It appears to be a relatively solitary animal but there was some evidence of social organisation within animals maintained in captivity. Aspects of the sexual and aggressive behaviour of L. hirsutus appear to resemble more closely those of the potoroids than of larger macropodids.
The hairy-footed dunnart Sminthopsis hirtipes (Marsupialia: Dasyuridae) in Queensland.
Authors: Dickman C.R. , Downey F.J. , Predavec M.
Published: September 2021

NA
Copulation and associated behaviour in the rufous hare-wallaby (Lagorchestes hirsutus)
Authors: McLean I.G. , Lundie-Jenkins G. , Jarman P.J. , Kean L.E.
Published: September 2021

NA
Skin lesions in two preserved thylacines, Thylacinus cynocephalus.
Authors: McOrist S. , Kitchener A.C. , Obendorf D.L.
Published: September 2021

NA
Dietary preference of koalas, Phascolarctos cinereus (Marsupialia: Phascolarctidae) for Eucalyptus spp. with a specific reference to their simple sugar contents.
Authors: Osawa R.
Published: September 2021

NA
Book Review: Daniel Lunney (Ed), 1992. Conservation Of Australia's Forest Fauna. Royal Zoological Society Of New South Wales: Mosman
Authors: Braithwaite W.
Published: September 2021

NA
Vocalisations of adult Northern Quolls, Dasyurus hallucatus.
Authors: Dempster E.R.
Published: September 2021

Vocalisations of Northern Quolls, Dasyurus hallucatus, were recorded during staged interactions between pairs of the same sex and different sexes. Four types of vocalisations were identified: 'hisses', 'sniffs', 'squawks' and 'twitters'. No pure ultrasonic calls were identified, although frequencies of twitters and sniffs extended into the ultrasonic range. All vocalisations were broadband, noisy sounds, with little evidence of harmonic structure or frequency modulation. Vocalisations of D. hallucatus are compared with data for other dasyurid species, and the correlation between frequencies of vocalisations and maximum sensitivity of the brain auditory pathway is discussed.
The status and seasonal occurrence of Leopard Seals, Hydrurga leptonyx, in Tasmanian waters.
Authors: Rounsevell D. , Pemberton D.
Published: September 2021

Seventy nine sightings of Leopard Seals, Hydrurga leptonyx, made over a period of 7 years in Tasmania are reported. They show that the species occurs annually in Tasmanian waters between July and November, probably as a result of northward movement from the Antarctic pack ice zone. Its seasonal occurrence in Tasmanian waters implies that it is a regular member of the marine fauna of the region. This is in contrast to previous reports that the species was a rare vagrant, occasionally stranding along the coastline. Comparisons of the age structure of H. leptonyx in Tasmania with those on subantarctic islands suggests that there is a clinal variation with latitude in the dispersal pattern, as young animals disperse further north than adults.
An overview of the localisation of video games into Arabic
Authors: Goaid Alotaibi Abdullah , Tuhaitah Zafer
Published: September 2021

With the emergence of video game localisation studies in the last decade, scholarly interest in translation studies in this young discipline has increased. Although globalisation has encouraged video game companies to offer their products in as many languages and markets as feasible, this academic discipline is still an under-researched area, especially in the Arab context. This article presents an overview to engender a better understanding of the nature of video games and their localisation in the Arab market. This market is distinct due to its culture, politics and language. In addition to the translational challenges related to the Arabic language, this study deals with the specificities of video game localisation from political, cultural and linguistic perspectives. This research offers a historical overview of the localisation of video games into Arabic since the inception of the practice, including an outline of the main localisation milestones in this field.
Comparison of the Josephson voltage standards of the MIKES and the BIPM
Authors: Solve Stephane , Chayramy Regis , Immonen Pekkra , Nissilä Jaani , Stock Michael , Manninen Antti
Published: September 2021

Main text

As part of the ongoing BIPM key comparison BIPM.EM-K10.b, a direct comparison of the Josephson array voltage standards of the Bureau International des Poids et Mesures (BIPM) and the National Metrology Institute of Finland (VTT MIKES), Espoo, Finland, was carried out in October 2019 at the level of 10 V. For this exercise, the option A of the BIPM.EM-K10.b comparison protocol was partially applied. Option A required the MIKES to provide a reference voltage with its Josephson voltage standard for measurement by the BIPM using an analogue nanovoltmeter and associated measurement cables. Since no sufficiently stable voltage could be achieved in this configuration, a digital detector was used instead. In all cases the BIPM array was kept floating from ground.

The final results were in good agreement within the combined relative standard uncertainty of 2.5 parts in 1010 for the nominal voltage of 10 V.

To reach the main text of this paper, click on Final Report. Note that this text is that which appears in Appendix B of the BIPM key comparison database https://www.bipm.org/kcdb/.

The final report has been peer-reviewed and approved for publication by the CCEM, according to the provisions of the CIPM Mutual Recognition Arrangement (CIPM MRA).
Efficient flexible characterization of quantum processors with nested error models
Authors: Nielsen Erik , Rudinger Kenneth , Proctor Timothy , Young Kevin , Blume-Kohout Robin
Published: September 2021

We present a simple and powerful technique for finding a good error model for a quantum processor. The technique iteratively tests a nested sequence of models against data obtained from the processor, and keeps track of the best-fit model and its wildcard error (a metric of the amount of unmodeled error) at each step. Each best-fit model, along with a quantification of its unmodeled error, constitutes a characterization of the processor. We explain how quantum processor models can be compared with experimental data and to each other. We demonstrate the technique by using it to characterize a simulated noisy two-qubit processor.
Influence of elongation and triangularity on plasma response to resonant magnetic perturbations
Authors: Yang Xu , Liu Yueqiang , Xu Wei , He Yuling , Lu Shuangshuang
Published: September 2021

Systematic toroidal modeling of the plasma response to the n = 1–4 (n is the toroidal mode number) resonant magnetic perturbation (RMP) field is carried out in order to understand the plasma-shaping effect on controlling the type-I edge-localized modes (ELMs) in tokamak experiments. Considered are large variations of the plasma elongation and triangularity at a fixed edge safety factor q
a, for limiter plasmas with both single-null (SN) and double-null (DN) divertor-like boundary shapes. Numerical results assuming conformal 3D RMP coils show that (i) the optimum coil phasing between the upper and lower rows for ELM control becomes increasingly sensitive to the plasma elongation with higher-n toroidal spectra, (ii) the optimum coil phasing is however essentially independent of the plasma triangularity for all n = 1–4 RMP fields, (iii) with the same coil current and the optimum coil phasing, high elongation generally favors ELM control but it may be more challenging for plasmas with intermediate elongation and with lower-n (n = 1–2) RMPs, and (iv) higher triangularity is generally always better for ELM control with all n = 1–4 fields for both DN and SN divertor-like plasma boundary shapes.
Computational ghost imaging with the sweeping algorithm
Authors: Adam I A , Gellert M E , Chernykh A V , Nasedkin B A
Published: September 2021

The idea of ghost imaging was firstly presented more than 25 years ago and since then many techniques have been proposed to improve image quality and simplify optical scheme. Nevertheless, the image reconstruction speed has always remained a serious problem to wide practical implementations. As a solution, a sweeping algorithm was proposed, which allowed to reduce the number of iterations to image resolution. However, this method has some serious limitations on objects shape. In this article we present a new technique, which combine a sweeping algorithm using alternating rows/columns and traditional pseudothermal ghost imaging using speckle structures.
Integrated optical RF intensity modulators transfer function traits
Authors: Gerasimenko V S , Gerasimenko N D , Petrov V M
Published: September 2021

The most common integrated optical intensity modulators are made according to the Mach-Zehnder interferometer scheme. It leads to specific interconnection between the interferometer arms phase difference and the output spectrum. The description and the experimental demonstration of this traits are presented.
Dynamics of field observables in quantum channels
Authors: Medvedeva S , Gaidash A , Kozubov A , Miroshnichenko G
Published: September 2021

We consider the time evolution of the mean values of the quadrature operators’ observables and the dynamics of the mean photon number variance for an arbitrary quantum state in a single mode transmitted through an optical fiber channel. Utilizing the density matrix formalism and the quantum optics theory we derive expressions for the dynamics of mentioned field observables for such prominent quantum states as squeezed vacuum state, squeezed coherent state and superposition of coherent states.
Generation of frequency harmonics for QKD systems at subcarrier waves
Authors: Gerasimenko N D , Gerasimenko V S , Petrov V M
Published: September 2021

This paper demonstrates the efficiency of using optical feedback without amplifiers to generate subcarrier waves in the microwave phase modulator output spectrum for quantum communications. It is proposed ideas for expanding the functionality of quantum communication systems and communication systems using DWDM standarts.
Population density gratings creation and control in resonant medium by half-cycle terahertz pulses
Authors: Arkhipov R M , Arkhipov M V , Pakhomov A V , Babushkin I , Demircan A , Morgner U , Rosanov N N
Published: September 2021

Electromagnetically induced gratings (EIG) are created by standing-wave laser field in resonant media. Such gratings can be also created by few-cycle electromagnetic pulses counter-propagating in the medium via coherent Rabi oscillations of atomic inversion. In this case, instantaneous cross-section of the pulses in the medium is not necessary for grating formation. In this paper, we revise our recent results in study of such grating formation and their control by few-cycle pulses coherently propagating in a resonant medium. We demonstrate the grating formation and their control in three-level medium excited by three subcycle THz pulses.
Assessment of diatom growth using fluorescence imaging
Authors: Cvjetinovic J , Nozdriukhin D V , Bedoshvili Y D , Salimon A I , Korsunsky A M , Gorin D A
Published: September 2021

Monitoring the growth of diatom microalgae requires sensitive, fast, and easy-to-use methods for selecting the most productive strains for further research and application. Here we propose a novel, rapid and non-destructive approach for monitoring the viability and growth of diatom colonies using the IVIS fluorescence imaging system. The fast-growing Achnanthidium sibiricum diatoms were cultivated in favorable laboratory conditions in a specially designed bioincubator for 100 days. The results showed that the diatoms reached the end of the exponential growth phase after 56 days of culture, after which there was a slight decrease in fluorescence intensity. This method relies on using chlorophyll a fluorescence without any sample preparation and has proved to be successful for monitoring algae growth in an incubator during long-term batch cultivation. This result paves the way towards controlled diatom cultivation aimed at collecting diatom-derived bioactive compounds for various purposes.
Comparison study of Surface-enhanced Raman spectroscopy substrates
Authors: Khnykina K A , Baranov M A , Babaev A A , Dubavik A Y , Fedorov A V , Baranov A V , Bogdanov K V
Published: September 2021

Different parameters are used when comparing SERS substrates in the research of most scientific groups. These parameters are more often aimed at comparing theory and experiment. We described experimental models for comparison and explain their applicability. In this work, a reaction mixture volume fixing technique was chosen when comparing different substrates. The intensity distribution maps with an area of 2025 μm2(9X9 points) were recorded and described. We successfully used the parameters average intensity of intensity distribution maps and percentage gate of intensity distribution maps for comparison of enhancing substrate. We have observed uniform enhancing across the entire surface of self-assembled plasmonic film. A comparative study has shown that the self-assembled plasmonic film sample has high enhancing factors and good reproducibility of factors over the studying sample surface. Average intensity of dropcasted colloidal gold nanoparticles (Au-NPs) sample is equal to 1860 counts and percentage gate of intensity data equals 125%. Average intensity of self-assembling plasmonic film is equal to 112000 counts and percentage gate equals 1,67%.
A set of multifunctional equipment for deposition of colloidal photonic crystal films and monolayers
Authors: Dyubanov V A , Ibragimov A R , Panfilova E V
Published: September 2021

It is impossible to obtain colloidal photonic crystal film of given properties without special equipment. In order to minimize the influence of external disturbing influences such devices should be automated. To obtain large-area or hetero structures it is rational to combine in one universal device equipment for the implementation of several depositional methods. In this paper the authors present two automated devices for both special and universal purposes. They can be used to obtain films and monolayers by vertical lifting of the substrate from the colloidal suspension, vertical deposition by pumping out the suspension, electrophoresis and Langmuir-Blodgett technique and its combinations.
Smart-UPS with a priority-based load management system
Authors: Bharti Prince , Singh Abhijeet , Singh Pushpendra
Published: September 2021

In this paper, a cost-effective Smart-UPS has been developed which will perform load shedding on a priority basis. This smart UPS will include an accessory installed along with the conventional UPS. This paper relates to the field of managing power distribution. In particular, it pertains to a system and method for power distribution among devices, based on priority. The objective of the present disclosure is to efficient supply to distribute power among requirement of devices, to provide cost efficient power management and to enhance output of the devices with limited power back up.

The designed project will switch off lower priority loads according to Battery percentage to minimize the load suffered by the battery. The loads connected to supply load are divided into three sections, i.e. high priority (HP), medium priority (MP) and low priority (LP) loads. The project involves the development of a smart UPS system which will automatically switch off/on the high priority (HP) loads, medium priority (MP) and low priority (LP) loads (specified during installation of the UPS as specified by the user).
IoT based wastewater spillage detection system
Authors: Patel Rutvik , Prajapati Jay , Dave Meha , Joshi Ishwariy , Rathod Jagdish M
Published: September 2021

Internet of Things (IoT) is a system of interrelated devices including computers, processors, machines, or objects capable of transferring data over a network with no object-object, object-system interactions. In India, one of the most influential problems observed is the overflowing drains in the sewage system which becomes more problematic during the monsoon seasons when the authorities are unaware of the overflowing drains. It becomes unhygienic for the nearby residents and also causes water-logging which leads to breeding of pests. Our solution to this problem is an IoT system which instantly notifies the municipal authorities about the overflowing drains via email or notification at the city control center, also the citizens will get updates via social media or a mobile application. This system mainly comprises a low-powered IoT based portable device to be attached below the manhole cover. It leverages the LoRa technology to transmit the sensor data. Also, the frame of the manhole will be using solar power to charge the device. The proposed system makes the management and monitoring of the underground drainage system easier and hence saves the lives of hundreds of manual scavengers who die each year while cleaning the drainage systems.
Setup Design for the Production of Methane Gas from Kitchen Waste
Authors: Kumar Satyam , Hussain Fahd , Trivedi Shefali
Published: September 2021

Generation of kitchen waste is increasing day by day because of raise in population as well as change in socio-cultural habits. Most of these wastes can be decomposed by the action of microorganism in a short span of time because they are biodegradable substances. E.g. Food waste, vegetable peals, fruit pulp etc. If these materials are dumped in soil or kept in open, it undergoes microbial changes & releases Carbon dioxide, Methane, Ammonia & Hydrogen sulphide which can lead to air pollution and foul smell. If these gasses are trapped properly, it can be used as a source of energy and can save environment on the same go. In the present paper, work has been done on a setup for conversion of kitchen waste into energy which will be useful for college canteen & mess, and at places where a large amount of waste are generated on daily basis. The setup design for the production of methane gas has been done using Solidworks software (2016 version) and stress analysis of the methane gas collector has also been carried out. This setup also consists of flow measuring sensors which can measure the amount of gas formed & used, in a certain period of time. This setup will be connected via mobile app for real-time data and can be used anytime for monitoring of gases and for research purpose as well.
The Analysis Of Scattering For Transverse Electric By Perfectly Conducting Connected Strips At Node
Authors: Vimal
Published: September 2021

This paper analyzes the scattering for transverse electric (TE) incidence by perfectly conducting connected strips. The configuration of the problem has multi-strips connected at a node. The proposed method is current-based hybrid method which reducing the number of unknowns. In the proposed procedure very few expansion functions are required to achieve the result. Hence this is very efficient method. The proposed method based on Galerkin scheme using expansion functions.
Hypergeometric interpretation of the modified Beta Stancu operator
Authors: Sharma Rupa Rani
Published: September 2021

In this article, we apply Gupta and Ahmad [18] out comesusing hypergeometric series. We research local and global properties, asymptotic formula-style Voronovskaja, and errors estimate for modified Beta operators. We also obtain specific other characteristics from these operators.
Comparison of Various Load Frequency Control Schemes in Restructured Power System Environment
Authors: Kumar Nagendra , Kumar Jitendra , Chaurasia Ravi , Sharma Himanshu
Published: September 2021

This paper presents comparison of performances of secondary controllers like Integral (I), Proportional-Integral (PI), Integral-Derivative (ID), Proportional-Integral-Derivative (PID) and Integral-Double Derivative (IDD) as load frequency control scheme. The controllers have been tested on two equal areas thermal power system with non-reheat turbines in the presence of nonlinearity i.e. generation rate constraint (GRC) of 3% per minute. The disco participation matrix (DPM) is considered for various power transactions between Genco and Discos in both areas. A well-known optimization algorithm i.e. genetic algorithm (GA) is used to determine the optimal parameters of different controllers. Three cases i.e. load perturbation in one area only, load perturbation in both areas and more demand asked by Disco than the contract have been considered to check the response of controllers. Comparative analysis of the results obtained for all three cases show that Proportional-Integral-Derivative (PID) controller provides better performance than other controllers in terms of settling time..
BLDC Drive for EV Application
Authors: Srinivasan Shiva Srenivasan , Lakshanasri N.R.S , Setty Sahana M , Dubey Piyush , Singh Anant , Senthilmurugan S.
Published: September 2021

The purpose of this paper is to evaluate the efficiency of a BLDC motor in regenerative braking mode. The mode of operation of the BLDC motor using its torque-slip characteristics is taken into consideration to evaluate its performance. The simulation, characteristics and the tabular column are all got from the MATLAB simulation. The paper ends with a suggestion of using supercapacitors to compensate for the energy lost while the motor is in regenerative mode. The purpose of the supercapacitor has also been discussed to show the usefulness on the inclusion of the component. The motor and the supercapacitor compliment each other to increase the efficiency of the electrical vehicle.
The Q-MBS Operators in a linear positive operator Voronovskaya style asymptotic formula
Authors: Sharma Rupa Rani , Mishra R.K. , Garg Sudesh Kumar
Published: September 2021

The paper reveals the development theory of modified Beta Stancu operators. Incorporate Q derivatives and get critical moments from another Q-Beta generator. There is also a simple module inference for Q operators. Primary moments, Voronovskaya method asymptotic process, and error calculations applying these characteristics are produced for these operators. We used Q integral properties to verify the recurrence theorem for Q analog moments of the updated Operators. We still have an asymptotic method. After the day, We examined all such Q operators’ updating to help estimates.
Performance evaluation of coconut shell originated activated carbon as an adsorbent on the paint factory effluent treatment
Authors: Vishali S. , Sandhiya J. , Divya  , Aarthi K. , Abhilash
Published: September 2021

The current study was aimed to evaluate the ability of the activated carbon prepared from coconut shell in the decolorization of paint factory effluent (PFE). The studies were performed in the fixed bed adsorption column by optimizing the design variables viz., initial effluent concentration, bed height and low rate. The experimental observations were used to make breakthrough curves and were validated using Adams – Bohart model and Yoon-Nelson model. The results recommended that the encapsulated activated carbon of coconut shell origin showcased its capacity to perform in the process of paint factory effluents decolorization as an adsorbent.
Fractographic investigation of Low Cycle Fatigue behaviour of IN718 coated with NaCl at 550°C
Authors: Kumar Mukesh
Published: September 2021

Nickel base super alloys due to their superior properties are used in different parts of gas turbines, in jet engines, and as well as in marine application from 250°C to 650°C. At such high temperature sulphur and vanadium as impurities in fuel oil get oxidised in SO2 and V2O5. Further, sulphur oxide reacts with NaCl to form Na2SO4. These salts cause high temperature corrosion which causes stress corrosion cracking of engine components of marine gas turbine. Therefore, LCF resistance of the material becomes an important consideration in design of turbine. Fatigue samples both coated with NaCl salt and uncoated samples were tested in low cycle fatigue. The fatigue tested samples were analyzed under Scanning Electron Microscope (SEM). Since micrographs analysis is an important tool with the testing of materials to evaluate the various properties of the materials. In present study micrographs analysis helped to a great extent for evaluation the Low cycle fatigue behaviour of Nickel base super alloy INCONAL 718 (IN718) at high temperature which is 550°C.
A Matching Algorithm T-AKAZE for Image Recognition of Hydroelectric Equipment Failure
Authors: Xu Jiayu , Ji Xiu , Wang Yan
Published: September 2021

Aiming at the shortcomings of the current image-based fault identification algorithm for hydropower station equipment, such as low efficiency and poor accuracy, an improved image matching algorithm based on AKAZE, T-AKAZE was proposed. In this paper, AKAZE algorithm is firstly used to obtain image feature points. Then, the improved algorithm T-AKAZE is used for coarse matching of feature points. On the basis of Tanimoto coarse matching, RANSAC algorithm is used for fine matching to improve the algorithm accuracy. In order to verify the matching effect of the improved algorithm, ORB algorithm, AKAZE algorithm and ORB+Tanimoto algorithm were compared and analyzed. The experimental results show that the proposed algorithm has good robustness for image matching of different scales and similarity, and its timeliness also meets the application requirements, which provides convenience for the staff to identify the fault of hydropower station equipment.
Research on the Emotional Polarity Classification of Barrage Texts
Authors: Su Qian , Tan Wenan , Zhang Lu
Published: September 2021

With the widespread application of multimedia technology, video barrage has become an important form of expressing opinions and emotions. The classification of Chinese barrage texts according to emotions is of great significance for mining users’ emotions. However, the large number of Internet buzzwords in the barrage texts brings certain difficulties to sentiment analysis. Therefore, in order to address the ambiguity problem of Internet buzzwords in the barrage texts and effectively classifying the video barrage texts, the BERT pre-training language model and Support Vector Machine are combined to classify the barrage texts of positive and negative emotions. In this paper, the word vectors of the barrage texts are firstly generated by the BERT model. The SVM model is used as a classifier, and Particle Swarm Optimization is introduced to optimize the parameters of the SVM model. This method is compared with the traditional methods on the barrage data sets of different video types. The experimental results show that the precision, recall and F1-score of the proposed method are higher than those of the traditional models.
A Classification Method for Network Traffic Based on Semi-supervised Approach
Authors: Liu Yun , Zhu Zhiqiang , Zhong Pengfei
Published: September 2021

Traffic data encryption has been a trend in most Internet applications, and traditional protocol filtering based on fixed port and traffic classification based on Deep Packet Inspection are unable to Identify encrypted traffic. Recently, the traffic classification method based on the statistical characteristics of network traffic, which can solve the problem of encrypting data or user privacy protection, has been widely discussed. However, the traditional supervised learning method requires manual marking of a large amount of network traffic data, which is tedious and time-consuming. In this paper, a improved semi-supervised traffic classification framework based on BIRCH clustering method is proposed, and through experiments, the proposed algorithm, supervised learning algorithm and classical semi-supervised traffic classification algorithm are analyzed and compared. The results show that the algorithm proposed in this paper has higher overall accuracy and classification accuracy, and the algorithm can increase the accuracy on traffic classification.
Tracing Knowledge of Student based on Academic Knowledge with Machine Learning and Deep Learning
Authors: Hu Jiayu , Li Mingyi , Mao Huimin , Liu Cheng
Published: September 2021

Because the number of students not attending school is expanding at an alarming pace, and because of the COVID-19 epidemic, 102 countries have implemented nationwide closures to conduct local shut-downs and temporarily close schools. This slowed down learning possibilities and intellectual growth even more. Every country’s equity disparities may widen. As a result, we must restructure our educational system so that students can gain correct knowledge and teachers can track how much each student has learned. As a result, Machine Learning and Deep Learning are the most effective solutions for this type of problem. As a result, we’re releasing a method for tackling this challenge using Tabnet, Transformers, LGBM, and a variety of other machine learning approaches for student knowledge tracing.
Batch scheduling with incompatible job families and common due date
Authors: Liu Lili
Published: September 2021

This paper explores incompatible batch scheduling with common due date on a single batch processing machine. The problem of minimizing the number of tardy jobs is proved to be NP-hard with respect to id-encoding, and pseudo-polynomial time algorithms for minimizing the number of tardy jobs and the weighted number of tardy jobs are presented, respectively.
Pedestrian age recognition method based on gait deep learning
Authors: Song Tao , Yang Xin , Wang Yulin , Lei Yu , Liu Guanting
Published: September 2021

A pedestrian age recognition method based on gait information and dynamic weight convolutional networks is proposed to solve the problem that face age recognition needs a close positive perspective and frontal angle which limits its application scenarios. Firstly, the method takes gait energy image as input and the gait energy image is divided into head, upper body and lower body. Then, the global and local features of gait are extracted by global local convolutional networks. Secondly, the multi-layer residual expansion networks is constructed to optimize the gait energy image, and the average pooling is used to replace the fully convolutional networks for age classification. In order to solve the problem of sample imbalance in different age groups, the dynamic weight cross-entropy loss function is utilized as the network loss function to constrain the parameter updating, so as to avoid the recognition results inclining to the class with more samples. Experimental results on OULP age dataset demonstrate the effectiveness of the proposed approach.
Comparative Study on Numerical Simulation of Thorax Blunt Impact Based on LS-DYNA Software Technology
Authors: Chen Chaoming , Zhao Fadong , Bao Hongtao , Zhuang Hongwei
Published: September 2021

In order to better predict the risk of blunt impact on human thorax, the LS-DYNA software was used to reproduce the launch conditions of the postmortem human specimens(PMHS) experiment of the Wayne State University research group, numerical simulations of thorax blunt impact were carried out in combination with the human body model AM50 and Hybird III 50th Dummy model. The projectiles of impact test were respectively 37mm in diameter, 100mm in length, 140g in mass, with an impact velocity of 20m/s and 40m/s, and 37mm in diameter, 28.5mm in length, 30g in weight, with an impact velocity of 60m/s. The numerical response of thoracic compression was obtained by simulation experiment, which was verified by comparison with the experimental data of PMHS. The displacement curves of the thoracic compression of the two models were both in the response corridors of PMHS by the simulation experiment, and the differences between two displacement curves were analyzed. The viscous standard of Dummy under three launch conditions was calculated to be within the boundary of VCmax in PMHS experiment, which provided a certain theoretical reference for Dummy as a subsequent experimental research object.
The Research Progress of the Deep Hybrid Model in the Field of Text Classification
Authors: Yang Chunfeng , Wu Qiang , Lu Jiajia , Chen Huiyu
Published: September 2021

The traditional deep convolution neural network model cannot extract the context information effectively in dealing with complex long text data sets, and it is difficult to obtain the deep semantic information of the text. The deep hybrid neural network can optimize and improve the local feature extraction ability of CNN model while preserving the ability of local feature extraction. It has achieved good performance on complex data sets, so it has been paid more and more attention by researchers. Firstly, this article sorts out the current mainstream text classification data sets. Secondly, the model of the hybrid neural network based on the convolutional neural network construction is as follows: the improvement of the CNN model; technology fusion based on CNN model and the CNN-based model mixing three categories carry out analysis and sorting. Finally summarize the current problems in the text classification field, and look forward to future development and research.
Ant Colony Algorithm for Time Optimal Load Balancing Scheduling Problem Strategy
Authors: Tong Yuxiang , Li Xiaohui
Published: September 2021

In order to optimize the task execution efficiency of FPGA high-performance network clusters, this paper proposes a time-optimal load balancing scheduling problem algorithm and initialization strategy. Taking the task completion time as the optimization direction, the load balancing scheduling problem is abstracted as solving the placement matrix problem. On this basis, a node selection strategy using critical matrix is proposed, and the algorithm design is completed based on the ant colony algorithm. Aiming at the problem of low efficiency of random initialization, this paper proposes two ant colony initialization methods, which are ranked greedy initialization strategy and polling decentralized initialization strategy. Experiments show that the algorithm and initialization strategy designed in this paper can adapt to different computing scales, and the two initialization strategies can achieve a 15%∼55% improvement in the iterative convergence times and load balancing compared to random initialization.
Research on Cell Counting Method Based on Flood Fill Algorithm
Authors: Ning Zile , Wang Shuo , Li Xiao , Yu Yuanhua , Gao Le
Published: September 2021

Cell counting has a wide range of applications in cytology research and clinical practice. Cell counts are widely used in the early diagnosis and treatment of serious diseases and the screening of effective drugs in the later stage. The method of studying cell counts is of great significance. This paper proposes a method for cell counting based on the highlight area of the cell center as a live cell marker. This method uses algorithms bilateral filtering to smooth noise in the original image; after adaptive threshold segmentation, an algorithm based on flood filling is used. Accurate segmentation of the highlighted area in the center of the cell; finally, counting is achieved through the connected domain labeling algorithm. The experimental results show that the accuracy of the cell counting method proposed in this paper is above 98%, which verifies the feasibility and practicability of the method proposed in this paper.
Research and Implementation of SSH Proxy System for Filtering and Auditing
Authors: Wang Zhuxiao , Zhang Jiaming , Wu Kehe , Li Wei , Cui Wenchao
Published: September 2021

With the rapid development of information technology and network, the informatization level of enterprises is constantly improving, and the security of information system is becoming more and more important. Not only the external intrusion needs to be effectively resisted, but the operation and maintenance of internal personnel also needs to be under security control. Starting from the internal security of enterprise information system, this paper designs and implements the SSH protocol operation and maintenance audit system based on libssh. The forwarding module of the system can meet the requirements of SSH protocol operation and maintenance, and set command parsing, filtering and recording modules, which can correctly identify the commands executed by users and server data, and addition to filter the forbidden commands. In addition, the setting of replay and monitoring module can record the whole process of personnel’s operation, so as to ensure that the auditors can monitor in real time or replay afterwards. The system ensures the security of the enterprise internal information system.
Research on remote data access and visualization for long pulse experiment based on web technologies
Authors: Fan Mengqi , Gu Yu , Cao Tengfei , Zhang Xiaodan
Published: September 2021

Model Drive System plus (MDSplus) is an efficient and convenient data storage and management software designed by MIT specifically for pulse experiments. After years of development, MDSplus has become a data management system that integrates data acquisition, storage and processing of complex scientific data. However, with the development of the experimental pulse, long pulse experiment has now become the main mode of pulse-type experiment. Compared with the short pulse experiment, the data acquisition under the long pulse experiment speed is faster, the experiment time is longer, and the amount of data is larger. In view of the fact that most of the existing visualization systems are based on client/server (C/S) architecture, which can only display local visualization. Therefore, In order to enrich the way for experimenters to obtain data, this paper designs a visual platform based on browser/server (B/S) that using the WAMP (Windows+apache+MySQL+php) architecture to build the server. The bootstrap framework is used to build the front-end. Before the visualization data transmission, the original data is processed by segmentation technology to reduce server load and improve transmission utilization so that experimenters can query and obtain the required data remotely through the platform.
Service Innovation of Industrial Big Data Based on Industry 4.0 Architecture
Authors: Cheng Xiaolei , Zhang Pinghua
Published: September 2021

The service innovation based on the cyber-physical system is a trend in the future manufacturing industry. In this article, the servicing functions involved in the manufacturing industry under the environment of industrial big data were analysed. In addition, the combination of the needs, environment and services of industrial big data were described. Furthermore, the intelligent forecasting tools to manage industrial big data, increase the transparency of industrial production, and improve work efficiency were proposed to adopt for the application of service innovation.
Key frame extraction for Human Action Videos in dynamic spatio-temporal slice clustering
Authors: Sima Mingjun
Published: September 2021

Detecting representative frames in videos based on human actions is quite challenging because of the combined factors of human pose in action and the background. This paper proposed a key frame extraction algorithm based on dynamic spatio-temporal slice clustering. This algorithm firstly uses the dynamic spatio-temporal slice position selection method based on the human mask heat map to calculate the position of slice to realize the dynamic selection of slice positions, then complete the extraction of spatio-temporal slice images. After clustering the spatio-temporal slice images, this method extracts key frames according to the clustering results. The experimental results prove the validity of spatio-temporal slice location selection method, the proposed algorithm can effectively solve the problems of information redundancy and key information missing in existing methods. We conduct experiments on a challenging human action dataset UCF101 and show that our method can detect key frames with high accuracy.
Design and Implementation of Hotel Big Data Analysis Platform Based on Hadoop and Spark
Authors: Chi Dianwei , Tang Chunhua , Yin Chen
Published: September 2021

In order to provide decision support for user travel and hotel management planning, this paper proposes the design and implementation of a hotel big data analysis platform based on Hadoop and Spark technology, using hotel basic data and user comment data as data sources. First, we design a crawler program to collect basic data and user comment data of city hotels in Qingdao, Shandong Province, and upload them to the hadoop storage platform, use Spark for big data preprocessing, use Hive to build a big data platform data warehouse, and finally use echarts to analyze the results and make decisions perform a visual display.
An illumination direction estimation algorithm of face images
Authors: Chen MeiLing
Published: September 2021

Illumination is one of the important factors affecting the accuracy of face recognition. This paper proposes an illumination direction estimation algorithm of face images and it can be applied to the non-frontal face image. In order to eliminate the influence of face’s albedo, the algorithm use SfSNet to get the shading image. The algorithm divides the face region into eight regions by using five landmarks in face and estimate the illumination direction by analyzing the average brightness of each regions. Experiment on YaleB dataset shows that the algorithm can estimate the illumination direction correctly in most cases.
Research on Modulation Recognition of Communication Signal
Authors: Liu Shukun , Gao Yifei , Wang Yuanshi , Ren Yifei , Huang Yixuan
Published: September 2021

Modular identification of radio communication signals is widely used in commercial software’s as well as the country’s defence. With the phenomenal development of modern telecommunications in various countries. The process of converting data into radio waves by adding information to an electronic or optical carrier signal becomes more sophisticated and variable. As a result, there has been a great deal of research and development into signal interpretation, and a number of effective schemes have been devised. For Signal Modulation, recent research has used a variety of techniques such as clustering, neural networks, automatic modulation, and analytical parameters. A quick description and summary of signal recognition approaches is offered in this study. We also reviewed contemporary technological hurdles, as well as the future direction of modulation.
An improved HOG-SVM recognition algorithm of power equipment with infrared images
Authors: Qian Yucheng , Zhen Chao , Wang Mengjun , Han Sheng , Li Jiaxuan , Zhao Changwei , Zhu Taiyun
Published: September 2021

Infrared image recognition of power equipment is a necessary prerequisite and a key step to using the infrared image for equipment defect detection, while one of the difficulties is to solve the problem of low accuracy of equipment recognition, which is caused by the difficulty of extracting equipment feature quantity caused by different rotation Angle and scale of equipment image. In this paper, 12 kinds of common power equipment, such as lightning arresters, current transformers, voltage transformers, circuit breakers, and insulators, are taken as the research objects. An improved HOG-SVM algorithm for infrared image recognition of power equipment with rotation invariance is proposed. Experimental results show that the proposed method can effectively compensate for the shortcoming of the HOG algorithm without rotation invariance, and the average recognition accuracy of 12 types of equipment reaches 92.14%, which significantly improves the recognition accuracy of infrared images of power equipment, and verifies the effectiveness and practicability of the proposed algorithm.
Design and Implementation of an Attention-Based Interpretable Model for Document Classification
Authors: Ye Zuoxian
Published: September 2021

With the rapid development of artificial intelligence and machine learning, deep learning technology has been successfully applied to various tasks in the field of natural language processing. However, the erroneous decisions produced by the deep learning model and the characteristics of its black box cause users to doubt its decisions. We urgently need the model to have the ability to make rationalized explanations of its decisions, that is, interpretability. In this paper, we propose an attention-based interpretable model for document classification, which aims to have a better model performance and at the same time have better interpretability. Experiments show that our classification model is close to the performance of other mainstream models. Also, the attribution score explanation provided by the interpretation method are effective.
Relation Aware Attention for Penson Re-identification
Authors: Song Junyu , Li Kaifang , Hui Guancheng , Zhang Miaohui
Published: September 2021

Person re-identification (Re-ID) means matching people across different camera views based on different locations. It is challengeing for person images where there are background clutter, pose variations, illumination changes, etc. Attention mechanisms have become attractive for person re-identification algorithms as they aim at strengthening discriminative features, which accord with the purpose of person re-id, i.e., learning discriminative features for diffirent pedestrains. Previous approches mostly learn attention by useing local convolutions which have limited receptive filds. In this paper, an Relation Aware Attention(RAA) module is proposed to address this issue. RAA infers attention maps along two dimensions, channel and spatial, then them are mutiplied to the feature as the output map. For each feature position, RAA harvests the pairwise relationship with others as its response. Furthermore, in order to grasp the structure information of global scope and the local apperance information, we stack the relations and the feature to lean the final attention with a convlutional model. We designe the experiment and compare it with the existing benchmark. The resulits show that our attention model can increas the abillity of feature representation.