bluuebunny/crossref_metadata_2025_split huggingface dataset:
Telecommunications package recommendation algorithm based on Deep forest
Authors: Zhang Yanhong , Wang Meng , Yu Yingfu 
Published: November 2021

AbstractIn view of the wide variety of telecom packages and the difficulty of adapting to the needs of users, this paper introduces a recommendation model for telecom packages based on deep forests. This paper first analyzes the telecom package data, and then optimizes the deep forest according to its characteristics such as discrete, continuous attribute interleaving and high coupling characteristics, including the use of decision trees to discretize continuous features and design continuous window sliding mechanism. These methods can improve the ability of deep forest combination high coupling features. Finally, the model optimization measures were verified by detail experiments. The experimental results show that the optimized deep forest can be applied to the telecom package recommendation field. Compared with other shallow models and unoptimized deep forest models, the deep forest model has increased the F1 score by 5%; after adjusting the deep forest hyper parameters, the F1 score can be increased by 2%.
Chua’s Circuit Simulation Experiment Based on Saturation Function
Authors: Lv Ensheng 
Published: November 2021

Abstract
This paper designs a Chua's diode circuit based on saturation function. It uses Matlab/Simulink to model Chua's circuit, and simulates and analyzes the dynamic behavior of chaos, the model simply generates efficient chaotic signals, and intuitively displays processes of the chaotic attractor, chaotic synchronization, period doubling and the road to chaos through the virtual oscilloscope, which is conducive to chaotic beginners' understanding of the basic characteristics and application of chaos. The electrical and mathematical analysis of the instrument is carried out by simulation, to explore the functions of each parameter, and helps beginners to understand its working principle more quickly and conduct experimental operations. It provides theoretical support for the improvement and optimization of Chua's circuit.
An iterative refinement method of point cloud for binocular vision 3D reconstruction
Authors: Hu Junwei , Sun Jifeng , Li Yinggang , Zhang Qi , Zhao Shuai , Lin Yibin 
Published: November 2021

Abstract
This paper introduces a new binocular stereo deep learning network based on point cloud, which can realize higher precision point cloud reconstruction through continuous iteration of the network. Our method directly carries out point cloud processing on the target, calculates the difference between the current depth map and the real depth, estimates the loss according to the predicted point cloud and the information of the dual view input image, and then uses the appropriate loss function to iteratively process the point cloud. In addition, we can customize the number of iterations to achieve higher precision point cloud effect. The proposed network basically achieves good results on KITTI data set.
An automatic sleep staging method based on CRNN-HMM model
Authors: Wu Mengran , Xie Hong , Shi Huiping 
Published: November 2021

Abstract
Sleep staging is an important process for detecting sleep quality and diagnosing sleep disorders. However, traditional sleep staging is a labor-intensive task, and it is prone to subjective errors. Therefore, this paper innovatively proposes an automatic sleep staging model based on single-channel EOG—CRNN-HMM. The CRNN-HMM in this paper combines Convolutional recursive neural networks(CRNN) and hidden Markov model(HMM). The main idea of this model is to use CRNN to automatically extract features from EOG, and send the feature signals to a variant of RNN, Bi-directional Long Short-Term Memory(BiLSTM), to mine the dependencies between sleep stages and realize automatic staging of sleep data. Finally, a Hidden Markov Model is used to convert the prior information of the sleep phase of the adjacent EOG cycle in order to improve the classification performance of S1, thereby improving the classification performance of CRNN. The simulation results show that the overall accuracy of the model on the CAP-Sleep data set reaches 95.0%, which proves that the model can provide a way for the evaluation of sleep quality.
Intelligent Lifebuoy Based on Machine Vision
Authors: Hu Lintao 
Published: November 2021

Abstract
This article mainly introduces the intelligent lifebuoy based on machine vision. The design uses the OpenMv camera to identify the drowning person. OpenMV sends the collected position information of the person to the MCU. If the drowning person is on the left or right side of the lifebuoy, the MCU controls the motor drive module. Control the differential rotation of the motor behind the lifebuoy so that the lifebuoy is facing the drowning person. If the drowning person is directly in front of the lifebuoy, the MCU controls the motor drive module to control the rotation of the motor behind the lifebuoy to make the lifebuoy gradually approach the drowning person, which can save life. Blue balloons was used instead of drowning people to conduct rescue experiments on the lake. The smart lifebuoy successfully recognized the blue balloon and swam near the blue balloon. Furthermore, a perfect solution is proposed for the shortcomings of the intelligent lifebuoy.
Performance analysis of vortex acoustic wave based on uniform circular array
Authors: Xu Jie , Li Hui , zhou You-Ling , Li Qian , Xue Liu-Xun , Shi Chong-Yue , Wang Hou 
Published: November 2021

Abstract
As a carrier for information and energy, acoustic waves have been applied in underwater communication widely, however, the narrow band and low transmission speed are the main problems. Whether in the field of optics or electromagnetic waves, the orbital angular momentum (OAM) represents the natural properties of the spiral phase structure. By introducing the OAM into the acoustics field, the transmission capacity and spectrum efficiency of the underwater acoustic communication system can be expanded. Based on the analysis and detection of the vortex acoustic wave generated by the circular array of transducers, we studied the array generation method of the spiral acoustic beam, and gave the characteristics of the vortex acoustic beam when propagating under the water. In the direction of the main axis, the uniform circular array was used to generate different topological acoustic vortex. To determine the relationship between the OAM topology mode and the transducer array, the spiral acoustic waves in different topology modes were generated, and the number of array elements, array radius, transmission frequency, etc. were investigated to give the effects on OAM acoustic vortex.
SA-HAVE: A Self-Attention based Hierarchical VAEs Network for Abstractive Summarization
Authors: Wan Xia , Ju Shenggen 
Published: November 2021

AbstractThe abstractive automatic summarization task is to summarize the main content of the article with short sentences, which is an important research direction in natural language generation. Most abstractive summarization models are based on sequence-to-sequence neural networks. Specifically, they encode input text sequences by Bi-directional Long Short-Term Memory (bi-LSTM), and decode summaries word-by-word by LSTM. However, existing models usually did not consider both the self-attention dependence during the encoding process using bi-LSTM, and deep potential sentence structure information for the decoding process. To tackle these limitations, we propose a Self-Attention based word embedding and Hierarchical Variational AutoEncoders (SA-HVAE) model. The model first introduces self-attention into LSTM to alleviate information decay of encoding, and accomplish summarization with deep structure information inference through hierarchical VAEs. The experimental results on the Gigaword and CNN/Daily Mail datasets validate the superior performance of SA-HVAE, and our model has a significant improvement over the baseline model.
Application Research of Internet of Things Smart-home System Based on MCU Micro Control
Authors: Huang Canjie 
Published: November 2021

Abstract
As a controller, the functions that need to be realized are very limited, and there is no need for large-scale calculation, a very simple single-chip microcomputer can be competent. However, it is necessary to make the single-chip microcomputer exquisite and powerful, that is, integrate one or more cores of RFID, ZigBee and PLC in the chip, so as to reduce the volume of the control system and realize embedded system.
Advanced assessment of beam-induced background at a muon collider
Authors: Collamati F. , Curatolo C. , Lucchesi D. , Mereghetti A. , Mokhov N. , Palmer M. , Sala P. 
Published: November 2021

Abstract
Renewed international interest in muon colliders motivates
the continued investigation of the impacts of beam-induced
background on detector performance. This continues the effort
initiated by the Muon Accelerator Program and carried out until
2017. The beam-induced background from muon decays directly impacts
detector performance and must be mitigated by optimizing the overall
machine design, with particular attention paid to the machine
detector interface region. In order to produce beam-induced
background events and to study their characteristics in coordination
with the collider optimization, a flexible simulation approach is
needed. To achieve this goal we have chosen to utilize the
combination of LineBuilder and Monte Carlo FLUKA codes. We report
the results of beam-induced background studies with these tools
obtained for a 1.5 TeV center of mass energy collider
configuration. Good agreement with previous simulations using the
MARS15 code demonstrates that our choice of tools meet the accuracy
and performance requirements to perform future optimization studies
on muon collider designs.
Evaporation process dominates vehicular NMVOC emissions in China with enlarged contribution from 1990 to 2016
Authors: Yan Liu , Zheng Bo , Geng Guannan , Hong Chaopeng , Tong Dan , Zhang Qiang 
Published: November 2021

Abstract
Non-methane volatile organic compounds (NMVOC) are important precursors of ozone and secondary organic aerosols in PM2.5 (particulate matter with aerodynamic diameters smaller than 2.5 μm), both of which cause severe climate, ecosystem, and human health damages. As one of the major anthropogenic sources, onroad vehicles are subject to relatively large errors and uncertainties in the estimation of NMVOC emissions due to complicated methods and parameters involved and a lack of comprehensive evaluation of influencing factors. Here, based on our previous work with necessary improvement, we estimate China’s vehicular NMVOC emissions by county and by month during 1990–2016 with a consideration of meteorological influence on the spatial-temporal dynamics of emission factors. Our estimate suggests that vehicular NMVOC emissions in China have peaked around 2008 and then declined up to 2016 with an enlarged contribution of the evaporative process to vehicular NMVOC emissions. Vehicular NMVOC emissions have been dominated by the evaporative process at present. Meteorological factors alter spatial-temporal distributions of NMVOC emissions, especially evaporative emissions, which are enhanced in South China and in summer. Emissions and ozone formation potential of the major chemical groups (i.e. Alkenes, Aromatics, and Alkanes) also increase substantially due to meteorological influences. Our analysis suggests that mitigation strategies for vehicle pollutions should be designed based on a sophisticated emission inventory accounting for the meteorological impact on emission factors to correct the potential underestimation of NMVOC emissions, especially those from the evaporative process.
On the properties of the asymptotic incompatibility measure in multiparameter quantum estimation
Authors: Candeloro Alessandro , Paris Matteo G A , Genoni Marco G 
Published: November 2021

Abstract
We address the use of asymptotic incompatibility (AI) to assess the quantumness of a multiparameter quantum statistical model. AI is a recently introduced measure which quantifies the difference between the Holevo and the symmetric logarithmic derivative (SLD) scalar bounds, and can be evaluated using only the SLD operators of the model. At first, we evaluate analytically the AI of the most general quantum statistical models involving two-level (qubit) and single-mode Gaussian continuous-variable quantum systems, and prove that AI is a simple monotonous function of the state purity. Then, we numerically investigate the same problem for qudits (d-dimensional quantum systems, with 2 < d ⩽ 4), showing that, while in general AI is not in general a function of purity, we have enough numerical evidence to conclude that the maximum amount of AI is attainable only for quantum statistical models characterized by a purity larger than

μ

min

=
1
/

(

d
−
1

)

. In addition, by parametrizing qudit states as thermal (Gibbs) states, numerical results suggest that, once the spectrum of the Hamiltonian is fixed, the AI measure is in one-to-one correspondence with the fictitious temperature parameter β characterizing the family of density operators. Finally, by studying in detail the definition and properties of the AI measure we find that: (i) given a quantum statistical model, one can readily identify the maximum number of asymptotically compatible parameters; (ii) the AI of a quantum statistical model bounds from above the AI of any sub-model that can be defined by fixing one or more of the original unknown parameters (or functions thereof), leading to possibly useful bounds on the AI of models involving noisy quantum dynamics.
Entanglement criterion via general symmetric informationally complete measurement
Authors: Li Jun , Chen Lin 
Published: November 2021

Abstract
We propose entanglement criteria for multipartite systems via symmetric informationally complete measurement and general symmetric informationally complete measurement. We apply these criteria to detect entanglement of multipartite states, such as the convex of Bell states, entangled states mixed with white noise. It is shown that these criteria are stronger than some existing ones.
The important role of multifunctional forests in society: a methodology for stands delimitation
Authors: Hernando A , Tejera R , García-Abril A , Velázquez J , Iglesias-Merchan C , Valbuena R , Manzanera J 
Published: November 2021

Abstract
Forest planning and management must be conceived in accordance with the circumstances and needs of the moment. Nowadays, the forest does not have a single and exclusive productive use but responds to multiple demands. The stand management method, with a broad approach, is has been recently well adapted to this type of multipurpose management. This study proposes a methodology for delimiting stands which led to manage different uses in forests in protected areas. The methodology consists of six phases: (i) create permanents units (ii) initial identification of forest typologies, (iii) image analysis, (iv) identification of tree types within the forest typology, (v) detailed inventory and (vi) formation of stands. An example is presented for the “Monte Paris” forest, located a few kilometers from Madrid, which combines protective, livestock and recreational use. For the protection use, pruning and thinning will be carried out, for the livestock use, supplementation, meadow sowing and enclosures, and for the recreational use, the design of an environmental center and five ecological trails are proposed. The organization in time and space of the activities planned in the stands allows a correct and satisfactory management of the multiple uses that occur in this forest.
River-flood forecasting methods: the context of the Kelantan River in Malaysia
Authors: Abdul Majid M , Hafidz Omar M , Noorani M Salmi M , Abdul Razak F 
Published: November 2021

Abstract
River-flood forecasting is among the most important feasible non-structural approaches used in reducing economic losses and alleviating human sufferings. In spite of uncertainty in the forecasting of natural disasters, the current prevailing methods developed in many parts of the world in the recent history has made good progress to a great extent. The advancement is attributed mainly due to the availability of high-resolution weather data and the use of sophisticated computer modelling algorithms. However, it is desirable to conduct exploratory review studies to further improving the current state of affairs. The present paper reviews briefly the river-flood forecasting methods currently used worldwide with a specific focus in the context of the Kelantan River in Malaysia. Flooding in Malaysia is recurrent covering a large inhabited area compared with other natural disasters. Some of the popularly used methods in the literature such as statistical methods machine learning and methods based on chaos theory have been reviewed, The paper will also attempt to explore the future direction for research and development that might be useful specifically for dealing with the recurrent rivers flooding in Malaysia. A reasonably acceptable prediction of river streamflow is significantly important in disaster management and water resources management.
Analysis of Malaysia electricity demand and generation by 2040
Authors: Azman Azreen Harina , Tukimat Nurul Nadrah Aqilah , Malek M.A. , Faizah Che Ros 
Published: November 2021

Abstract
Malaysia as an emerging country, increasing population, gross domestic product (GDP) growth and enhanced access to electricity lead to an expanding of demand. The crucial parameters to determine future energy demand and generation projections are GDP, population growth rates and weather implications due to climate change. The study aims to forecast the future trends based on the historical values and also to project the future electricity demand and generation. The electricity demand and generation growth evaluated based on 2 main elements which are population growth and weather parameters (maximum temperature and rainfall). The future trends are forecasted based on the historical values of population and weather parameters. There is 152.9% of population growth in 32 years. The population will keep on developing yet with the lower rate. The GDP trend and the population growth mirrors the pattern of emissions. The findings from Statistical Downscaling Model (SDSM) analysis shows that the rainfall distribution will diminish while the temperature will expand that depict the climate change impact as time passes by. In 2020, the most extreme temperature recorded is 31.7 °C while in 2040, the estimated greatest temperature is 32.3 °C. There will be a 0.6 °C increase in temperature in 20 years. The demand in 2040 will be expanded 50.3% more than demand in 2020. The estimated electricity demand per capita will continue expanding because of the augmentation of the populace and the significance of electricity in daily activities. The pattern shows that electricity demand and generation in Malaysia will be expanding massively year by year.
The Biology and Research History of the Solitary Wasp Genus Bembix (Hymenoptera: Bembicidae): A Brief Review
Authors: Frank J A 
Published: November 2021

Abstract
Wasps of the genus Bembix (Fabricius) have enjoyed over 300 years as subjects of interest to entomologists and ethologists due to their large size and repertoire of dramatic nesting behaviors. This research history began with these wasps as the focus of brief behavioral accounts, which developed over time to yield detailed studies of the habits of individual species, as well as comparative studies of behavior. This work has revealed that Bembix is behaviorally diverse, with most aspects of their nesting habits showing variation both within and between species. Ultimately, this research history has made Bembix one of the best-known groups of solitary aculeate wasps. At the same time, much work remains to be done on Bembix. While the genus' behavioral diversity is well-recognized, it has not nearly been fully characterized, with the majority of Bembix species remaining unstudied in the field. Furthermore, no phylogeny has ever been published for the genus, and its evolutionary and biogeographic history remains essentially unknown. Thus, this review presents an overview of historical and biological information on Bembix with the aim of stimulating further work on this behaviorally diverse genus.
Adjusting COVID-19 Seroprevalence Survey Results to Account for Test Sensitivity and Specificity
Authors: Meyer Mark J , Yan Shuting , Schlageter Samantha , Kraemer John D , Rosenberg Eli S , Stoto Michael A 
Published: November 2021

Abstract
Population-based seroprevalence surveys can provide useful estimates of the number of individuals previously infected with serious acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and still susceptible, as well as contribute to better estimates of the case-fatality rate and other measures of coronavirus disease 2019 (COVID-19) severity. No serological test is 100% accurate, however, and the standard correction that epidemiologists use to adjust estimates relies on estimates of the test sensitivity and specificity often based on small validation studies. We have developed a fully Bayesian approach to adjust observed prevalence estimates for sensitivity and specificity. Application to a seroprevalence survey conducted in New York State in 2020 demonstrates that this approach results in more realistic—and narrower—credible intervals than the standard sensitivity analysis using confidence interval endpoints. In addition, the model permits incorporating data on the geographical distribution of reported case counts to create informative priors on the cumulative incidence to produce estimates and credible intervals for smaller geographic areas than often can be precisely estimated with seroprevalence surveys.
Effects of the Coronavirus Disease 2019 Pandemic on Human Immunodeficiency Virus Services: Findings from 11 Sub-Saharan African Countries
Authors: Harris Tiffany G , Jaszi Edward , Lamb Matthew R , Laudari Carlos A , Furtado Maria Lúcia Mendes , Nijirazana Bonaparte , Aimé Ndayizeye , Loni Ekali Gabriel , Ebiama Lifanda Lifanda , Brou Hermann , Ehui Eboi , Malele Bazola Faustin , Mboyo Aimé , Sahabo Ruben , Advocate Dlamini Nkhosikhona , Melaku Zenebe , Getachew Meselu Mirtie , Hawken Mark , Ngugi Catherine , Vitale Mirriah , Abudou Munira Abubakar Bin , Bayoa Florence , Achut Victoria , Kasonde Prisca , Munsanje Paul , El-Sadr Wafaa M 
Published: November 2021

AbstractBackgroundDue to concerns about the effects of the coronavirus disease 2019 (COVID-19 pandemic on health services, we examined its effects on human immunodeficiency virus (HIV) services in sub-Saharan Africa.MethodsQuarterly data (Q1, 10/2019–12/2019; Q2, 1/2020–3/2020; Q3, 4/2020–6/2020; Q4, 7/2020–9/2020) from 1059 health facilities in 11 countries were analyzed and categorized by stringency of pandemic measures. We conducted a difference-in-differences assessment of HIV service changes from Q1–Q2 to Q3–Q4 by higher vs lower stringency.ResultsThere was a 3.3% decrease in the number HIV tested from Q2 to Q3 (572 845 to 553 780), with the number testing HIV-positive declining by 4.9% from Q2 to Q3. From Q3 to Q4, the number tested increased by 10.6% (612 646), with an increase of 8.8% (23 457) in the number testing HIV-positive with similar yield (3.8%). New antiretroviral therapy (ART) initiations declined by 9.8% from Q2 to Q3 but increased in Q4 by 9.8%. Across all quarters, the number on ART increased (Q1, 419 028 to Q4, 476 010). The number receiving viral load (VL) testing in the prior 12 months increased (Q1, 255 290 to Q4, 312 869). No decrease was noted in VL suppression (Q1, 87.5% to Q4, 90.1%). HIV testing (P &lt; .0001) and new ART initiations (P = .001) were inversely associated with stringency.ConclusionsAfter initial declines, rebound was brisk, with increases noted in the number HIV tested, newly initiated or currently on ART, VL testing, and VL suppression throughout the period, demonstrating HIV program resilience in the face of the COVID-19 crisis.