bluuebunny/crossref_metadata_2025 huggingface dataset:
An Exploratory Study of Allied Health Students' Experiences of Electronic Medical Records During Placements
Authors: Baysari Melissa Therese , Wells Jacqueline , Ekpo Ernest , Makeham Meredith , Penm Jonathan , Alexander Nathaniel , Holden Alexander , Ubeja Raj , McAllister Sue
Published: April 2022

Background Allowing students to access and document in electronic medical records (eMRs) during clinical placements is viewed as critical for ensuring that graduates have a high level of digital proficiency prior to entering the workforce. Limited studies have explored student access to eMRs in health disciplines outside of medicine and nursing.

Objective Our main objective was to examine allied health students' experiences and perceptions of the opportunity to develop eMR competencies during their placement, across a range of allied health disciplines and placement settings.

Methods An explanatory sequential design was used, comprising a quantitative survey (n = 102) followed by qualitative semi-structured interviews (n = 6) with senior allied health students to explore their experiences and perceptions of eMR access during placements.

Results Of the 93 students who responded to the question about their placement eMR, nine (10%) reported their placement site did not use an eMR and four students reported that they were not allowed to access the eMR during their placement. Most students (64%, 54 out of 84) accessed the system using their own credentials, but 31% (26 out of 84) used someone else's log-in and password. Students were satisfied with the eMR training and support received while on placement, but there was significant variability across sites on the level of training and support provided. All students believed that eMR access was beneficial for learning and preparation for work, improved delivery of care, taking ownership of work, and feeling responsible for patient care.

Conclusion Providing students with access to eMRs during placements is fundamental to the development of a student's professional identity and to recognizing their role in the delivery of interprofessional patient care. For graduates to be equipped to effectively contribute to multi-disciplinary care in a digital health environment, universities need to work with practice partners to standardize and formalize eMR access, registration, training, and support, and to provide students with early exposure and training on eMRs in university courses.
Going beyond the AHA! moment: insight discovery for transdisciplinary research and learning
Authors: Pearce BinBin J. , Deutsch Lisa , Fry Patricia , Marafatto Francesco Femi , Lieu Jenny
Published: April 2022

In this paper, we develop and apply the concept of ‘insight discovery’ as a key competence for transdisciplinary research and learning. To address complex societal and environmental problems facing the world today, a particular expertise that can identify new connections between diverse knowledge fields is needed in order to integrate diverse perspectives from a wide range of stakeholders and develop novel solutions. The capacity for “insight discovery” means becoming aware of personal mental representations of the world and being able to shape and integrate perspectives different from one’s own. Based on experiences and empirical observations within the scope of an educational programme for Masters students, PhD candidates and post-doctoral researchers, we suggest that insights are the outcome of a learning process influenced by the collective and environment in which they are conceived, rather than instant moments of individual brilliance. The process which we describe, named the insight discovery process (IDP), is made up of five aspects. Within a group setting, a person begins with an “original mental model”, experiences an “insight trigger”, processes new information within the “liminal space”, “formulates an insight” and eventually forms an “adapted mental model”. There is a potential for incorporating such process as a fundamental competence for transdisciplinary curricula in undergraduate and graduate programmes by cultivating specific practices and safe learning environments, focused on the enquiry, exchange and integration of diverse perspectives.
Translating citizen-generated air quality data into evidence for shaping policy
Authors: Mahajan Sachit , Chung Ming-Kuang , Martinez Jenny , Olaya Yris , Helbing Dirk , Chen Ling-Jyh
Published: April 2022

The practice of participatory sensing for environment monitoring has rapidly evolved over the years. There has been a steady growth of citizen-based air quality monitoring projects that aim to build partnerships, knowledge-sharing platforms, awareness, and ultimately resilience to issues related to air quality. Whilst citizen science has reshaped air quality research by bringing a fresh perspective on democratizing science for the public good, there is little research about how citizen-generated data can be used for facilitating and improving evidence-based policymaking. To address the problem in a structured manner, we examine the existing literature related to citizen science, air quality, and policymaking to understand the existing gaps and opportunities. That is followed by a review of major grassroots and collaborative citizen science air quality monitoring initiatives in Asia, Africa, Europe, and Latin America. We explore the range of citizen science methods and applications to understand how they are creating opportunities for dialog between practitioners and policymakers, discuss the concerns about citizen-generated data, and see if the data is used for policy action. Finally, we propose a methodology for integrating data-based evidence into shaping policy. The methodology combines scientific evidence, participation, and deliberation to realize the full potential of citizen science in air quality monitoring.
Nanomaterial coating improves chemical sensor selectivity
Authors: Patrick Chris
Published: April 2022

An optical fiber coated with molybdenum disulfide can distinguish between ultralow concentrations of 12 different organic vapors
Assessment of repeated reference measurements to inform the validity of optical breast spectroscopy
Authors: Lloyd Rachel , Walter Jane , Pirikahu Sarah , Cadby Gemma , Hickey Martha , Sampson David D. , Karnowski Karol , Hackmann Michael J. , Saunders Christobel , Lilge Lothar , Stone Jennifer
Published: April 2022

Mammographic breast density is a strong breast cancer risk factor, and its routine clinical measurement could potentially be used to identify women at higher risk of breast cancer and/or monitor primary prevention strategies. Previous reports of optical breast spectroscopy (OBS), a novel approach to measuring breast density, demonstrated that it is safe (no ionizing radiation), portable, low-cost, and does not require image interpretation but have been limited to small, single-center studies. Reference measurements taken on a phantom breast prior to and after each woman’s OBS assessment are required for the calibration of the system transfer function as a part of processing participant data. To inform the validity of participant data, a detailed description of the reference measurements and a repeatability analysis of these measurements taken before and after participant assessment is presented. Reference measurements for OBS from 539 women aged 18–40 years were obtained as a part of a high-throughput epidemiological pilot study. Of these, measurements from 20 women with no useable data due to device failure (3.7%) were excluded and from another 12 women due to user error. The intra-class correlation (ICC) within complete pairs of reference data (taken before and after assessment) was high (all ICC > 0.84). The analysis presented here confirms the OBS participant data as valid for use in ongoing epidemiological research, providing further supporting evidence of OBS as a measure of breast density. A novel method of measuring breast density is needed to bridge large gaps in the knowledge of breast density in younger women and its relation to later-life breast cancer risk.
Local spin base invariance from a global differential–geometrical point of view
Authors: Emmrich Claudio
Published: April 2022

This article gives a geometric interpretation of the spin base formulation with local spin base invariance of spinors on a curved space-time and, in particular, of a central element, the global Dirac structure, in terms of principal and vector bundles and their endomorphisms. It is shown that this is intimately related to Spin and SpinC structures in the sense that the existence of one of those implies the existence of a Dirac structure and allows for an extension to local spin base invariance. Vice versa, as a central result, the existence of a Dirac structure implies the existence of a SpinC structure. Nevertheless, the spin base invariant setting may be considered more general, allowing for more physical degrees of freedom. Furthermore, arguments are given that the Dirac structure is a more natural choice as a variable for (quantum) gravity than tetrads/vielbeins.
Frame-guided assembly from a theoretical perspective
Authors: Raschke Simon , Heuer Andreas
Published: April 2022

The molecular self-assembly of various structures such as micelles and vesicles has been the subject of comprehensive studies. Recently, a new approach to design these structures, the frame-guided assembly, has been developed to progress toward fabrics of predefined shape and size, following an initially provided frame of guiding elements. Here, we study the frame-guided assembly in a two-dimensional membrane via computer simulations based on a single-bead coarse grained surfactant model in continuous space. In agreement with the experiment, the assembly process already starts for surfactant concentrations below the critical micelle concentration. Furthermore, upon increasing temperature, the formation process gets more delocalized. Additionally, the assembly process of the resulting membrane plane is modeled by a lattice gas model. It displays a similar phenomenology but additionally allows for the derivation of analytical mean-field predictions. In this way, a fundamental understanding of frame-guided assembly can be gained.
Photo-induced exfoliation—A facile synthesis route for atomristor prototype
Authors: Malavika C. , Manoj Kumar B. , Kannan E. S.
Published: April 2022

Brain inspired memory prototypes, such as atomristors, are touted as next generation two terminal memories for neuromorphic computation. To make rapid progress toward developing such atomic scale memory, a facile technique to fabricate atomristor prototypes has to be developed. In this work, one such simple and lithography free technique to fabricate an atomristor prototype using photoexfoliated monolayer molybdenum di-sulfide (MoS2) is illustrated. Resistive switching characteristics of the atomristor were demonstrated by applying a write voltage pulse of 10 (SET) and −5 V (RESET) for 100 s between the active tantalum di-sulfide (TaS2) and inert indium tin oxide electrodes. During the SET process (ON state), the Ta2+ ions from the active electrode diffuse through monolayer MoS2 to create a number of parallel conducting channels. The persistence of the conducting channel even after removing the SET bias drives the atomristor to the low resistance state. On applying the “RESET” bias, the device resistance increased by a factor of five possibly due to the rupturing of the conducting channel. On cyclically applying the “SET” and “RESET” biases, the device was switched between low and high resistance states with excellent repeatability. Interestingly, it was also observed that the switching ratio increased on increasing the SET bias making this device a promising candidate for realizing tunable write once read many (WORM) memory devices.
Quantitative evaluation of plasma-damaged SiN/Si structures using bias-dependent admittance analysis
Authors: Kuyama Tomohiro , Urabe Keiichiro , Eriguchi Koji
Published: April 2022

Plasma process-induced damage (PID) to SiN dielectric films was investigated by using an impedance (admittance)-based technique. Multi-layered equivalent circuits were introduced to assign the spatial and energy distribution of defects created in the SiN/Si system. We propose to use admittance as the principal parameter for damaged SiN/Si systems after Ar and He plasma exposures. The change in the border trap density was determined from the admittance in accumulation, whereas the interface state density and energy profile that was created was determined from the admittance in depletion. Plasma source-dependent damage-creation mechanisms are discussed. It was found that the extracted border trap density in the He plasma-damaged sample was larger than that in the Ar plasma-damaged sample under the same ion dosage. The proposed characterization scheme is useful for assessing PID to dielectric/Si systems.
A first-principles study on the electrical conductivity of Ag2S1−xSex (x = 0, 0.25, 0.5): Electron–phonon coupling
Authors: Nam Ho Ngoc , Suzuki Katsuhiro , Masago Akira , Nguyen Tien Quang , Shinya Hikari , Fukushima Tetsuya , Sato Kazunori
Published: April 2022

The development of flexible thermoelectric devices is gradually attracting increasing attention, particularly in the field of material design. In this study, we use first-principles calculations combined with Boltzmann equations to study the electronic and transport properties of Ag2S1−xSex, a key material with many important properties and extraordinary ductility, as well as a wide range of thermoelectric applications. The effect of Se alloying on the electronic structure of Ag2S and defect formation is investigated, and the role of alloying in increasing the n-type carrier concentration is discussed. The electron–phonon coupling approximation is used to reproduce the experimentally observed transport properties reasonably well, which shows that this scattering model is suitable for predicting the transport properties of semiconductors in thermoelectric applications.
The stability of expanding reactive shocks in a van der Waals fluid
Authors: Calvo-Rivera A. , Huete C. , Velikovich A. L.
Published: April 2022

Despite the extensive literature accumulated since the pioneering works of D'yakov and Kontorovich in the 1950s, the stability of steady shocks is still an open question when realistic boundary conditions are accounted. The consideration of a supporting mechanism, which is indeed a necessary condition for shock steadiness, modifies the perturbation shock dynamics in the unstable range. The Noh problem is a suitable example to form steady expanding shocks. This configuration is of great interest to the high-energy-density-physics community because of its direct application to inertial confinement fusion and astrophysics, for which the stagnation of a supersonically converging material via an accretion shock front is ubiquitous. In this work, we extend the generalized Noh problem, both base-flow solution and linear stability analysis, to conditions where endothermic or exothermic transformations undergo across the shock. Within the spontaneous acoustic emission conditions found for a van der Waals gas [J. W. Bates and D. C. Montgomery, “The D'yakov-Kontorovich instability of shock waves in real gases,” Phys. Rev. Lett. 84, 1180 (2000)], we find that cylindrical and spherical expanding shocks become literally unstable for sufficiently high mode numbers. Counterintuitively, the effect of exothermicity or endothermicity across the shock is found to be stabilizing or destabilizing, respectively.
A hydraulic model for flow rate ratio of triple cannulation extracorporeal membrane oxygenation
Authors: Wu Fan , Wang Hongping , Wang Chunyu , Xu Duo , Wang Shizhao
Published: April 2022

Triple cannulation extracorporeal membrane oxygenation (ECMO) provides advanced life support to patients with respiratory and hemodynamic failure by replacing the function of the heart and lungs. The application of triple cannulation ECMO suffers from the difficulty in predicting the flow rate ratios of the cannulas. We address this difficulty by proposing a hydraulic model, where the effects of the triple cannulation are modeled by head losses in a bifurcated tube. The proposed model correctly predicts the flow rate ratios and quantitatively captures the effects of geometrical parameters. This model can help to configure the cannula pair for clinical practices and interventional therapy.
Experimental study of the impact of splash closure on the cavity evolution behind a sphere entering water
Authors: Zhang Q. , Zong Z. , Li H. T. , Sun T. Z.
Published: April 2022

In this paper, we conduct an experimental study on the cavity evolution behind a hydrophobic sphere entering the water. It is found that there is a correlation between splash and cavity evolution. Two dominant regimes for cavity pinch-off, including hydrostatic pressure and pressure pulsation inside cavity, are confirmed. When the splash is removed by a guard, the cavity pinch-off is dominated by hydrostatic pressure. The theoretical model is well consistent with the experimental results, including the cavity profile and the dimensionless pinch-off depth. However, when the splash domes, the theoretical solution fails with the increase in the effect of pressure pulsation inside the closed cavity. With the increase in the Froude number Fr, the splash closure most significantly impacts the necking position. The impact of the splash closure is dependent of Fr, and there is a critical value of Frcri separating the deep pinch-off into two regimes. The critical value of Frcri = 134 is theoretically proposed, which is a reasonable predication for the present experimental observations. In addition, the expansion rate of cavity volume is measured to confirm the transition of distinct regimes. Based on our theoretical analysis, the critical expansion rate is determined as 4.9, which agrees well with present experimental result 4.6. Distinct pinch-off regimes significantly impact the subsequent cavity evolution and the forces on sphere. A deep seal controlled by hydrostatic pressure is constantly accompanied by severe cavity resonance and a dramatic decrease in the cavity length, whereas pinch-off controlled by pressure pulsation leads to weak ripples.
Transition metal doping enhances catalytic selectivity and activity of Pt13 nanoclusters for the reduction of CO2 to CO
Authors: Niu Weibing , Wu Jiaojiao , Chen Chunguang , You Yuqing , Zhu Yuanzheng , Lu Lingzhu , Cheng Ping , Zhang Shuping
Published: April 2022

Electrochemical CO2 reduction to value-added chemicals provides an efficient way to lower global warming if using efficient and selective electrocatalysts. However, the search and design of such electrocatalysts remain a considerable challenge. Here, in this work, the performance of Pt13−nMn (M = Mn, Fe, Co, Ni, Cu, and Zn) bimetallic catalysts was systematically studied in this work using spin-polarized density functional theory calculations. The Gibbs free energy results show that the doping of Mn to the Pt clusters was more beneficial to the improvement of the catalyst activity, following is the addition of Zn and Co. Among all the clusters, 15 nanoclusters are promising catalysts with a barrier of ΔG <1 eV. The Pt8Mn5, Pt2Mn11, and Pt11Mn2 are the three most promising catalysts with the barrier of only 0.148, 0.237, and 0.286 eV, respectively, displaying all more than 1 eV lower than that of pure Pt13. For most of the Pt13−nMn (M = Mn, Fe, Co, Ni, Cu, and Zn) systems, the desorption of CO is the rate-limiting step. The d band center of Pt8Mn5 is far from the Fermi energy level, which causes CO detachment more easily from Pt8Mn5. Pt8Mn5 exhibits superior catalytic activity toward CO. The study can be used to guide the design of bimetallic catalysts in the future.
Election 2022 should address unfinished business in health and aged care
Authors: Duckett Stephen
Published: April 2022

The 2022 federal election is critical for the health and aged care sectors. Both parties need to address the COVID care deficit, oral health care, and commit to fix the aged care mess. The ongoing tragedy of First Nations health should also remain a priority. And a bipartisan acceptance of the need to address climate change is also required.
Spatial heterogeneity of the seed bank at a peat lake in Australia
Authors: Ling Joanne E. , Wen Li , Ellis Ben , Krogh Martin
Published: April 2022

Context In the face of global biodiversity decline, understanding the effects of potential climate change on the persistence of soil seed banks is critical, especially in wetland ecosystems. Although studies have explored the response of soil seed banks to changes in periodically inundated wetlands, little is understood about seed banks in peatlands. Aims We examined the spatial variability of soil seed banks during a recent drying event, the last of which occurred over 60 years ago. Methods We sampled the soil seed bank in three zones away from the centre of the dry lakebed at five depth intervals down to 50 cm. Key results Our study showed that the seed bank distribution in a peatland reflected the wetland plants examined at the time of the drying event. The distribution of seeds was along a flood gradient, suggesting an interaction between historical inundation intensity (Zone) and vertical (Depth) distribution of seeds, and correlated with the extant vegetation, as determined during a significant water drawdown period. Conclusions and implications This study shows that the ability of seeds to survive burial, either submerged or desiccated, even after long periods, may prove to have advantages for plant survival and establishment.
Estudio cognitivo e intercultural del eufemismo chino y español de muerte
Authors: Dai Xin
Published: April 2022

Abstracta

Dadas las características generales e intemporales a nivel universal del tabú de la muerte, este artículo tiene el
objetivo de realizar un análisis contrastivo del eufemismo en chino y español de este tema a través de asociaciones
conceptualizadas de metáfora, metonimia y su interacción. La base teórica en la que se sustenta el estudio deriva del modelo
cognitivo propuesto por Lakoff & Johnson en 1980 en su célebre libro
Metáforas de la vida cotidiana. Construimos diez principales mecanismos comunes y tres específicos
respectivos de proyección conceptual en ambas lenguas respecto a dicho tema. Al final, basándonos en las muestras resultantes,
concluimos con la importancia de las características de la cultura material, la psicológica y la institucional de ambas regiones a
la hora de desarrollar manifestaciones eufemísticas de la muerte.
Corpus-based bilingual terminology extraction in the power engineering domain
Authors: Ivanović Tanja , Stanković Ranka , Todorović Branislava Šandrih , Krstev Cvetana
Published: April 2022

This paper presents the resources and tools used to extract and evaluate bilingual, English-Serbian terminology in
the power engineering domain. The resources consist of existing general and domain lexica, and a domain parallel corpus; tools
include term extractors for both languages and a tool for aligning the segments belonging to corpus sentences. The system was
tested by varying a match function that establishes the presence of an extracted term in an aligned segment (a chunk), ranging
from very loose to strict. The evaluation of results showed that the precision of English term extraction was 92%, Serbian term
extraction 86%, while the precision of bilingual pair extraction was 72% based on the strictest match function. The result of
extraction was 2,684 correct bilingual pairs that enhanced the terminology database and can further be used to support the search
of the power engineering aligned collection stored in a digital library.
Enhancing photon entanglement in a three-mode optomechanical system via imperfect phonon measurements
Authors: Qiu Jing , Chen Dongni , Wang Ying-Dan , Chesi Stefano
Published: April 2022

By considering a 3-mode optomechanical system formed by two cavities interacting with a common mechanical mode, we demonstrate that phonon-counting measurements lead to a significant enhancement of entanglement in the output of the two cavities. This conclusion still holds for an inefficient detector, but the dependence on system parameters changes qualitatively from the ideal limit of perfect projective measurements. We find non-trivial optimal points for the entanglement as functions of detector efficiency, measurement outcome, and optical drive strengths. We characterize both the highest achievable entanglement as well as a ‘typical’ value, obtained at the most likely measurement outcome. Numerical results are well understood within an approximate analytical approach based on perturbation theory around the ideal detector limit.
Angstrom-precise fabrication of surface nanoscale axial photonics (SNAP) microresonators with a flame
Authors: Sumetsky Misha , Vassiliev Victor
Published: April 2022

We demonstrate the fabrication of surface nanoscale axial photonics bottle microresonators with angstrom precision using a flame. We observe strongly unscalable behavior of the whispering gallery mode cutoff wavelengths with different radial quantum numbers along the fibre length.
SOC Estimation of Lithium-ion Battery Based on RLS-EKF for Unmanned Aerial Vehicle
Authors: Zhang Shuaishuai , Tao Hongfei , Bi Kaitao , Yan Wenxu , Ni Hongyu
Published: April 2022

In recent years, in the civil and military unmanned aerial vehicle(UAV) market, the demand for UAV is increasing day by day, the iteration cycle of UAV products is significantly shortened, and UAV has developed rapidly. Among them, lithium battery has the advantages of high energy density, lightweight and bendability. At present, as the main power source of electric UAV, lithium battery affects the range and flight time of UAV, and is the key factor that directly restricts the development and application of UAV. Therefore, accurate estimation of battery state of charge (SOC) has always been the focus and difficulty in the field of UAV battery research. This paper mainly improves the accuracy of SOC estimation of power battery from the following aspects:

First, the significance of researching power batteries is clarified, the advantages of lithium-ion power batteries are pointed out, the definition of SOC and its influencing factors are discussed, and the common methods of battery SOC estimation are more comprehensively introduced and analyzed.

Next, a second-order RC network equivalent circuit model that is convenient for engineering realization is established, and its state-space model is deduced. The SOC-OCV relationship was measured.

Then, the recursive least squares (RLS) method suitable for real-time calculation is used to identify the parameters of the equivalent circuit model of lithium-ion battery on-line, and the parameters of the equivalent circuit model are identified under UDDS conditions, which proves the correctness and rationality of the identification method.

Finally, it is proposed to use the extended Kalman filter (EKF) algorithm to estimate the SOC of the lithium-ion battery, that is, use the EKF algorithm to estimate the open circuit voltage of the battery, and then estimate the battery SOC according to the open circuit voltage method. The accuracy of the joint estimation algorithm to estimate SOC is verified under simulated conditions.
Design of Intelligent Wireless Laser Engraving Machine
Authors: Zhang Yan , Feng Bin , Sang ShengJu
Published: April 2022

The wireless laser engraving machine system is designed by using the wireless data transmission and programming processing ability of MCU esp8266. The browser of computer accesses the micro web server built in MCU through wireless channel to realize real-time control of engraving.

MCU establishes and maintains the Wi-Fi channel for computer connection. The computer browser downloads and runs the HTML5 Web APP stored in MCU flash memory to generate the operation interface. The APP completes the image loading, graying, binarization, thinning, vectorization and other processing. In the browser, the final G-codes are generated and sent back to MCU in real time. The MCU executes G-codes line by line. According to the intention of G-codes, MCU uses linear interpolation algorithm to control stepping motor and PWM to control laser intensity. Finally, the engraving or cutting is completed in a perfect way.

The core hardware circuit requires only one MCU and two driver ICs. So the design is portable, easy to be assembled, precise to be controlled and low cost. And the open software architecture makes it more extensible, compatible and easy to be deployed.
The Detection and Following of Human Legs Based on Feature Optimized HDBSCAN for Mobile Robot
Authors: Liu Penghua , Yao Hanchen , Dai Houde , Fu Wei
Published: April 2022

Accurate target recognition and stable follow in real clutter environment are important tasks for following a random robot. In this paper, a scheme of detecting and tracking human legs using a single lidar is proposed. The HDBSCAN algorithm is optimized by human leg characteristics, and the leg line features are fused on the basis of the density characteristics of the leg laser radar data, and the leg information of the target is clustered and its location is obtained. Based on the relative shift angle of target moving and the lock-in algorithm of tracking distance, the single target detection and tracking in unstructured environment can be realized. The lidar dataset in multiple scenes verifies that the clustering algorithm based on feature optimization improves the accuracy of target legs detection by more than 10% compared with the original algorithm. The scheme performs follow-up experiments on a self-built solid robot. The experimental results show that the robot can achieve accurate and stable human target follow in clutter environment.
Optimal scheduling of electric vehicle aggregators based on sac reinforcement learning
Authors: Yu Fancheng , Lao Penghui
Published: April 2022

Aiming at the optimal scheduling problem of electric vehicle aggregators, a charge change load optimal scheduling strategy based on sac deep reinforcement learning is proposed. The strategy fully considers the users, power system and power market in the process of load regulation, and can realize the friendly interaction between electric vehicle and power system. Based on the establishment of the joint optimal scheduling framework of charging pile and exchange station, considering the multiple temporal and spatial characteristics of optimal scheduling of charging and exchange station, the optimal scheduling model of adjustable charging and exchange load in different scenarios is constructed, and the real-time scheduling scheme of grid connected charging and exchange load is solved based on sac algorithm. An example is given to verify the economy and efficiency of sac algorithm applied to the real-time optimal scheduling of charging and changing load of large-scale electric vehicles.
Multi-sensor fusion of sparse point clouds based on neuralnet works
Authors: Yang Qiming , Liu Fei , Qu Jingjing , Jing Hui , Kuang Bing , Chai Wenjing
Published: April 2022

The fusion of laser point cloud and visual image depends on the point cloud density and the target framing effect, the traditional laser point cloud processing for sparse point cloud clustering effect is poor, it is difficult to frame small objects as well as medium and long distance objects. Then the subsequent sensor fusion is easy to miss the recognition of obstacles. In this paper, we improve the frame selection method for sparse point clouds, firstly build a deep learning framework pointpillar, use pointpillar to frame the sparse laser point clouds, then spatially calibrate the lidar coordinate system and camera coordinate system, project the lidar point clouds to the camera image, improve the late fusion method, effectively use the detection results of single sensor, and finally The late-fusion is performed with the target detection results of the camera image to output the exact distance as well as the category of the target. Experiments show that compared with the recognition effect of the traditional fusion algorithm, the number of frames is increased by 6 and the missed recognition rate is reduced from 31.41% to 12.31%.
Centralized Control System for Smart Street Lights Based on STM32 and LoRa
Authors: Qu Yuanchi , Yang Yanhua , Li Yaoyao
Published: April 2022

In order to solve the problem of waste of power and human resources in the traditional street lamp control system, this paper designs a smart street lamp centralized control system based on STM32 and LoRa technology. The centralized control system consists of a centralized control device and multiple single lamp control devices. The STM32F103 is the MCU of the centralized control device. The system uses the characteristics of low communication cost and long transmission distance of LoRa technology to realize the communication between the centralized control device and the single lamp control device. The centralized control device uses the Modbus RTU protocol to communicate with the sensor module, and adjusts according to environmental factors. The brightness of the street lamp realizes the "on-demand lighting" of the street lamp, and an adaptive rate algorithm is proposed to optimize the communication of the LoRa network and improve the working efficiency of the system. This centralized control system combines embedded and wireless communication technology and has advantages in cost, reliability, energy saving and intelligent control. It can be applied to street lamp lighting control in various environments. It has a high degree of intelligence and has a strong market potential.
Workspace Analysis of Cable-driven Continuum Manipulator with Cable-constrained Synchronous Rotating Mechanism
Authors: Zhou Zhen , Zheng Xudong , Chen Zhang , Wang Xueqian , Liang Bin , Wang Qi
Published: April 2022

In this paper, a cable-driven continuum manipulator with cable-constrained synchronous rotating mechanism (CCSRM) is studied. The purpose of this paper is to give the workspace for the cable-driven continuum manipulator, where the friction effects and the allowable range of cable tension are considered. The problem of solving workspace is transformed into a linear programming problem, which is solved by dual-simplex algorithm. On this basis, the influence of the pre-tightening force of the connecting cable on the workspace is analyzed. In addition, the tension of the motor on each driving cable is optimized to minimize the control error. Finally, the load range that the manipulator can withstand within the workspace is analyzed.
Electronic Differential Control System Based on Particle Swarm Optimization and PID Control
Authors: Yang Dongxue , Lu Huacai , Zhang Chenyan
Published: April 2022

For the front wheel steering, the control effect of the four-wheel hub-driven electric vehicle driven by the rear wheel is not accurate and stable. It is proposed to replace the traditional PID control system with the particle swarm algorithm to realize the online optimization of the PID regulator parameters. The simulation model of the improved system is built in MATLAB. Compared with the conventional PID control method, the results show that the improved four-wheel drive system has a smaller slip ratio between the left rear wheel and the right rear wheel, which improves the directional stability and braking efficiency of the wheel electric vehicle.
Research on Distribution Network Fault Location based on Improved Genetic Algorithm
Authors: Wang Hao , Mei Kaifeng , Zhu Chao , Zhai Chengjian , Li Meng
Published: April 2022

Compared with the traditional recloser fault location without communication channel, feeder automation based on FTU is in line with the development of modern distribution system. FTU plays a key role in the whole system, but the location is inaccurate due to the lack of information caused by FTU itself or communication fault. When using genetic alogrithms for distribution network fault location, the result often converges prematurely or converges to an infeasible solution due to algorithm reasons. Aiming at the above problems, an improved genetic algorithm is proposed for distribution network fault location. Through simulation analysis, it can be found that the improved genetic algorithm has high convergence and good optimal fitness, which can better solve the convergence problems of the unmodified algorithm, which is of great significance for distribution network fault location.
Research on fronthaul scheme based on DRoF
Authors: Feng Chenwei , Sun Yu , Su Youmei , Jiang Fuchun , Tao Lin , Ji Huazhi
Published: April 2022

With the rapid increase of global data traffic, storage and transmission of massive data is a challenging problem. Therefore, data compression is necessary. Based on DRoF, mobile fronthual has the advantages of high data rate, good connectivity and system capacity, and becomes the key part of communication system transmission. In this paper, an optimized vector quantization data compression algorithm based on DRoF system is proposed, which mainly studies OFDM baseband modulation signals. Firstly, the modulation signal is transformed by DCT. Then the optimized fast-global K-means clustering algorithm is used for quantization to overcome the problem that the original algorithm may choose noise points as the cluster center. Finally, Huffman coding is used to reduce the code length of the quantized data. Simulation results show that the proposed algorithm has good CR and EVM performance within the error tolerance range. It has a high degree of compression and signal recovery.
Research on Cooperative Control for Multi-motor System of Space Climbing Robot
Authors: Yin Yecheng , Yan Guodong , Huang Yuping , Chen Zhihong , Yu Zhiyuan , Jia Longfei
Published: April 2022

A system model of space climbing robot with dual power units is established and three control strategies for motors are presented in this study. The simulation results show that the robot has a certain fault tolerance for the speed synchronization of motors, and voltage difference on motors can achieve dynamic balance of power. Control strategy based on voltage synchronization, control strategy based on current synchronization and control strategy based on current following have been proposed. The simulation results show that those control strategies can effectively distribute the system power. Among them, the control strategy based on voltage synchronization is the simplest and has the best effect. It provides a reference for further research on the control method of multi-motor climbing robot.
Temporal Logic Control Synthesis for Distributed Multi-Agent Cooperative Tasking
Authors: Xu Ning , Peng Ting , Liu Dawei , Li Jie
Published: April 2022

In this work, we present a novel control synthesis method for cooperative multi-agent systems to fulfill a global mission given as linear temporal logic on finite traces (LTLf). The proposed method first synthesizes satisfiable global controllers for uncontrolled system, such that the global specification is met; and then, searches for a decomposable global controller among them over a maximum synchronization scheme; finally, further refining the synchronization scheme to obtain decomposed distributed controllers. To search for a decomposable global controller among the satisfiable ones, we present an informed searching algorithm based on the decomposability analysis of global controllers. A multi-UAV cooperative fire surveillance scenario is developed to illustrate the method.
Federal SNN Distillation: A Low-Communication-Cost Federated Learning Framework for Spiking Neural Networks
Authors: Liu Zhetong , Zhan Qiugang , Xie Xiurui , Wang Bingchao , Liu Guisong
Published: April 2022

In recent years, research on the federated spiking neural network (SNN) framework has attracted increasing attention in the area of on-chip learning for embedded devices, because of its advantages of low power consumption and privacy security. Most of the existing federated SNN frameworks are based on the classical federated learning framework -- Federated Average (FedAvg) framework, where internal communication is achieved by exchanging network parameters or gradients. However, although these frameworks take a series of methods to reduce the communication cost, the communication of frameworks still increases with the scale of the backbone network. To solve the problem, we propose a new federated SNN framework, Federal SNN distillation (FSD), whose communication is independent of the scale of the network. Through the idea of knowledge distillation, FSD replaces the network parameters or gradients with the output spikes of SNN, which greatly reduces the communication while ensuring the effect. In addition, we propose a lossless compression algorithm to further compress the binary output spikes of SNN. The proposed framework FSD is compared with the existing FedAvg frameworks on MNIST, Fashion MNIST and CIFAR10 datasets. The experiment results demonstrate that FSD communication is decreased by 1-2 orders of magnitude when reaching the same accuracy.
2D Pose Estimation Based on Deep Learning for Mobile System
Authors: Liu Yan , Wang Jingwen , Li Yujie , Li Guangwei , Tang Gaopeng
Published: April 2022

Pose estimation is the detection of human action poses, which is an important task of computer vision. The requirements of tasks such as unmanned driving and intelligent surveillance have also contributed to the development of human pose estimation. In this context, deep learning (DL) has a remarkable impact on human pose estimation. In this study, we investigate a pose estimation algorithm called convolutional pose machines (CPM) and implement it on a mobile platform (i.e., Android). By combining the classical CPM and the mobile deep learning framework Mobile AI Compute Engine (MACE), the model is deployed to the mobile platform to estimate the human pose directly and locally on the mobile phone without relying on the Internet. Thus, the proposed method can achieve effective performance while protecting users’ personal data. Experimental results on real-world data validate that this system has achieved the expected results of accurate recognition of common actions with a simple interface.
Research on Job-shop Scheduling Problem Based-on Improved Genetic Algorithm
Authors: Wei Bo , Qi Jiayuan , Wen Jiafu
Published: April 2022

Considering minimizing completion time and maximizing equipment utilization of job shop scheduling problem, an improved genetic algorithm was proposed. First, constructing a two-layer chromosome coding structure, with which the initial population quality and the diversity of the population were strengthened and improved. Next, in order to enhance the local search ability and improve the algorithm convergence speed, the population generated after selection, crossover, and mutation was divided into families, and the elite population were combined with explosive fireworks of the firework algorithm. Then, in order to prevent the algorithm from maturing prematurely, the disadvantaged groups were mutated through(by) the dynamic mutation mechanism to narrow the gap between the super individual and the average. Last, the parameters of the algorithm were optimized by orthogonal tests, and performance of the algorithm was verified by classical test examples.
Observer-based Finite-time Boundedness of Itô Stochastic Markov Jump Systems with Time-varying Delay
Authors: Liu Xiao , Liu Ningzhe , Li Yan
Published: April 2022

This paper is concerned about the problem of observer-based finite-time boundedness (OBFTB) of
Itô
stochastic Markov jump systems (MJSs) with external disturbances and time-varying delay. To begin, an observer-based controller (OBC) is constructed to assure finite-time boundedness (FTB) of the closed-loop system. Then, using linear matrix inequalities (LMIs), the state feedback gains and observer gains are calculated. Eventually, a numerical example is provided to demonstrate the value of the obtained results.
An MPF Based Aerial Platform Tracking Method for Road Network Targets
Authors: Yuan Jing , Chen Xin , Zhang Min , Zhang Pengfei
Published: April 2022

This paper presents a new algorithm to improve the tracking accuracy of the aerial mobile observation platform by using road information constraints. Combined with the road information and Mixed Particle Filter(MPF) algorithm, the Road Constrained Mixed Particle Filter(RCMPF) algorithm is proposed. RCMPF algorithm can effectively solve the problem of non-linear observation equation of aerial observation platform and realize the tracking of ground targets. The simulation results show that the algorithm improves the tracking accuracy of the target.
Detection of Chip Layered Defects Based on Dual Focus Mechanism
Authors: Chen Shuguang , Gao Jingyang , Zhao Di , Xu Pinjie , Zhang Tian
Published: April 2022

Chip layering defects affect the performance of chips and lead to the failure of chips, so chip layering defects detection is an important step in the quality acceptance of chip production. Chip layering defects, which are characterized by insignificant color change in defect area, small defect area and difficult localization, bring challenges to traditional detection. In recent years, deep learning has shown its powerful ability to solve complex problems in computer vision. In this paper, semantic segmentation method is used to study the problem of chip hierarchical defect detection. Dual focus mechanism first applies whiteboard network structure to identify the true hierarchical area. Afterwards the defective layer area and the original map, the layered defect is recognized in the whiteboard attention. Since the contrast of the layered defect is not obvious, the precise layered defect tag extraction is another important factor affecting network performance. Based on the fuzzy-c-mean clustering algorithm and expert acceptance principle, obtaining the precise layered defect label, the practicality of this method is further enhanced. The effectiveness of the method for detecting the chip layering defects is verified by testing the chip image provided by Huawei.
A Prediction Model of Alloy Yield in RH Furnace Based On SSA-ELM
Authors: Guo Jiaqing , Liu Huikang , Chai Lin
Published: April 2022

Aiming at the problem that it is difficult to predict the alloy yield in the RH furnace refining process, an alloy yield prediction model based on a sparrow search algorithm (SSA) optimized ELM neural network is proposed. Firstly, because the dimensions of input parameters are different, 11 input features are reduced by factor analysis (FA), and 5 input features are obtained. Then, through the sparrow search algorithm with fast convergence, high precision, and good stability, the input weight value and threshold of the ELM neural network are optimized, the SSA-ELM alloy yield prediction model is established, the alloy yield is predicted, and the off-line operation of the model is realized, which provides a theoretical basis for the prediction of alloy yield in the actual production process. Finally, by comparing the simulation results with the actual production data, it is found that the prediction results of the target element alloy yield predicted by the SSA-ELM are within the error range, and the prediction accuracy is higher than that of the ELM prediction model, which verifies the feasibility and effectiveness of the model.