bluuebunny/crossref_metadata_2025 huggingface dataset:
Novel machine learning approaches for improving the reproducibility and reliability of functional and effective connectivity from functional MRI
Authors: Mellema Cooper J , Montillo Albert A
Published: November 2023

Objective. New measures of human brain connectivity are needed to address gaps in the existing measures and facilitate the study of brain function, cognitive capacity, and identify early markers of human disease. Traditional approaches to measure functional connectivity (FC) between pairs of brain regions in functional MRI, such as correlation and partial correlation, fail to capture nonlinear aspects in the regional associations. We propose a new machine learning based measure of FC (
ML.FC
) which efficiently captures linear and nonlinear aspects. Approach. To capture directed information flow between brain regions, effective connectivity (EC) metrics, including dynamic causal modeling and structural equation modeling have been used. However, these methods are impractical to compute across the many regions of the whole brain. Therefore, we propose two new EC measures. The first, a machine learning based measure of effective connectivity (
ML.EC
), measures nonlinear aspects across the entire brain. The second, Structurally Projected Granger Causality (
SP.GC
) adapts Granger Causal connectivity to efficiently characterize and regularize the whole brain EC connectome to respect underlying biological structural connectivity. The proposed measures are compared to traditional measures in terms of reproducibility and the ability to predict individual traits in order to demonstrate these measures’ internal validity. We use four repeat scans of the same individuals from the Human Connectome Project and measure the ability of the measures to predict individual subject physiologic and cognitive traits. Main results. The proposed new FC measure of
ML.FC
attains high reproducibility (mean intra-subject R
2 of 0.44), while the proposed EC measure of
SP.GC
attains the highest predictive power (mean R
2 across prediction tasks of 0.66). Significance. The proposed methods are highly suitable for achieving high reproducibility and predictiveness and demonstrate their strong potential for future neuroimaging studies.
The Impact of Teaching Simple Harmonic Motion Supported by A Smartphone-based Sensor on Students’ Conceptual Mastery
Authors: Arum A S , Suana W , Permadi D
Published: November 2023

One of the common challenges encountered when conducting physics experiments is ensuring measurement accuracy. Conversely, the emergence of smartphone-based sensor applications presents an opportunity to address these issues. Thus, this research aimed to assess the effectiveness of Physics Toolbox Sensor Suite (PTSS), a smartphone-based sensor, in enhancing students’ conceptual mastery of simple harmonic motion. The study employed a non-equivalent control group design, with a valid and reliable multiple-choice test as the research instrument. The sample comprised 70 2nd grade students from a public senior high school in Indonesia, with 35 students for each experimental and control group. The research was conducted during the Even Semester of the 2022/2023 Academic Year at a public high school in Lampung Province. Both groups were instructed using the same pedagogical approach-discovery learning. However, the experimental group conducted experiments aided by PTSS, while the control group did not. N-gain analysis revealed a greater increase in conceptual mastery within the experimental class compared to the control class. The average n-gain for the experimental group was 0.74, whereas for the control group, it was only 0.64. Furthermore, the Mann-Whitney test indicated an Asymp. Sig. (2-tailed) value of 0.004, smaller than 0.05, suggesting that smartphone-based sensors like PTSS could facilitate simple harmonic motion experiments and enhance students’ conceptual mastery.
Simulation of Hypothetical Radiological Accident at Potential Nuclear Power Plant Sites in Malaysia
Authors: Jamaludin A F , Karim M K A , Kechik M M A , Shah N M , Harun M H , Kamal I
Published: November 2023

After any nuclear incident, the main concern for human well-being is the extent of radiation released beyond the site. This study simulated a similar scenario on three potential nuclear power plant sites in Malaysia, using the Fukushima Daiichi Nuclear Power Plant incident as a reference. The computer model Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) was used to simulate and track the movement of air parcels and the dispersion of radioactive emissions. HYSPLIT analyzed the dispersion profile of radioactive materials, revealing that in S1, S2, and S3, the maximum ground dose was 7.9 mSv, 28.0 mSv, and 7.6 mSv, respectively. The maximum activity deposited on the ground was 62 MBq, 210 MBq, and 14 MBq for S1, S2, and S3, respectively. The analysis of ground deposition indicated that S1 covered an estimated area of 1500 km2, S2 covered 3025 km2, and S3 had the largest coverage of approximately 4537 km2. Overall, this study demonstrates that the hypothetical accident would contaminate the vicinity of the three potential nuclear power plant (NPP) sites.
Initial Finite-Difference Time-Domain (FDTD) Modeling of Graphene Based on Intra-band Surface Conductivity
Authors: Tola P S , Wardhani P C , Islamiyah S
Published: November 2023

Graphene is a single two-dimensional layer of carbon atoms arranged in a hexagonal lattice, possesses interesting optical properties, and has potential for applications in optical devices. Graphene exhibits tunable surface conductivity, which arises from its electronic band structure. Graphene surface conductivity is determined by its chemical potential, which can be controlled by bias voltage and/or chemical doping. The tunability of surface conductivity allowed to tailored optical properties of graphene, making it a controllable material for optoelectronic applications. Graphene surface conductivity is applied to update the field values at each time step in the Finite-Difference Time-Domain (FDTD) method, enabling us to visualize electromagnetic (EM) wave propagation in graphene. The current article serves as a starting point for developing the FDTD approach to simulate EM wave interactions with graphene, particularly at low frequencies. In this study, we use the Kubo formula for low EM wave frequency (10-105 GHz) at ambient temperature to calculate the intra-band surface conductivity of graphene. The outcome shows that the imaginer’s intra-band surface conductivity value is relatively considerable compared to the actual value at frequencies between 102 and 104. Moreover, the chemical potential exhibits a positive linear relationship with the imaginer intra-band surface conductivity and the intra-band conductivity falls to zero as the frequency rises to NIR.
A Profile of senior high school student’s critical thinking skills in physics learning
Authors: Neswary S B A , Prahani B K , Marianus  , Wibowo F C , Uulaa R F R
Published: November 2023

In the 21stcentury, students are required to have skills, one of which is Critical Thinking Skill (CTS) in physics learning. Physics aims to master concepts and principles to solve problems by applying critical thinking skills in physics learning. This study aims to analyze the CTS profile of Senior High School (SHS) in physics learning. This current research is pre-research with 107 of 10thgrade students as participants. This research was conducted in a high school in Indonesia. CTS has four indicators: interpretation, analysis, evaluation, and inference. In this study, the CTS profile of high school students in physics learning is still low. The implications of this study can be used as a bridge as clear evidence that the CTS of SHS students in physics learning is still low and needs to be leveled up.
Design of Multi-band Microstrip Antenna with Rectangular Patch for 2.3 GHz, 2.4 GHz, and 3.5 GHz Frequencies
Authors: Katsirotin  , Rahayu V
Published: November 2023

Cellular developments encourage the integration of both 4G, Wi-Fi, and 5G network technologies into one device; an antenna is a tool that can be used to support the integration of these networks. A microstrip antenna is an antenna that is small, light, thin, easy to fabricate, and can be used in long ranges. In this paper, a microstrip antenna is designed on a printed circuit board (PCB) with a permittivity of 4.3 and a thickness of 1.6 mm. This research aims to design a microstrip antenna that is capable of working on 4G (2.3 GHz), Wi-Fi (2.4 GHz), and 5G 3.5 GHZ) frequencies in one antenna. The microstrip antenna is designed on a Printed Circuit Board (PCB) with a permittivity of 4.3 and a thickness of 1.6 mm, rectangular shaped patches, and each patch is connected using a bridging method. Next, the antenna is simulated using CST Suite 2021 software. Simulation results at frequencies of 2.3 GHz, 2.4 GHz, and 3.5 GHz produce return losses of -23.70, -22.87, and -20.60, VSWR values of 1, respectively. .13, 1.15, and 1.20, the bandwidth values are 6.27%, 3.84%, and 5.84%, respectively, and the gain values are 4.69 dBi, 8.53 dBi, and 3.49 dBi.
Dynamic and Relaxation of PEG polymer Chain Segment for Phase Change Materials (PCMs)
Authors: Fauziyah N A , Sakinah  , Rachma W , Paratapa S , Perwitasaric D S , Wardhani P C , Hidayah E N
Published: November 2023

This work’s most notable memory concept for next-generation novels was a reversible phase shift in a substance called phase change materials (PCMs). Here, a polyethylene glycol (PEG) polymer relaxation study employing DMA will be conducted to investigate the qualities of PCMs as superior materials. Through the method of wet mixing, PEG polymer with reinforcement made of silica was synthesized. The variation of silica xerogel was a composition of up to 20% silica xerogel. Adding silica is quite good in reducing the loss factor up to 50 MPa at the addition of 20% silica xerogel. This condition was due to the bonds formed in the polymer chain causing shrinkage and flexibility of composites. Due to the addition of silica xerogel as filler, we can study the relaxation behavior and loss factor of a material using DMA and learn more about its viscoelastic characteristics, including its capacity to absorb vibrations, resistance to impacts, and overall mechanical performance at various temperatures. Relaxation was frequently used to describe phase change materials (PCMs), especially when discussing their capacity to store thermal energy. The release or absorption of thermal energy by a PCM during its phase transition was referred to as the relaxation process.
Suitability of Torricelli’s Theorem Formulation in Cases of Leaking Reservoirs with Video Analysis Tracker
Authors: Habibbulloh M , Anggaryani M , Satriawan M , Saputra O , Zakaria A , Septiawan F
Published: November 2023

This study aims to empirically prove the Torricelli equation formula in the case of leaky reservoirs with the help of video tracker analysis. The method used in this research is quantitative descriptive. The experiment was carried out with a simple tool: a 19-liter gallon of water filled with water and dyed, and then three holes were made vertically with different heights. The gallon is filled with water with a constant water level. Next, take a video of each leaking hole. Video is analyzed with Tracker software. Variables observed were the velocity of water exiting from the leak point (v), the time it took for water to gush from the leak point to the bottom (t), and the horizontal distance from the leak point position to the bottom (x). The results obtained based on video analysis with the tracker are that the farther the distance from the surface of the water to the leak point, the farther the horizontal distance of the resulting jet of water will be. This study concludes that theoretical data and experimental data have significant value, so the video analysis tracker software is feasible to use in dynamic and static fluid learning.
Could Physics Teachers Also Have Misconceptions on Basic Kinematics?
Authors: Admoko S , Suliyanah
Published: November 2023

The role of a physics teacher in learning is to facilitate student activities to construct correct conceptual understanding as that of a scientist. As the primary source of knowledge for students, a physics teacher is required to have the right concept, but this demand is not necessarily fully fulfilled. This study aims to determine the profile of physics teachers’ understanding of concepts on kinematics material detected by a four-tier misconception test. Participants in this study were 20 high school physics teachers in Surabaya. Based on the results of data analysis, it was found that the dominant misconceptions included: (1) Two objects that make the same displacement at the same time interval will have the same velocity, regardless of the type of movement of the two objects (2) Objects that move vertically straight up or down will always have the acceleration of motion equal to the acceleration of gravity which is directed downwards. (3) As long as the object’s position is at positive coordinates, it means the object is moving in the forward direction. (4) The graph of velocity against time, which has a positive gradient, means that the object always moves forward (5) In parabolic motion, the length of time an object is in the air only depends on the length of its path, the longest path will require the longest time. (6) In parabolic motion, the final speed of an object when it lands on the ground depends not only on its initial speed but also on its elevation angle. The findings of several misconceptions above show that even a physics teacher cannot escape misconceptions. Therefore, it is crucial for a teacher to be able to remedy the misconceptions he suffers so that these misconceptions are not transmitted to the students he teaches. This finding is the first step for researchers to detect misconceptions, followed by the application of certain learning methods to remedy misconceptions in future research.
Archimedean Screw Based Micro Hydro Power Plant (MHPP) Prototype with Turbine Elevation Angle Parameters
Authors: Indarto B , Kumalasari D N , Bustomi M A
Published: November 2023

Electrical energy has a very important role in human life, but the electricity supply still needs to meet society’s needs fully. Many potential energy resources can be converted into electrical energy. One of the potential energy resources is the flow of water, which can be used for micro-hydro power plants in remote areas. This paper presents the results of an analysis of a prototype Micro Hydro Power Plant (MHPP) using a 3-blade turbine with a gearbox ratio of 2.8:1. The purpose of the analysis is to determine the greatest value of voltage, current, power, rpm, torque, and efficiency based on variations in the angle of the turbine tilt of 20°, 25°, 30°, and 35° at a water debit of 2.91 l/s and a generator in the form of BLDC 3 phase. The measurement results and data analysis found that the turbine tilt angle of 20° produced the greatest voltage, rpm, torque, and efficiency values. This is because the increase in the angle of inclination of the turbine results in an addition to the volume of the bucket so that the speed of the water flow in the turbine increases. As a result of the addition of this water flow, the turbine becomes heavier to rotate so that the efficiency value decreases.
Morphological Identification of Rocks around Ranupani Village, Mount Semeru, Lumajang, East Java
Authors: Hariyono E , Fahmi M N , Wulandari A
Published: November 2023

Mount Semeru is the highest volcano on Java Island, with its peak of Mahameru at 3.676 meters above sea level (masl). The Semeru volcano is of the Strato type with volcanic-strombolian eruption. This study aims to identify the morphology of rocks found around the mountain in Ranupani Village, Mount Semeru, Lumajang, East Java. Samples were prepared from rocks that had been searched in a limited area from Ranupani Village, Semeru Volcano, then selected, and taken a small portion of the process into powder form, then filtered or sifted. After the sieving process is done, a subtle powder will be obtained. The subtle powder is then ready for XRD testing to find out the identification of the rock morphology. The x-ray diffraction test results were then analyzed qualitatively with the method of search and match. Qualitative analysis of XRD is to determine the crystal structure and composition of the elements contained in these rocks. The sample, phase 1, showed the presence of Barium diiron tetraoxide (Ba Fe2 O4) to form a crystal system orthorhombic. The sample_2 phase shows the presence of Albite (Al Na O8 Si3) to form a crystal system triclinic (anorthic). In sample_3, the phase indicates the presence of Anorthite (Al2 Ca O8 Si2) and the presence of Albite (Al Na O8 Si3) to form a crystal system triclinic (anorthic). The results of rock characteristics with X-ray diffraction show that in sample _2 and sample _3, resulting Silica and Aluminum elements are present. This suggests that the predominant minerals in these samples are likely silicates, such as feldspars and clay minerals, which are rich in silica and aluminum. Further analysis is needed to identify these samples’ specific mineral compositions and proportions. Through Match! 2, from the top of the diffraction pattern (short angle 2 10, 10-60 °), the sample corresponds to the silica and aluminum diffraction patterns.
The Relationship between Multiple Representational Skills and Understanding of Physics Concepts in the Pre-Service Science Teacher
Authors: Wasis  , Widodo W , Sunarti T , Setyarsih W , Jauhariyah M N R , Zainuddin A
Published: November 2023

The concept of physics has various representations that must be mastered by the Pre-Service Science Teacher (PSST). It is not uncommon for PSST to have poor multiple representation skills, impacting the delivery of concepts in school. Therefore, this study aims to analyze the profile of multiple representation skills and their relation to understanding the concept of PSST Physics. The representations studied include verbal, visual, symbolic, and mathematical forms. Eleven PSST became respondents in the study. Multiple representation and conception measurements use instruments with a three-tier item format containing content, argumentation, and confidence levels. Student responses are analyzed descriptively, qualitatively, and quantitatively. The findings of this study are: 1) 18% of PSST belong to the concept understanding, 27% experienced misconceptions, and the rest (55%) were classified as not knowing the concept or responding by guessing; 2) the highest representation format mastered by students is the visual representation, and the lowest is the mathematical representation; and 3) the ability to multiple representations and understand physics concepts has a significant and perfect correlation with a Pearson Correlation of 0.847. This research implies that learning for PSST can emphasize multiple representation abilities as it affects their understanding of concepts.
A Profile of Senior High School Students’ Problem-solving Skills on Dynamic Fluid Materials
Authors: Qotrunnada N A , Prahani B K , Marianus  , Wibowo F C , Uulaa R F R
Published: November 2023

Physics learning requires problem-solving in the learning process. This research is a pre-experimental study with random samples. This research aims to find out the initial profile of high school students’ problem-solving on dynamic fluid material. The subjects of this study were 108 students of grade XI in senior high school. The problem-solving indicator used ACCES, which consists of 5 indicators. The result shows that the problem-solving abilities of high school students in dynamic fluid material still need to be improved because of several factors. Earning models and media need to be more relevant in supporting students’ problem-solving abilities. This research can be used as empirical evidence that students’ problem-solving skill in dynamic fluid material needs to be improved.
The Results Comparison of Numerical and Analytical Methods for Electric Potential on Rectangular Pipes
Authors: Maulana Z S , Rizaldi M F R , Bustomi M A
Published: November 2023

Two methods can be used to solve the problem of electric potential distribution in a rectangular pipe: numerical and analytical. The analytical solution is obtained using the Laplace equation and the given boundary conditions to complete the solution in the form of a linear combination of sinusoidal and hyperbolic functions. While the numerical solution is obtained using the finite difference method in the Python programming language. The comparison between the analytical and numerical solutions shows that the two have a good fit. This can be seen from the graph of the electric potential distribution in the rectangular pipe produced by the two methods. Numerical solutions obtained using the finite difference method in the Python programming language provide accurate and efficient results in solving the problem of the electric potential distribution in rectangular pipes. The use of the first four terms in the analytical method and the selection of 4 observation points on the pipe, namely points A (3.33, 1.67), B (3.33, 3.34), C (6.67, 1.67), and D (6.67, 3.34) produces a difference in the electric potential value between analytical and numerical methods each point is 35.91%, 51.96%, 51.96%, and 35.91%. The value difference between analytical and numerical methods will be smaller if more terms are taken in the analytical calculation, and more observation points are considered on the pipe.
Performance of Polyaniline Thin Film as a Functional Material of Acid Vapor Sensors
Authors: Pratiwi I F R , Putri N P , Rohmawati L , Kusumawati D H
Published: November 2023

Polyaniline (PANI) is a conductive polymer that can be produced by the electrodeposition process. The purpose of this research is to evaluate the performance of PANI sensors on hydrochloric acid (HCl) and acetic acid (CH3COOH) vapor using a scan rate of 100 mV/s and ten cycles, a thin PANI layer was created on the surface of the ITO substrate. The PANI spectroscopic test results before and after CH3COOH vapor exposure revealed no differences and remained within the PANI functional group range. A four-point probe (FPP) test was performed to evaluate the sensing performance of the PANI thin film against analyte gas. The results of recovery time, response time, and sensitivity tended to increase as analyte concentration increased. The quickest CH3COOH sensing (1 ppm) has a reaction time of 29.7 seconds, a recovery time of 21.9 seconds, and a sensitivity of 5.11%. The greatest CH3COOH sensing (10 ppm) resulted in a reaction time of 50.3 seconds, a recovery time of 39.7 seconds, and a sensitivity of 13.64%. The reaction time for the lowest HCl sensing (1 ppm) was 42.6 s, the recovery time was 32.4 s, and the sensitivity was 7.82%. The greatest level of CH3COOH sensing (10 ppm) resulted in a response time of 60.6 s, a recovery time of 55.3 s, and a sensitivity of 16.31%. As a result, the PANI thin film is a functional material for acid gas sensors.
Chemical Reagent Localization and Recognition Algorithm for Robot Chemists Based on YOLOv5 and CRNN
Authors: Liu Jiasheng , Li Haoyuan , Zhang Han , He Chuanning , Xiong Liangtao , Shi Yue , Liu Zhifan , Li Xiaolong , Zhang Jianhua
Published: November 2023

Artificial intelligence and robotics are increasingly used in chemical experiments for reagent preparation, but it is still a challenge to accurately grasp the reagent bottle in small and dense scenarios. Therefore, precise positioning and identification of the reagent bottles are crucial. However, the different kinds of chemical reagents create complexity in target detection, making the task difficult. Therefore, we propose a model, named TA-YOLOv5, based on YOLOv5 for the task of chemical reagent localization. To enrich our dataset and prevent single-background overfitting, we employed Mosaic and Mix-Up data augmentation during dataset processing. Furthermore, Transformer Encoder and Coordinate Attention modules are utilized to enhance the feature expressive ability for both small target objects and global information during model training. Finally, the CIoU-NMS algorithm is utilized to optimize prediction box filtering in dense scenarios. In addition, for the task of chemical reagent classification, this paper uses the CRNN (Convolutional Recurrent Neural Network) algorithm to identify character information on the label of the reagent bottle, enabling the successful classification of the reagent bottle. The experimental results illustrate that TA-YOLOv5 achieves 98.49% precision on the self-made reagent bottles dataset, which is 4.12% higher than the YOLOv5 network model. Moreover, the CRNN network reached 97.6% accuracy on IIIT 5k dataset.
Complex Query in Process Knowledge Graph Based on Box Embedding
Authors: Zhou Tingting , Wang Yajun , Jin Bo
Published: November 2023

To make use of past practical experience and expertise effectively and accurately, and reduce the waste of resources due to repetitive labor, this paper conducts intricate multi-hop logical deduction by using the information obtained from the process knowledge graph (PKG). Here, BoxE is introduced in this context, which is a box embedding framework designed to address diverse First-Order Logic queries (FOL) across Process Knowledge Graphs (PKG). A key insight of BoxE is that entities and queries can be embedded as boxes and geometric operations can be used iteratively for logical reasoning to answer the complex logical queries. Our demonstration showcases BoxE’s ability to effectively respond to various First-Order Logic queries involving technology, process, procedure, etc. on PKG and shows that BoxE has higher accuracy on each query structure, which can generalize unseen query structures and answer complex query structures scalably and accurately.
Improved Genetic Algorithm Based on Oscillation Factor to Solve the AUV Path Planning Problem
Authors: Wu Zhengjia , Zuo Luyang , Ma Jianming , Meng Ronghua , Xiang Chongchong , Guan Feng , Cheng Xinhao
Published: November 2023

In this paper, the bi-objective AUV path planning problem considering the shortest path and the minimum path smoothness is studied. Firstly, a mathematical model of the problem is established and a two-dimensional Cartesian coordinate system model is used to model the AUV working environment. Then the dual objective is normalized and transformed into an adaptation function by dimensionality reduction. An improved Genetic Algorithm is proposed to solve the problem according to its characteristics. An initial solution generation strategy for the n-1 equipartition method based on the improved oscillation factor is designed, and an elite retention strategy with simulated annealing operation is introduced to improve the genetic strategy. To verify the effectiveness of the improved algorithm in this paper, simulation experiments were conducted by the Microsoft Visual Studio platform. After the comparison and analysis of the three algorithms, the algorithm proposed in this paper has shorter and smoother paths, faster convergence speed, and more obvious advantages in the quality of the solution.
Research on Human Pose Estimation Based on High-resolution Network
Authors: Ji Xu , Niu Yanmin
Published: November 2023

The problem addressed in this paper is the increase in the parameter quantity of existing human body pose estimation network models when the depth of the network is scaled up to improve forecast precision. To tackle this issue, an optimization network model of the new human body pose estimation called BDENet is proposed, inspired by high-resolution detection networks. This model incorporates a bottleneck structure and dilated convolution to reduce parameters and incorporates the ECA lightweight attention mechanism to enhance precision. Compared with HRNet, the proposed model achieves a 21.4% reduction in parameter quantity on the MSCOCO dataset while scaling up precision by 1.4%. The experimental findings strongly suggest that the modified network significantly improves network precision along with lowering the number of parameters.
Temporal-difference Adaptive Graph Convolutional Network for Skeleton-based Action Recognition
Authors: Liu Fuchun , Huang Shengfeng
Published: November 2023

In action recognition based on the skeleton, graph convolutional networks (GCNs) have shown great superiority based on the design of making the skeleton in the video a spatiotemporal map and extracting features from the spatiotemporal map. However, the topology of the skeleton in GCN-based methods is pre-designed according to prior knowledge, which limits the capacity of the network to learn high-level topology about the skeleton. To improve this deficiency, we design a temporal-difference adaptive graph convolutional network (TDA-GCN) that can learn the potential topology of the human skeleton from the input data, which is augmented using the channel attention module. Experiments show that TDA-GCN achieves state-of-the-art performance on two large-scale skeleton datasets, NTU-RGBD and Kinetics-Skeleton.
Fisheries Water Quality Monitoring Improvement System
Authors: Jia Junle , Luo Chun , Hou Zhengyi , Xia Qiqi , Ma Xuanhang , Pan Xiang , Ma Awen , Zheng Yuru
Published: November 2023

In this paper, the system of dynamic identification and monitoring of water bodies and intelligent allocation of pharmaceutical discharge is designed. At present, aquaculture technology in our country is relatively traditional, and the water environment-bearing capacity will often be ignored. This paper aims to realize the efficiency of equipment in the multiple stages of aquaculture through the design system, the remote control of motion software device, and strive to combine intelligent equipment and the basic process of aquaculture, so as to make the aquaculture industry gradually upgrade. Through the test, our device can dynamically identify and detect the water body, and ensure the fishery output and water quality at the same time, bringing economic and environmental benefits to a great extent.
An airborne object detection and location system based on deep inference
Authors: Hu Xiao , Pan Shenfu , Li Dongdong , Feng Long , Zhao Yuan
Published: November 2023

In recent years, with the development of sensors, communication networks, and deep learning, drones have been widely used in the field of object detection, tracking, and positioning. However, there are inefficient task execution and some complex algorithms still need to rely on large servers, which is intolerable in rescue and traffic scheduling tasks. Designing fast algorithms that can run on the airborne computer can effectively solve the problem. In this paper, an object detection and location system for drones is proposed. We combine the improved object detection algorithm ST-YOLO based on YOLOX and Swin Transformer with the visual positioning algorithm and deploy it on the airborne end by using TensorRT to realize the detection and location of objects during the flight of the drone. Field experiments show that the established system and algorithm are effective.
Design and Research of AGV Indoor Positioning System Based on Visual and Ultra Wideband Combination Positioning
Authors: Li Xudong , Wu Ruiming
Published: November 2023

Aiming at the problems of cumulative error in monocular visual positioning and Non-Line-of-Sight (NLOS) error in UWB positioning for the automated guided vehicle (AGV) in indoor environments, a combined method of vision and Ultra-Wide Band (UWB) is proposed for indoor AGV positioning. Firstly, the overall structure and system of the AGV are designed to achieve indoor navigation and positioning functions. Secondly, the monocular visual and UWB positioning data are fused using the Error State-Extended Kalman Filter algorithm (ES-EKF) to obtain the optimal pose estimation of the AGV. Finally, the AGV is used as a mobile platform to conduct positioning experiments in different indoor environments. The experimental results demonstrate that the navigation and positioning system has high accuracy and robustness in indoor environments with obstacles, and no significant drift or discontinuity phenomena occur during the positioning process, indicating its practicality in indoor settings.
English Pronunciation Quality Evaluation System Based on Continuous Speech Recognition Technology for Multi-Terminal
Authors: Wu Xianxian , Zhang Yan , Feng Bin
Published: November 2023

This paper presents a novel approach for evaluating the pronunciation quality of English speech using continuous speech recognition technology. The research focuses on the application of artificial intelligence in speech recognition, utilizing web browsers on various terminal devices such as computers, mobile phones, and tablets to allow users to read the provided text aloud. The web program captures audio input from the microphone, records it in MP3 format, and uploads it to the server. The server employs the Whisper model to transcribe the audio into semantic text, which is then compared with the displayed text. By calculating the semantic distance and assessing the accuracy of pronunciation, the system provides an evaluation of pronunciation quality, marking correct and incorrect words. To achieve real-time processing, the compact tiny model is employed, and further optimization is performed using Ctranslate 2, resulting in significant performance improvements.
Development of a Testing System for High-efficiency Power Recovery Bag Accumulators
Authors: Hao Weigu , Ma Donghui , Xing Keli
Published: November 2023

Currently, most of the bladder-type accumulator test benches used have problems such as large installed capacity, severe energy loss, and incomplete testing functions. This article focuses on the research of the testing requirements and power recovery issues of bladder-type accumulators. A new type of hydraulic schematic and electrical control system for power recovery bladder type accumulator testing based on mechanical compensation with dual output shaft motor transmission, differential charging and discharging of dual accumulators, and parallel addition of oil replenishing accumulators has been designed. A measurement and control software based on the LabVIEW platform has been developed. The experimental results show that the system’s power recovery efficiency can reach 60.5% by adopting a scheme of mechanical compensation type power recovery, differential charging and discharging of energy accumulator group, and parallel addition of oil replenishing energy accumulator. The testing system can accurately, efficiently, and conveniently complete various performance tests of hydraulic bladder accumulators.
Noise Reduction of TBM Big Tunneling Data by Butterworth Filter
Authors: Xiao Haohan , Zheng Lifeng , Zhang Di
Published: November 2023

The location of a Tunnel Boring Machine (TBM) is prone to external environmental and internal system noise interference. To address TBM vibration characteristics, this study analyzed the sources of excavation data noise, the need for noise reduction, and the methods used, using excavation speed as the prime example. We validated the results through three actual tunnel projects. Our research showed that excavation parameters automatically collected by the TBM, such as excavation speed, cutter head thrust, and cutter head torque, contain noise and require filtering and noise reduction before data mining. Different cutoff frequencies correspond to varying filtering effects, and after considering both smoothness and accuracy, we recommend setting the Butterworth filter’s cutoff frequency to 0.1.
RGB and LiDAR Fusion-based 3D Semantic Segmentation for Autonomous Driving
Authors: Liu Jianguo , Jia Zhiling , Li Gongbo , Yan Fuwu , Wu Youhua , Sun Yunfei
Published: November 2023

Projection-based multimodal 3D semantic segmentation methods suffer from information loss during the point cloud projection process. This issue becomes more prominent for small objects. Moreover, the alignment of sparse target features with the corresponding object features in the camera image during the fusion process is inaccurate, leading to low segmentation accuracy for small objects. Therefore, we propose an attention-based multimodal feature alignment and fusion network module. This module aggregates features in spatial directions and generates attention matrices. Through this transformation, the module could capture remote dependencies of features in one spatial direction. This helps our network precisely locate objects and establish relationships between similar features. It enables the adaptive alignment of sparse target features with the corresponding object features in the camera image, resulting in a better fusion of the two modalities. We validate our method on the nuScenes-lidar seg dataset. Our CAFNet achieves an improvement in segmentation accuracy for small objects with fewer points compared to the baseline network, such as bicycles (6% improvement), pedestrians (2.1% improvement), and traffic cones (0.9% improvement).
Research and Implementation of 3D Object Detection Based on Autonomous Driving Scenarios
Authors: Chen Xi
Published: November 2023

Perception function, as an important part of autonomous driving, ensures the safety and intelligence of driving. We collect the surrounding environment of driving through hardware sensors, providing a basis for subsequent decision-making of autonomous driving. In recent years, deep learning has made breakthrough progress in object detection. Based on this, this paper uses lidar point cloud data, combined with deep learning theory and method, to carry out three-dimensional target detection tasks around lidar point cloud data, and carries out theoretical analysis, method verification, and result analysis. A 3D object detection method based on LiDAR point cloud data is proposed. The backbone network of the network model corresponding to the method is VoxelNet’s backbone network. After outputting the feature matrix, sparse point clouds are supplemented with point clouds, and then the feature matrix is decoded to generate candidate boxes. The model used in this paper on the KITTI data set can effectively solve the problem of 3D target detection in the process of autonomous driving and has good performance.
Research of a novel aerodynamic evaluation method for fixed-wing UAV
Authors: Wu Yansen , Liu Deshan , Wang Tiancheng , Zhao Anmin
Published: November 2023

The aerodynamic parameters of unmanned aerial vehicles (UAVs) play an important role in the newly designed drone. For the purpose of the real-time measurement of the aerodynamic performance parameters of the UAV in flight status, based on the self-development connected-wing configuration airplane, a novel airborne aerodynamics test scheme is researched and verified in this work. The findings of this study indicate that the effectiveness of numerical calculations can be verified by comparison with both results of the numerical simulation and airborne flight test in the same conditions. The newly designed UAV equipped with this test system in the future, not only achieves quick and reliable results of aerodynamic performance and powered system efficiency but also can save the expense of wind tunnel experiments, which is of high potential to the UAV application.
Performance optimization design of wide-body aircraft pressure refueling system
Authors: Gong Hao
Published: November 2023

In order to reduce the wide body aircraft refueling process time-cost and improve the airport operation efficiency, pressure refueling system design strategy was innovated. The shutoff valves’ operation sequence in refueling process was optimized. The diameter of the orifices on the pressure refueling system fuel line was designed. Pressure refueling performance was simulated and analyzed at different scenarios. The results show that it can improve the pressure refueling system performance at different scenarios by optimizing the pressure refueling process strategy design including optimizing the fuel line orifice design and optimizing the wing tank inner side shut-off valve operation sequence.
Research on solar sail attitude maneuvering method based on adaptive sliding mode control
Authors: Wang Jie , Ma Tianyi , Song Haibo , Yu Ye
Published: November 2023

A solar sail is a spacecraft propulsion system that uses the pressure of light to push a spacecraft. It consists of a lightweight support structure that deploys a large area of flexible film. During attitude maneuvering in space, the solar sail will excite vibrations in the flexible support structure and film, which can affect the accuracy of the attitude control system. To address this issue, this article first establishes a rigid-flexible coupled dynamic model of the solar sail that includes attitude motion and flexible structure elastic vibrations. Then, based on an adaptive sliding mode control method, a solar sail attitude maneuvering method is proposed. Finally, a numerical simulation is conducted using a hexagonal-shaped solar sail as the object. The numerical simulation results show that the attitude maneuvering method has the performance of attitude tracking and attitude stabilization, can meet the requirements of large-angle attitude maneuvering for solar sail spacecraft, and has strong robustness to model parameter uncertainty.
Research on radial velocity and airspace position calculations of target in airborne active radar simulation
Authors: Zhang Wenguo , Gan Hanghua , Pan Xin , Tian Feng , Pan Li , Shao Peng , Jiang Xiangle , Zou Xiaobin
Published: November 2023

The detection of the target in the airborne active radar simulation is simplified to the calculations of the radial velocity, the maximum detecting range of the airborne active radar corresponding to the RCS, and the airspace position of the target. However, the coordinate transformations related to the calculations of the radial velocity and the airspace position are usually bewildering due to the different referenced coordinate systems. This paper introduces the radial velocity and airspace position calculations of the target in the airborne active radar simulation to illuminate the transformation process containing the specific rotation matrices, suggesting the unifying transformation to the north-up-east (NUE) rectangular coordinate system of the aircraft for both the radial velocity calculation and airspace position calculation of the target.
Effect of oxygen rich environment on detonation characteristics of pulse detonation engine
Authors: Yang M F , Qi S B , Bai H B , Gao S Y , Song J , Hu B W , Xu Z
Published: November 2023

The detonation tests of propane/air pulse detonation engine at normal temperature were carried out in this paper. The effects of chemical ratios on the detonation performance of propane/air pulse detonation engine in oxygen-rich environment were studied. The propagation modes and characteristics of detonation waves and the detonation characteristics of the engine under different conditions were analyzed. Detonation tests were conducted on propane/air mixtures with oxygen mass fraction of 20%, 25%, 30% and 35% respectively. The results showed that: In the detonation experiment of the propane/air mixture with oxygen content of 20%, 25% and 30%, the flame wave propagation velocity in the detonation tube is low, which fails to form a stable detonation wave. The detonation effect of the fuel mixture with oxygen content of 20% is the worst, and the propagation velocity of flame wave is 384.00 m/s. In the experiment of propane/air mixture with oxygen content of 35%, the detonation velocity and pressure obtained by pressure signal analysis are both greater than the theoretical CJ detonation velocity, and the detonation state is successfully reached.
Numerical simulation of rebar corrosion in track bed of shield tunnel under stray current
Authors: Yu Shuo , Sun Huajun , Wang Zijuan , Liu Changbao
Published: November 2023

Track bed is the important support structure at the bottom of shield tunnel, during metro operation, the leakage of stray current will lead to corrosion of rebar in the track bed, which will affect the safe operation of metro. In this paper, the corrosion calculation model of track bed rebar under stray current is established, and the effects of stray current input mode and concrete resistivity on the corrosion rate of track bed rebar are studied. The result shows the corrosion rate of track bed rebar decreases nonlinearly with the increase of concrete resistivity, and the reduction gradient of corrosion rate in bilateral input mode is greater than that in unilateral input mode. With the decrease of concrete resistance, the corrosion area will cover the left half in unilateral input mode and cover both ends of track bed rebar in bilateral input mode. When the input point voltage increases by 40%, the corrosion current density in the middle of track bed will increase by about 61%.
Mixed Horizontal Well Pattern and Fracturing Parameter Optimization of Low Permeability Reservoir
Authors: Hu Qi-hao , Guo Fa-jun , Cao Hong-qiang , Wang Xiu-wei , Wang Ya-zhou , Wang Xia , Wang Hong-tao , Cao Jie-feng
Published: November 2023

Horizontal well fracturing development is significant in improving the development effect of low permeability reservoirs and is widely applied in many low permeability reservoirs of China. In this study, the reservoir numerical simulation is used to establish different mixed horizontal well networks of the target reservoir. The result shows that the best waterflood development effect is achieved when horizontal segment orientation and crack orientation are at an angle of 45°. The horizontal segment length and fracturing parameters of mixed horizontal well networks are optimized. It is considered that the rational horizontal segment length of the horizontal well is 400 m, the rational number of cracks is 3, and the optimal crack conductivity is between 180-200 mD.m. Through the study of mixed horizontal well network and fracturing parameter optimization, the low permeability reservoir efficient horizontal well fracturing development is well guided.
Design and engineering application of a new type of copper bar-embedded metering box based on DFA theory
Authors: Chen Zhiru , Zhao Xi , Zhang Zhi , Jing Zhen
Published: November 2023

Based on the design theory that products can be assembled, the optimal design of the electric energy metering box in the embedded copper bar and other aspects is realized, the product wiring is standardized and concealed, the assembly method is optimized, the assembly difficulty is greatly reduced, several problems in cost and quality are solved in industrial design, and objective score data from experts are obtained through perceptual experiments. It provides a new design method and evaluation idea for the field of power measurement and has great popularization value.
A Method for Estimating the System’s Maximum Effective Reserve under the Electricity Market
Authors: Liu Junlei , Chao Zhu , He Xiangzhen , Bao Bo , Duan Qinwei , Tang Xuchen , Xie Xiangzhong , Chen Huican , Su Xiangyang
Published: November 2023

System’s reserve is one of the important security constrains when conducting the day-ahead clearing calculation. Usually, the reserve requirement is determined by the local dispatching center based on their experience. However, this experience-based threshold may lead to two issues, i.e., the invalid reserve and the slow calculation speed under the electricity market condition. Based on the concept of effective reserve, a method for estimating the system’s maximum effective reserve is proposed in this paper. The main idea is to design an optimization algorithm to determine the operating unit set with the goal of maximizing the system’s effective reserve. The maximum value obtained can help the dispatching center to design the system’s reserve threshold, which is of great engineering significance. Simulation analysis verified the correctness and rationality of the proposed model through comparative analysis of multiple scenarios.