bluuebunny/crossref_metadata_2025_split huggingface dataset:
Detection method of obstacles in the dangerous area of electric locomotive driving based on MSE-YOLOv4-Tiny
Authors: Wang Wenshan , Wang Shuang , Guo Yongcun , Zhao Yanqiu , Tong Jiale , Yang Tun 
Published: July 2022

Abstract
Aiming at the problems of error warning, low detection efficiency and inability to meet the requirements of lightweight deployment in current track obstacle detection algorithms based on computer vision, a detection method of obstacles in the dangerous area of electric locomotive driving based on improved YOLOv4-Tiny (MSE-YOLOv4-Tiny) was proposed. An obstacle image dataset was constructed to provide a testing environment for various target detection algorithms. The method of perspective transformation, sliding window and least square cubic polynomial was used to fit the track line. By finding the area where the track was located and extending a certain distance to the outside of the track, the dangerous area of the electric locomotive running was obtained. A three-scale detection structure was formed by increasing the shallow detection scale in the detection layer, so as to improve the detection accuracy of the network for smaller targets, such as stones. An improved SKNet (ECA_SKNet) attention mechanism module was added to the output ends of the three scales of the backbone network, and the weight was reassigned to realize feature reconstruction, thus further improving the detection accuracy of the target. By adding the Spatial Pyramid Pooling module, the local and global features of the image were fused to improve the accuracy of localization and detection accuracy of the network. A comparative experiment was carried out on the dataset constructed in this paper. The experimental results show that the problem of false warnings caused by taking the target in the safe area as an obstacle can be effectively solved by dividing the danger area of electric locomotive driving. Compared with the original YOLOv4-Tiny algorithm, the MSE-YOLOv4-Tiny algorithm has a 3.80% increase in mean average precision while maintaining a higher detection speed and a smaller model memory. It has better detection performance and can be used for autonomous driving electric locomotive obstacle detection to provide technical support.
Electron emission from bromouracil and uracil induced by protons and radiosensitization
Authors: Roy Chowdhury Madhusree , Monti Juan M , Misra Deepankar , Weck Philippe F , Rivarola Roberto D , Tribedi Lokesh C 
Published: July 2022

Abstract
Absolute double differential cross sections (DDCS) of electrons emitted from uracil and 5-bromouracil (BrU) in collisions with protons of energy 200 keV have been measured for various forward and backward emission angles over wide range of electron energies. The measured DDCS are compared with the continuum distorted wave-eikonal initial state (CDW-EIS) calculations. The optimized structure of the BrU was estimated along with the population analysis of all the occupied orbitals using a self-consistent field density. A comparison between the measured DDCS data for the two molecules show that the cross section of low energy electrons emitted from BrU is substantially larger than that for uracil. The BrU-to-uracil DDCS ratios obtained from the present measurements indicate an enhancement of the electron emission by a factor which is as large as 2.0 to 2.5. These electrons being the major agent for damaging the DNA/RNA of the malignant tissues, the present results are expected to provide an important input for the radiosensitization effect in hadron therapy. It is noteworthy to mention that the CDW-EIS calculations for Coulomb ionization cannot predict such enhancement. A large angular asymmetry is observed for uracil with a broad structure, which is absent in case of BrU.
The influences of B-site doping on ferroelectric and energy-storage properties of Bi0.5(Na0.82K0.18)0.5TiO3–LiSbO3 ceramics
Authors: Yang Wentao , Uddin Sarir , Zaman Arif , Zheng Guangping 
Published: July 2022

Abstract
Single-phase Bi0.5(Na0.82K0.18)0.5Ti1−xMxO3–0.01LiSbO3 (BNKT–LS-xM) (M = Ta, Nb or Zr, 0 ≤ x ≤ 0.05) lead-free ceramics are prepared by a solid-state reaction method. The influences of Ta5+, Zr4+or Nb5+ doping at B-site of perovskite structures on the crystal structure, chemical structure, ferroelectric and energy-storage properties of BNKT–LS ceramics are systematically investigated. Although the introduction of Ta5+, Zr4+ and Nb5+ at B-site could disturb the long-range ferroelectric ordering, Ta5+ or Nb5+ doping results in excellent thermal stability of the energy-storage density (as large as 0.7 J cm−3) at elevated temperatures (50 °C–200 °C) with a high energy-storage efficiency (>90%). The results demonstrate that the lead-free BNKT–LS-xM ceramics are promising dielectric materials that can be finely tuned for electrical energy storage with high energy storage efficiency and a wide range of operating temperature.
Forward kinematics of body posture perception using an improved BP neural network based on a quantum genetic algorithm
Authors: Chen Buqing , Zhang Taihui , Cong Lin , Ma Jin , Hu Wendong 
Published: July 2022

Abstract
Forward kinematics analysis of body posture perception is the basis for studying other performance of 6-degree of freedom parallel robot. Because forward kinematics involves many sets of nonlinear equations, it is usually difficult to solve. In this paper, an improved BP neural network (BPNN) based on a quantum genetic algorithm (GA) is designed to solve the forward kinematics problem. Additionally, we use the characteristics of easy calculation of inverse kinematics to generate a dataset for training and testing. Finally, through a large number of experiments, we show that the improved strategy of BPNN by quantum GA is effective, and the accuracy of the model we designed is high enough to solve the forward kinematics of body posture perception.
Mono-γ production of a dark vector at future e
+
e
− colliders*
Authors: Ma Kai 
Published: July 2022

Abstract
The associated production of a dark particle and photon, represented as a mono-γ event, is a promising channel to probe particle content and dynamics in the dark sector. In this study, we investigate the properties of the mono-γ production of vector dark matter at future

colliders. Photon-like and Pauli operators as well as triple gauge boson interactions involving dark matter are considered in the framework of effective field theory. We show that, in comparison with the Pauli operator, the triple gauge boson couplings are significantly more interesting in high energy colliders. Beam polarization effects are also analyzed, and we show that the experimental sensitivities cannot be significantly enhanced because of the smaller luminosity.
Isotopic production cross sections of fragmentation residues produced by 18O ions on a carbon target near 260 MeV/nucleon*
Authors: Xu Xiao-Dong , Sun Ya-Zhou , Wang Shi-Tao , Mei Bo , Jin Shu-Ya , Zhang Xue-Heng , Sun Zhi-Yu , Zhao Yi-Xuan , Tang Shu-Wen , Yu Yu-Hong , Yan Duo , Fang Fang , Zhang Yong-Jie , Ma Shao-Bo 
Published: July 2022

Abstract
The isotopic cross sections of residual nuclei produced in fragmentation reactions of 18O projectiles impinging on a carbon target at energies near 260 MeV/nucleon were measured at the HIRFL facility in Lanzhou (China). A full identification of atomic and mass numbers of fragments was achieved from the determination of their magnetic rigidity, energy loss, and time of flight. The production cross sections for a dozen of nitrogen, carbon, and boron isotopes were determined with uncertainties below 30% for most of the cases. The obtained cross sections for N and B isotopes show a rather good agreement with previous experimental data obtained with different projectile energies. The cross sections for some C isotopes seem to exhibit a dependence on the projectile energy. A comparison of the data and several theoretical model calculations are presented.
Fractional Klein–Gordon equation on AdS2+1
Authors: Basteiro Pablo , Elfert Janine , Erdmenger Johanna , Hinrichsen Haye 
Published: July 2022

Abstract
We propose a covariant definition of the fractional Klein–Gordon equation (KGE) with long-range interactions independent of the metric of the underlying manifold. As an example we consider the fractional KGE on AdS2+1, computing the explicit kernel representation of the fractional Laplace–Beltrami operator as well as the two-point propagator of the fractional KGE. Our results suggest that the propagator only exists if the mass is small compared to the inverse AdS radius, presumably because the AdS space expands faster with distance as a flat space of the same dimension. Our results are expected to be useful in particular for new applications of the AdS/CFT correspondence within statistical mechanics and quantum information.
Electronic transport in three-terminal chaotic systems with a tunnel barrier
Authors: Oliveira Lucas H , Barbosa Anderson L R , Novaes Marcel 
Published: July 2022

Abstract
We consider the problem of electronic quantum transport through ballistic mesoscopic systems with chaotic dynamics, connected to a three-terminal architecture in which one of the terminals has a tunnel barrier. Using a semiclassical approximation based on matrix integrals, we calculate several transport statistics, such as average and variance of conductance, average shot-noise power, among others, that give access to the extreme quantum regime (small channel numbers in the terminal) for broken and intact time-reversal symmetry, which the traditional random matrix approach does not access. As an application, we treat the dephasing regime.
Augmenting the concept of Institutional Analysis to the inter-state border delimitation and demarcation practice in peninsular Malaysia
Authors: Jumari Shahril Azhari , Omar Abdullah Hisam , Idris Khairulnizam M. , Abdullah Nazirah Mohamad 
Published: July 2022

Abstract
Enhancing border management policies appears to be a crucial aspect of the state border nations’ proposal for interstate border governance. Understanding the action principle that guides an effective decision-making process among the institutions involved is necessary to improve a policy. The Institutional Analysis and Development Framework (IAD), proposed by Elinor Ostrom, an American political scientist specializing in institutional behaviour, is the most applicable framework for reforming guidelines. This article aims to raise awareness of the significance of incorporating the Institutional Analysis and Development Framework concept into the Joint Border Committee’s (JBC) effective practice of interstate border determination in Peninsular Malaysia. Although incorporating social science knowledge into border management cycles remains limited, it appears to have increased over the past decade. The findings are analyzed to determine the suitability of integrating Institutional Analysis & Development (IAD) into Peninsular Malaysia’s JBC practice to predict institutional behaviour and relationships related to the outcomes
Assessments of Nutrients Content in Soil and Leaves of Harumanis Mangoes and Its Relationship with the Yield
Authors: Razi Noorazwani Mohd , Syazwani Zakaria Siti Noor , Shahidin Nurhaliza Mohamad , Nasron Nursyahani 
Published: July 2022

Abstract
Crop yield can determine the health of a tree based on the nutrient content applied by the farmers. Soil nutrients are essential for plant production. This research aims to study the relationship between the yields of Harumanis mango and the nutrient content in soil and leaves. Three (3) primary objectives are highlighted, namely: (1) to study the distribution of nutrients content in the soil; (2) to determine the relationship between the yields of Harumanis mango and nutrient content in soil and leaves; and (3) to identify the significant factors affecting the yields of Harumanis mango. The study area is in the UiTM Perlis branch. Overall, 25 samples have been collected with information on the coordinate position, crop yield and nutrient content; nitrogen (N), phosphorus (P), potassium (K) and calcium (Ca). The Kriging method interpolated the distribution of nutrient content in the soil. Pearson correlation and multiple linear regression analysis were used to study the relationship between yield and nutrient content in soil and leaves to determine which nutrients influenced the yield of Harumanis mango. The result shows only K and Ca in the leaves significantly contribute to the yield of Harumanis mango. The multiple linear regression model for the predicted yield of Harumanis mango is 347.974 – 51.426 (N% in leaves) – 550.225 (K% in leaves) + 86.672 (Ca% in leaves).
Determining Optimal Solar Power Plant Location in Melaka, Malaysia: A GIS-Based Solutions
Authors: Durrany Zulkifly Muhammad Iqbal , Mohd Said Mohd Shahmy 
Published: July 2022

Abstract
The energy demand has risen dramatically in recent years as a result of population growth and the fast expansion of the global economy. Due to rising carbon dioxide (CO2) emissions and increasing energy needs, Malaysia has recently intensified its efforts to encourage the development of renewable energy supplies. Despite the abundance of solar resources, the PV growth in underdeveloped countries such as Malaysia is moving slower. Malaysia has the advantage in solar energy generation since it is geographically close to the equator and has a significant solar generation potential due to its hot and sunny weather all year. Therefore the question here is, where is the most suitable place to build more solar power plants? What methods will we be using to find the most suitable place to build the solar power plant? In picking a place for such development, several factors must be examined, such as how effective the PV power station site is and how to decrease the overall cost of the project by minimising proximity to existing infrastructures while improving solar panel power production. A geographic information system (GIS) is a tool that can help to solve this challenge. In this case, we integrate economic, environmental, and technical variables such as solar radiation intensity, local physical terrain, environment, climate, and placement criteria such as distance from roads and rivers. As additional input factors, other geographical information data were used (solar radiation, digital elevation models (DEM), land cover, and temperature). Further analysis using the Analytic Hierarchy Process (AHP) based Multi-Criteria Decision Making (MCDM) was then applied to this study to get the suitable location based on the importance of the criteria. In order to build a cost-effective and high-performing solar project, a complete solar site assessment is required. The results of the study should give a decision support system model and map on determining the optimal locations of solar power plants in Melaka.
A Review: Progression of Remote Sensing (RS) and Geographical Information System (GIS) Applications in Oil Palm Management and Sustainability
Authors: Aikal Baharim Mohd Sharul , Adnan Nor Aizam , Mohd Fazly Amri , Seman Idris Abu , Izzuddin Mohamad Anuar , Aziz Nordiana Abd 
Published: July 2022

Abstract
In agriculture management and cultivation, many researchers tend to introduce and implement new methods or techniques to improve the sectors in order to sustain a good production from the sectors. The oil palm plantation is one of the sectors that have received an improvement in development in many aspects. Thus, this paper reviews in detail the recent expansion of oil palm management and sustainability through the latest application technologies specifically in Remote Sensing (RS) and Geographical Information System (GIS) knowledge which covered land classification and crop changes, disease detection and pest control, age estimation for oil palm, above-ground biomass (AGB) and carbon estimation, tree counting for oil palm assessment and land suitability with soil nutrients. In the end, it concluded the most significant GIS and RS tools for oil palm management come from the implementation of Machine Learning (ML) and Deep Learning (DL) knowledge in it which can be improved over time through recent technologies and variation analysis to enhance the results.
Evaluation The Accuracy of Oil Palm Tree Detection Using Deep Learning and Support Vector Machine Classifiers
Authors: Khalid Nafisah , Shahrol Nur Aina 
Published: July 2022

Abstract
Oil palm is one of the important sources of vegetable oil that is mostly consumed by the Malaysian citizen. Because the demand of vegetable oil is high in Malaysia, the expansion of oil palm tree plantation has been increasing rapidly. Remote sensing application in monitoring and detecting oil palm trees has become a very useful tool to help minimize the human energy to monitor in large plantations. The aim of this study is to evaluate the accuracy of oil palm tree detection using deep learning and support vector machine (SVM) approaches using high-resolution remote sensing images. Deep learning is one of the base frameworks for oil palm tree detection using high-resolution remote sensing images. Deep learning also is a counting tool provided in newest technology software such as ArcGIS Pro, where the tools use the pattern recognition concept as a template in detecting objects in a high-resolution image. In machine learning, support vector machines are supervised learning models with associated machine learning algorithms that analyse data for classification analysis. Based on this study, 91% of the oil palm trees detected using deep learning approach gained higher accuracy than SVM classifier with 86%. The accuracy of oil palm tree detection using deep learning is higher than the accuracy of support vector machine classifier. Based on the findings, deep learning approach create better object interpretation than SVM. The oil palm tree detection using both classification approaches had also been displayed by using a spatial map distribution for easier analysed and observation.
Utilising Landsat-8 OLI in determining Soil pH using single and combination band method for paddy fields area in Malaysia.
Authors: Salim Pauziyah Mohammad , Samsuddin Noramirah , Alias Ummi Atiqah , Abdul Rasid Muhammad Zamir , Kamaruddin Hasliana 
Published: July 2022

Abstract
The pH of a soil is a measure of its acidity or alkalinity. The pH of the soil is important in agricultural activities because it has an impact on crop yield. Remote sensing, Geographic Information Systems (GIS), and digital soil maps are becoming more appreciated in soil science studies. The research thus focuses on creating a predicted soil pH map of the study area using Landsat-8 satellite imagery and GIS. The single and combination of spectral bands were used to generate three models using simple linear regression. The results suggested that the approach is not sensitive enough for prediction of soil pH in the study area. R2 value obtained are 0.049 from Model 1, 0.016 from Model 3, and 0.0003 for Model 2. All the models indicate that the soil pH is in the acid situation but the full range of observed pH is not matched by any predicted model. In the validation process, Model 1 has an RMSE value of 0.397, whereas both Model 2 and 3 have RMSE value of 0.405. To obtain a more promising pH result, it is suggested to use indices such as vegetable indices (VI), salinity index (SI), and a combination of band ratios.
Fatigue fracture behavior of high-strength low-alloy steel for flexible marine riser in the high cycle fatigue regime
Authors: Zhang Dazheng , Gao Xiuhua , Wang Mingming , Li Weijuan , Guo Jing , Teng Yingxue , Zhang Wanshun 
Published: July 2022

Abstract
The relationship between microstructure, stress ratio, and fatigue fracture behavior of high-strength steel for flexible marine risers was investigated by microstructure characterization and fatigue test. The microstructure characteristic, S-N curve, fatigue fracture morphology, and fatigue crack morphology after quenching and tempering treatment and cyclic heat treatment, respectively, were evaluated. The results revealed that after cyclic heat treatment, the microstructure was refined considerably, the grain boundary density and the content of high-angle grain boundary increased, which inhibited the fatigue crack propagation and improved the fatigue strength. The average stress increased by increasing the stress ratio, which promoted the crack initiation and propagation; consequently, the fatigue strength and fatigue life of the tested steel decreased.
Analysis and improvement of self-heating effect based on GaN HEMT devices
Authors: Zuo Zhipeng , Tang Naiyun , Chen Hui 
Published: July 2022

Abstract
Gallium nitride high electron mobility transistor (GaN HEMT) applications in high-power and high-frequency environments can lead to high device temperatures due to the self-heating effect, thus limiting device performance and reliability. In order to address this problem, this paper changes the material and structure of the device. It successfully reduces the maximum temperature of the device to 335 K by using a new structure of the diamond substrate, diamond heat sink layer, and InGaN insertion layer. Simulation results show that the new structure has a 35% reduction in maximum temperature, a 61% increase in current, a 37% improvement in maximum transconductance, and a 35% improvement in current collapse. At the same time, the new structure also improves the electron mobility of the channel.
Theoretical and experimental evaluation of the distance dependence of fiber-based fluorescence and reflection measurements for laser lithotripsy
Authors: Lange Birgit , Ozimek Tomasz , Wießmeyer Judith Riccarda , Kramer Mario W , Merseburger Axel S , Brinkmann Ralf 
Published: July 2022

Abstract

Objectives. In laser lithotripsy, a green aiming beam overlying the infrared (IR) treatment radiation gives rise to reflection and fluorescence signals that can be measured via the treatment fiber. While stone autofluorescence is used for target detection, the condition of the fiber can be assessed based on its Fresnel reflection. For good applicability, fluorescence detection of stones should work even when the stone and fiber are not in direct contact. Fiber breakage detection, on the other hand, can be falsified if surfaces located in front of the fiber reflect light from the aiming laser back into it. For both applications, therefore, a fundamental investigation of the dependence of the signal amplitude on the distance between fiber and surface is important. Methods. Calculations of the signal drop of fluorescence or diffuse and specular reflection with increasing fiber distance were performed using ray tracing based on a simple geometric model for different fiber core diameters. Reflection signals from a mirror, diffuse reflector, human calculi, and porcine renal tissue placed in water were measured at varying distances (0–5 mm). For human calculi, fluorescence signals were recorded simultaneously. Results. The calculations showed a linear signal decrease down to ∼60% of the maximum signal (fiber in contact). The distance z at which the signal drops to for example 50% depends linearly on the diameter of the fiber core. For fibers used in lithotripsy and positioned in water, z
50% ranges from 0.55 mm (200 μm core diameter) to 2.73 mm, (1 mm core diameter). The calculations were in good agreement with the experimental results. Conclusions. The autofluorescence signals of stones can be measured in non-contact mode. Evaluating the Fresnel signal of the end face of the fiber to detect breakage is possible unless the fiber is situated less than some millimeters to reflecting surfaces.