bluuebunny/crossref_metadata_2025_split huggingface dataset:
Review about the Application of Biocompatible Materials in Oral Cavity Drug Delivery Systems
Authors: Ram Mriganka , Jakhmola Prabhav , Deshmukh Sonali , Dhatrak Pankaj 
Published: October 2024

Abstract
Biomaterials play a crucial role in modern medicine because they enable patients to heal from injury or sickness and restore function. Biomaterials—natural or synthetic—are employed in health care to preserve, improve, and restore impaired tissue or biological pro-cesses. Additionally, biomaterials can be used in biocompatible medication delivery systems as carriers. Drug delivery devices composed of biocompatible materials are essential for the safest release of drugs into the mouth cavity’s target tissues. Biomaterials with drug delivery systems are most suitable applications for dental implants, surgeries, and therapies for oral dis-eases such as peri-implantitis, periodontitis, and gingivitis. Therefore, the current review article’s goal is to concentrate on the application of biocompatible materials in drug delivery systems for oral and dental illnesses. The review focuses on several delivery methods made using natural polymeric materials such as gelatin, chitosan, calcium phosphate and alginate. Additionally, several alloys are used in medication complexes for transportation purposes. Even though research on biomaterials and their use in Drug Delivery System (DDS), has a significant influence on oral medicine in several dental illnesses, there are still certain limitations to improving oral cavity issues. A potential future lies in the combination of multimodal drug delivery with biomaterials, particularly natural polymers, in the treatment of oral disorders.
Analysis of Metamaterial Integration Effects on Antenna Structures
Authors: Yechuri Sivaramakrishna , Vijay Velpula , Laxma Reddy D. 
Published: October 2024

Abstract
This abstract offers a concise overview of the design and deployment of antennas employing metamaterials (MTM). The integration of MTM components within antenna architectures aims to optimize radiation characteristics and other pertinent antenna parameters. To understand the advantages associated with MTM utilization, two distinct antenna configurations incorporating metasurfaces (MTS) are analysed. MTS is commonly recognized as a two-dimensional version of MTM. The initial antenna design features a truncated corner squared patch as the primary radiating element, accompanied by a non-uniform MTS positioned within the same layer. This integration extends the impedance bandwidth and introduces additional bands within the high-frequency spectrum. The second configuration entails an array antenna comprising a 4 x 4 non-uniform patch array, a quadrature phase quarter-power divider, and an air gap interspersed between them. The inclusion of MTM elements in both antenna configurations is instrumental in enhancing overall antenna performance.
Optimization of Process parameters and Evaluation of Tensile Properties of Friction Stir Welded Dissimilar Joints (AA6082:AA5083) using Traditional and Hybrid Tool Pin Profiles
Authors: Ravi Kumar B.V.R. , Venkata Ramana M. , Sreenivasa Rao M.S. 
Published: October 2024

Abstract
Friction stir welding (FSW) system was pondered to generate weld joints with favourable strengths. Owed to the least set of process parameters are to be monitored thru welding process, this green welding method contains visible benefits upon further welding methods. This work focuses on the effect of process parameters implied during the process of joining and orientation of the tool pin profile towards the enhancing the mechanical properties of the dissimilar weldments made with AA6082 - AA5083 aluminium alloys. This paper covers the comparative study of weld tensile properties of the weldments made by utilizing hybrid and conventional tool pin profiles. This paper also covers the optimization of the weld parameters using Taguchi method. The UTS of hybrid tool pin weldments ranges from 160.05 MPa to 213.46 MPa.
Multi-Objective Optimization in Dry Turning of Hardened 20MnCr5 Using Random Forest Model
Authors: Venkata Ramana M. , Prasad M.V.R.D. , Yugeshwar C. 
Published: October 2024

Abstract
Dry machining has become a viable alternative to traditional machining processes, given the various drawbacks associated with the use of cutting fluids. In this work, 20MnCr5 has been selected as workpiece material to perform a dry turning operation after it had been case-hardened up to 51 HRc. It is crucial to find the behaviour of the hardened material under dry machining as the usage industries are going toward dry machining. For the experimentation PVD coated TH1000 insert grade is utilized. Depth of cut (DoC), cutting speed (Vc) and feed (f) were the input parameters. Surface roughness (Ra), tool wear (Tw), material removal rate (MRR) and power consumption (Pc) were the performance characteristics examined after the machining process. Multi-objective optimization was performed using grey relational analysis. In multi-objective optimization, the optimal condition was achieved at 120 m/min cutting speed, 0.1 mm depth of cut and 0.1 mm/rev feed. All the machine learning models developed had an accuracy of 90%. The predicted values from machine learning models were utilised to determine the optimal condition in multi-objective optimization. The results obtained for multi-objective optimization from the random forest model were also 0.1mm/rev feed, 120m/min cutting speed and 0.1 mm depth of cut. Feed was the factor that had most influenced by 14.78% on multi-objective optimization. It was observed that the models developed had high accuracy of 86.7% and there was significant harmony between actual and predicted values.
A Review of Thermoplastic Filament Extruder Design and Fabrication Technologies
Authors: Bhanuprakash Lokasani , Kumar Harikishor 
Published: October 2024

Abstract
Thermoplastic filament extrusion plays a crucial role in diverse fields, particularly in 3D printing and sustainable recycling. This review delves into the design and fabrication aspects of filament extruders, highlighting key functionalities and recent advancements. We explore essential components like screws, barrels, and dies, discussing their impact on material processing and filament quality. Different fabrication methods, including machining, 3D printing, and casting, are evaluated based on their advantages and limitations for various materials and complexity levels. The review further highlights recent innovations in modular components, integrated mixing systems, and advanced control systems. We also discuss the growing adoption of sustainable practices in extruder design and fabrication. Finally, the diverse applications of filament extruders are explored, covering 3D printing, filament recycling, composite material creation, and medical applications. We conclude by outlining emerging trends like multi-material printing, nanocomposites, and bio-based materials, emphasizing the future potential of this dynamic technology.
Comparative Study on Effect of Material on structural Performance of a Quadcopter Drone with ‘X- Frame’
Authors: Harika Chitkula , Sai Kumar A , Raghavendra Rao M V 
Published: October 2024

Abstract
Drones have become most important parts of the day-to-day life from a hobby to serious research. But, the operation and maintenance cost of these drones is very high due to multiple failures while flying. The most common component that experience heavy loads and undergo failure is frame of the drone. Hence, there is a need to address the best shape and material that can be used to reduce the operation cost due to catastrophic failures. The present work deals with design of a micro-drone frame which must withstand a load of at least 2 kgs. The ‘X’-shaped frame, were modelled and analysed at various load conditions for glass fiber, carbon fiber, aluminum alloy, and plastic materials. The results obtained for the different materials were compared and it was observed that carbon fiber is the preferred material for load-bearing applications but the cost for manufacturing and maintenance is very high. Aluminum alloy shows good strength and is cost effective. The ease of manufacturing and make it more suitable for drones. Plastic, though flexible and easy to fabricate, does not meet the required strength to weight ratio.
Research on PMSM sliding mode control based on a novel variable exponential convergence law
Authors: Wang Zexin , Chen Quanru , Feng Yao 
Published: October 2024

Abstract
To optimize the overshoot and anti-interference ability of permanent magnet motors (PMSM) under PI control and the traditional exponential approach law, a PMSM sliding mode control method with an improved exponential approximation law was proposed. The approach velocity is adaptively adjusted by the distance from the sliding mode surface to weaken the sliding mode jitter. By embedding a time-varying function into the constant velocity ring, with sliding mode surfaces as its variable, we verify the stability of the improved convergence law control by combining the Lyapunov function. Combined with the Lyapunov function to verify the stability of the improved approach law control, simulation and comparative tests are carried out on MATLAB/Simulink. The simulation results demonstrate that the control method has strong adaptability and low jitter compared to the traditional exponential approach law and PI control. It can also quickly and smoothly bring the system to the equilibrium point position in the event of an abrupt load change.
Comparative study on estimation and identification of electromechanical oscillation parameters
Authors: Wang Yuefan , Liu Yuhao , Liang Shutong , Zeng Qi 
Published: October 2024

Abstract
This study compares the performance of the bandpass filtering method and the Prony algorithm in identifying parameters of power system electromechanical oscillation. The bandpass filtering method suppresses noise by selectively passing signals in a certain frequency range, while the Prony algorithm directly estimates the signal parameters. In simulations, we find that the Prony algorithm outperforms the bandpass filtering method in extracting signal features. To further improve the performance of the Prony algorithm, we introduced a genetic algorithm for global optimization. This study provides an important reference for the selection of parameter identification methods for power system oscillation analysis, which is of practical importance for improving system stability and security. In addition, this study provides a new perspective on the application of genetic algorithms in signal processing and a theoretical basis for further research in related fields.
Design of Yolov4-Tiny convolutional neural network hardware accelerator based on FPGA
Authors: Du Wenhe , Chen Shuoyu , Wang Lei , Chai Ruili 
Published: October 2024

Abstract
This article designs a Yolov4 Tiny convolutional neural network hardware accelerator based on FPGA. A four-stage pipeline convolutional array structure has been proposed. In the design, the NC4HW4 parameter rearrangement and Im2col dimensionality reduction algorithm are used as the core to maximize the parallelism of matrix operations under limited resources. Secondly, a PE convolutional computing unit structure was designed, and a resource-efficient and highly reliable convolutional computing module was implemented by combining INT8 DSP resource reuse technology. Finally, the accelerator will be deployed on Xilinx’s Zynq7030 development board. The experimental results show that at a clock frequency of 130 MHz, the power consumption of the hardware accelerator is only 2.723 W, and the performance is 59.54 Gbps. Compared with related research, it has improved more than 2.1 times. This accelerator can complete hardware-accelerated computing tasks in object detection with high energy efficiency.
A new y-source high-gain buck-boost converter suitable for solar PV power generation system
Authors: Rong Desheng , Yu Yangyueyu 
Published: October 2024

Abstract
To reduce the pollution caused by fossil fuel combustion, the research on new energy power generation technologies such as distributed photovoltaics at home and abroad is becoming more and more in-depth, and the high-gain DC-DC converter, which is very important in the new energy power generation system, has also been rapidly developed. In this paper, a new type of high-gain DC-DC converter is proposed, which has a stronger boosting ability at a lower duty cycle and the characteristics of continuous input and output current and low voltage stress of components, and the duty cycle range is not limited by the ratio of coupled inductor turns. The working principle, voltage gain, expression of voltage, and current stress of each component of the converter in continuous conduction mode are analyzed at length, and an experimental prototype is built for experiments, which verifies the accuracy and practicability of the theoretical analysis.
VSG with additional damping controller for suppressing system low-frequency oscillations
Authors: Han Qi , Zhang Li 
Published: October 2024

Abstract
With the increasing attention paid to virtual synchronous generator (VSG) control technology in modern power systems, it not only provides necessary inertia and damping for the system but also introduces a new type of low-frequency oscillation mode, which not only retains the characteristics of low-frequency oscillation of synchronous generator (SG) but may also exacerbate this phenomenon. In response to this issue, this article proposes an innovative additional damping controller design aimed at providing effective active oscillation damping for SG without affecting the steady-state output power of VSG. By establishing a connection model between VSG and Single Machine Infinite Bus System (SMIB), this study deeply analyzes the specific impact of additional damping controller parameters on system stability. The simulation experiment results have verified the significant performance of the proposed controller in effectively suppressing low-frequency oscillations in the system.
A non-resonant piezoelectric generator for extracting energy from low-frequency magnetic field
Authors: He Wei , Luo Mingshan , Huang Baoan 
Published: October 2024

Abstract
This paper proposes a non-resonant piezoelectric generator to scavenge energy from a low-frequency magnetic field. The generator employs shear-mode piezoelectric single crystal plates (PMN-PT) assembled between NdFeB magnets and retaining plates. The use of the piezoelectric array helps to increase the total capacitance of the generator. Shear-mode vibrations are induced when a current flows through the power line, and the response of the generator to electric currents is improved due to the large piezoelectric voltage coefficient (g
15). Theoretical analysis and the shear piezoelectric constitutive equations have been conducted to study the electrical output characteristics, and the feasibility of the generator has been verified experimentally. The generator exhibits a good linear output under non-resonant conditions (50 Hz), and the maximal power shows an approximate quadratic increase with the electric current. The results indicate that the proposed generator has the potential for realistic applications.
Research on the simulation of single-event burnout in 1.2-kV GaN CAVET
Authors: Wei Yuan , Zhao Yuhao , Xu Binyi , Hu Kaifu , Zhang Xiaodong , Shen Chong 
Published: October 2024

Abstract
The simulation outcomes of single event burnout (SEB) in the common Gallium Nitride (GaN) Current Aperture Vertical Electron Transistor (CAVET) and Single Buffer Layer CAVET (SBL CAVET) were contrasted and elaborated in this thesis. In accordance with the employment of the 1.2-kV GaN CAVET, the boundary of the gate dielectric and source electrode region is the utmost sensitive ion’s strike point to SEB. The simulation of SBL’s robustness CAVET possessing various single buffer layer designs against a heavy-ion was conducted. From this, the compromising of the largest temperature near the source electrode by the doping concentration and the buffer layer’s thickness was realized. When it comes to the heavy ion, under the situation of transferring a linear energy of 0.9 pC/µm vertically, the threshold voltage of SEB for SBL-CAVET is 1, 250 V instead of CAVET’s 650 V.
MBGD-LSTNet-based IGBT aging fault prediction for photovoltaic inverters
Authors: Wang Tingting , Yang Jie , Xu Ziqian , Yu Chao , Liu Yanxi , Liu Xiao 
Published: October 2024

Abstract
The photovoltaic inverter serves as the core component of solar photovoltaic power generation equipment. However, during its operational lifecycle, common issues such as aging of the IGBT on the inverter’s DC side often arise. This aging not only hinders the inverter’s output power and efficiency but also undermines the stable operation of the entire photovoltaic power generation system. In this paper, to address the aging faults of DC-side IGBTs in PV inverters, a novel approach utilizing the Long- and Short-term Time-series Network (LSTNet) is introduced for aging fault prediction, which employs the transient turn-off spike voltage as a key characteristic parameter. Additionally, the Mini-Batch Gradient Descent (MBGT) method is employed to optimize the model, enabling more accurate predictions of aging faults and improved handling of noisy data. By utilizing the accelerated aging dataset for IGBTs provided by the NASA test center, the model is constructed and subjected to rigorous testing for comprehensive evaluation. By analyzing the experimental results for the comparative analysis of the model error, compared with the recurrent neural network and wavelet neural network prediction model, the MBGD-LSTNet network model exhibits reduced error and enhanced prediction accuracy, significantly improving the precision of forecasting aging faults in IGBTs.
Research on metrology method of surface magnetic field based on the nitrogen-vacancy center (NV) in diamonds
Authors: Sun Jinglu , Zhang Peiyan , Ji Rui , Zhang Xiangyang 
Published: October 2024

Abstract
This paper proposes a novel metrology method for surface magnetic fields based on the nitrogen-vacancy (NV) center in a diamond. A coplanar waveguide is used to calibrate the NV center, and its standard values are derived from its simulation results. This metrology method involves leveraging quantum NV scanning technology to capture the Optically Detected Magnetic Resonance (ODMR) spectrum and Rabi oscillation curves of the waveguide, and test data of the surface magnetic field of the coplanar waveguide are meticulously extrapolated through a rigorous fitting process. We compare the test data and simulation results to verify the accuracy of the metrology method. This method promises to enhance the fidelity of magnetic field distribution measurements on chip surfaces, thereby elevating the standards of chip testing accuracy for future applications.
Exogenous data enhancement-driven load cell prognostics
Authors: Zhang Ni , Wang Peng , Wang Chu , Wang Bin , Zhang Yufang 
Published: October 2024

Abstract
Load cells are widely used in various engineering applications. With the increase in service time, its performance tends to decline, resulting in measurement errors. Judging the deterioration degree of the load cell by error and predicting its remaining service life are the key prerequisites to increasing the performance of the load cell and decreasing the maintenance charge. Many factors may cause the load cell to deteriorate, the most prominent of which is temperature. The forecasting method, employing long-term and short-term memory networks, demonstrates strong memory capability for short-term historical data in time series. However, The Long Short-Term Memory Networks prediction algorithm, prone to succumbing to local optima and accumulating errors in long-term prognostication, entails intricate challenges that can not be used for Remaining Useful Life estimation. Therefore, it is suggested that the ambient temperature be used as an additional input to increase the accuracy of the deterioration trend forecast of the load cell. The result of this experiment shows that the forecast accuracy of this method in Remaining Useful Life estimation is 95.6126%, and it is very robust.
Research on fault location and distance measurement methods for low current grounding systems in short distances
Authors: Bai Dikai , Wu Weili , Yang Puwei 
Published: October 2024

Abstract
As the scale of the power system continues to expand, the quality of the power source is crucial to the stable operation of the electric network, making the automation of feeders an inevitable trend in power system development. In this context, this paper takes errors in low current grounding systems as a research subject. The mechanism of grounding fault occurrence is analyzed first, followed by the functional modeling of fault voltage and current, and a formulation describing changes in resistance at the fault point is provided. Subsequently, a neural network-based fault distance measurement model incorporating the resistance relationship is proposed. Extensive simulations of short-distance grounding fault distance measurements were conducted, achieving a high degree of fit. The results demonstrate that the neural network fault distance measurement model offers minimal prediction error for fault distance and significant practical research significance, making it suitable for application in engineering practices.
In-situ Thermal resistance measurement of GaN HEMTs
Authors: Yao Zhanwu , Feng Shiwei , Li Xuan , You Binyu , Lu Xiaozhuang , Bai Kun , Pan Shijie 
Published: October 2024

Abstract
The electrical method allows for quick, non-destructive, and accurate thermal resistance assessment in power devices. However, in practical engineering applications, the presence of decoupling capacitors affects the acquisition of the in-situ thermal resistance of the devices. Therefore, periodic thermal resistance monitoring requires repeated disassembly of the devices, which can introduce new reliability issues. This paper employs an operational circuit design to develop a method for in-situ thermal resistance measurement. The feasibility of this method is validated through the analysis of static and dynamic characteristics.
Research on optimal scheduling of virtual power plant considering demand response under carbon-green certificate trading mechanism
Authors: Yi Yingmin , Zhou Dingsong , Yuan Yiwei , Yu Yongjun 
Published: October 2024

Abstract
With the increasingly serious environmental problems and the randomness of wind-power output, the virtual power plant (VPP) has a positive significance for realizing the dual carbon goal and promoting the stable operation of the power system. To minimize the cost and the carbon emission of VPP operation, this paper proposes a VPP optimal dispatching model considering demand response (DR) under the carbon-green certificate trading mechanism. Firstly, the VPP operation architecture, which can meet various load requirements of electric heating and cooling, is established, and each component equipment of the system is modeled. Afterward, the price and alternative demand response models are constructed, respectively, and the carbon trading (CT) and green certificate trading (GCT) models are analyzed. Then, considering energy purchase cost, system maintenance cost, and carbon-green certificate trading cost, a low-carbon economic dispatching model is formulated to minimize the operational costs of the VPP throughout the dispatching cycle. Finally, the optimization model is solved; the total operating cost of the VPP under this model is 16633.15 yuan, and the carbon emission is 6094.75 kg. Experimental results prove that this optimized model can reduce system operational costs while simultaneously considering environmental benefits.