bluuebunny/crossref_metadata_2025 huggingface dataset:
Cultural Strategy of Jaranan Arts in the Midst of Modernization: Portrait of Jaranan Okta Putri Kencono in Surabaya City
Authors: Oktavia Nur Laili , Sudrajat Arief
Published: December 2024

Jaranan as the traditional heritage of the people of East Java, Surabaya faces great challenges due to urbanization and globalization. The Jaranan Okta Putri Kencono group, although new, managed to survive in the midst of social changes and competition with other art groups. This study examines the cultural strategies applied by this group to adapt to modernization. This research reveals how technological and social adaptations are applied in maintaining the existence of traditional arts amid declining interest in modern entertainment. This qualitative research examines Okta Putri Kencono cultural strategy in adapting to modernization in Surabaya. The study was conducted in Lakarsantri and Wiyung, Surabaya which were chosen because of their relevance to the group's origins and appearance. We triangulated between observation, interview, and documentation as our data collection methods. Interview was conducted with various members of the Okta Putri Kencono group, consisting of consists of the founder, leader, and bopo; bopo senior; and sound system administrator.The study show that three phases faced by Jaranan Okta Putri Kencono group are mythical phase, ontological phase, and functionalist phase. In the mystical phase, Jaranan still maintains spiritual rituals such as offerings as a tribute to ancestors. The ontological phase is characterized by the reinterpretation of traditional values to answer the challenges of modern society, including adaptation to performance elements without leaving traditional identities. Meanwhile, the functionalist phase adapts to modernization, Okta Putri Kencono integrates modern elements, such as audiovisual technology, updated story themes, and collaborations with young artists and creative communities. In essence, the Jaranan Okta Putri Kencono group has successfully navigated the challenges of modernity while preserving its rich cultural heritage. By adapting to changing times, the group ensures the continued vitality of the Jaranan tradition for future generations.
DAMPAK KINERJA PERUSAHAAN, LIKUIDITAS DAN UKURAN PERUSAHAAN TERHADAP TRANSPARANSI CSR : PERSPEKTIF KEBERLANJUTAN KORPORAT
Authors: Dewi Putu Pande R. Aprilyani , Budiadnyan Ni Putu , Kustina Ketut Tanti , Permana Gusi Putu Lestara
Published: December 2024

Seiring dengan meningkatnya perhatian publik terhadap isu keberlanjutan dan tanggung jawab sosial, perusahaan diharapkan untuk lebih transparan dalam mengungkapkan aktivitas corporate social responsibility (CSR) mereka sebagai bagian dari strategi bisnis yang berkelanjutan. Seiring dengan meningkatnya kesadaran global tentang isu-isu sosial dan lingkungan, ada kecenderungan bahwa perusahaan dengan kinerja keuangan yang baik semakin terbuka dalam pengungkapan tanggung jawab sosialnya. Penelitian ini dilakukan di perusahaan pertambangan periode 2019-2021 yang terdaftar di Bursa Efek Indonesia. Penentuan sampel menggunakan purposive sampling dan mendapatkan sampel sebanyak 42 perusahaan pertambangan. Hasil penelitian menunjukan bahwa kinerja perusahaan tidak berpengaruh pada pengungkapan corporate social responsibility dan likuiditas tidak berpengaruh pada pengungkapan corporate social responsibility. Sedangkan ukuran perusahaan berpengaruh positif pada pengungkapan corporate social responsibility.
OPTIMIZATION OF THE EXTRACTION PROCESS OF BIOLOGICALLY ACTIVE COMPLEXES FROM PSORALEA DRUPACEA BGE ROOTS
Authors: Baisalova G. , Zhunisova A. , Shukirbekova A. , Torsykbayeva B. , Imangaliyeva B.
Published: December 2024

In recent years, due to the emergence of previously unknown types of viral diseases (avian influenza, swine flu type A/H1N1), the search for new drugs against bacteria and viruses has become a very pressing problem. Synthetic drugs, which, in addition to the obvious antiviral and antiviricidal action, have a number of side effects on the nervous, respiratory, digestive, hepatobiliary systems, and also cause allergic reactions as a result predominate among modern drugs in this field. In terms of side effects of herbal medicines, the advantage is to reduce the effects, since the biosynthesis of plant-based drugs does not contradict the biosynthesis of humans and animals. In the course of solving these current problems, it has been established that the dry extract obtained from the roots of Psoralea drupacea Bge. is active against strains of avian influenza viruses. The article presents the results of research related to the optimization of the extraction process of this substance. The influence of various factors of the extraction process: extractant nature, raw material grinding degree, extraction duration, extraction method (sedimentation (maceration), percolation, extraction with a boiling solvent in a Soxhlet apparatus) on the total yield of extractive substances and the amount of furocoumarins was studied. The results of the research demonstrated that the most effective extractant is ethanol, and the optimal degree of raw material grinding is 1.25 mm. The most optimal extraction method is raw material extraction with ethanol by Soxhlet apparatus. In this case, after 3 days, the dry extract yield was high (5.80%) and the maximum amount of furocoumarins was also high (72.34%). Nevertheless, maceration with stirring and heating can give good results, and the advantage of the process is its simplicity and the ability to increase the raw material upload.
ПОЛУЧЕНИЕ ГИДРОГЕЛЕВЫХ ПОВЯЗОК НА ОСНОВЕ СОПОЛИМЕРОВ ПОЛИВИНИЛОВОГО СПИРТА, 2-ГИДРОКСИЭТИЛАКРИЛАТА И N-ВИНИЛКАПРОЛАКТАМА С БАКТЕРИЦИДНЫМ ДЕЙСТВИЕМ
Authors: Хакимов М.Я. , Абдулетип Д.Т. , Уркимбаева П.И. , Ирмухаметова Г.С. , Кенесова З.А.
Published: December 2024

В настоящее время раневые повязки на полимерной основе являются эффективными лекарственными формами ускоряющие заживление ран, способные предотвращать проникновение микроорганизмов, обладающие достаточной проницаемостью для воздуха, эластичностью и отсутствием аллергических действий.К настоящему времени так и не получили раневую повязку, отвечающую всем предъявляемым требованиям. Целью данной работы является синтез гидрогелевых повязок на основе сшитых сополимеров N-винилкапролактама - 2-гидроксиэтилакрилата с поливиниловым спиртом с добавлением наночастиц оксида меди (II) и изучение их основных характеристик. Гидрогелевые повязки получали методом сшивки с использованием радиационного излучения. Исследованы их основные физико-механические и бактериостатические свойства. Получены гидрогелевые повязки на основе ПВС-ГЭА:NВКЛ различного состава. Обнаружено, что с уменьшением концентрации наночастиц CuO (II) в составе повязок, гель выход увеличивается. При концентрации наночастиц 0.075 % наблюдается максимальная степень набухания в воде (4.19 г/г) и физиологическом растворе (4.14 г/г). Установлено, что с увеличением концентрации наночастиц CuO (II), уменьшается предел деформации, а также механические свойства, что обусловлено повышением плотности сшивки гидрогеля. Образцы повязок с концентрацией наночастиц 0.1%, обладают незначительным бактериостатическим действием в отношении тест-штамма Escherichia coli и Staphylococcus aureus в сравнении с контрольным образцом без наночастиц оксида меди (II), зона подавления составила в среднем 12±1 мм. Установлено, что гидрогелевые повязки при соотношенииПВС-ГЭА:NВКЛ = 60-20:20 и 60-30:10 моль.% с концентрацией наночастиц CuO (II) 0.1%, обладают незначительным бактериостатическим действием.
Study on Electromechanical Coupling Dynamic Characteristics of Cabin Door Drive System for Aircraft
Authors: Hu Xiaohang , Zhang Ming , Zhao Yapan
Published: December 2024

Taking the aircraft cabin door drive system as the focus of this research, this paper establishes a dynamic model that incorporates the rigid-flexible coupling of the drive mechanism, as well as a control system model for the permanent magnet synchronous motor. Building on this foundation, an integrated mechatronics simulation analysis model for the cabin door drive system is developed. In accordance with the actual operational requirements of the system, the effects of various driving forms on the cabin door drive system are analyzed. The research findings indicate that all dynamic responses of the cabin door drive system exhibit fluctuations. Under various driving forms, the speed of the cabin door and the power of the motor show the most significant differences, while there is no notable difference in the deployment angle of the cabin door and the output torque of the motor. Specifically, the maximum speed of the cabin door in driving form 1 is approximately 10.1 r/min, while the maximum power of the motor is around 2469 W. This study provides theoretical guidance for the design, speed regulation, and monitoring of cabin door drive systems.
Online Inductor Identification Method for Synchronous Reluctance Motors Based on High-Frequency Square-Wave Voltage Injection
Authors: Fang Lianghe , Liu Jinpeng , Wang Xiuhe
Published: December 2024

The performance of sensorless control in synchronous reluctance motors (SynRMs) can be significantly affected by the nonlinear characteristics of inductance. To resolve this challenge, a method that employs high-frequency square-wave voltage signals for estimating inductance in real-time has been introduced. Considering the substantial variation of SynRM inductance with current, a motor model is developed that incorporates inductance variation as a function of current, providing a more accurate representation of real-world conditions. Injecting high-frequency voltages in the crossed and straight axes responds to corresponding high-frequency currents. A simple calculation of the current signal yields the inductance. The effectiveness for online inductance identification of the proposed method is validated through MATLAB simulations, demonstrating computational simplicity, accurate tracking, and high precision.
Design and Construction of an Automatic Dispenser for the Visually Impaired Using Microcontroller Technology
Authors: Febriandirza Arafat , Sahuri Abdiel Alpriyan Gempa Alamsyah
Published: December 2024

Water is a fundamental need for humans, comprising 70% of the human body. Dispensers are commonly used due to their convenience and hygienic nature for storing drinking water. Visually impaired individuals often face challenges in using conventional dispensers, which can lead to injuries when retrieving water. This study aims to design an automatic dispenser to assist the visually impaired, reducing the risk of injury when using dispensers. The dispenser is designed with two microcontrollers: Atmega32 and ESP8266. The ESP8266 microcontroller has a Wi-Fi feature, enabling it to connect to the internet. The dispenser uses two ultrasonic sensors to detect objects obstructing the sensor’s beam, helping control the flow of water. The system communicates between the two microcontrollers and connects to the Telegram app via Wi-Fi, allowing for remote monitoring and control. The Arduino Uno microcontroller serves as the system’s control center.
Design of Distributed Motor Bearing Health Management System Based on Embedded Edge and Cloud Platform
Authors: Huang Yijun , Zeng Zhaoyang , Jiang Jueyi , Zhu Qingyu
Published: December 2024

In order to solve the problems of large-scale factory workshop, such as large number of motors, changeable working conditions of motor bearings, frequent faults and difficulties in diagnosis, a distributed motor bearing health management system based on embedded edge and cloud platform is designed. This system uses Raspberry Pi and STM32 to build a low-cost embedded edge motor condition monitoring platform, and deploys the lightweight bearing fault diagnosis algorithm in it, and then uses the Internet of things technology to connect the edge end with the remote server cloud platform to make web pages to realize motor bearing fault diagnosis and motor running status monitoring. The test results show that the system can effectively realize the health management of the motor and facilitate the maintenance and management of the motor.
Optimization of High-Pressure Gas Cylinder Design Using Aluminum Alloy and Fiber Winding Technology Under High Temperature Conditions
Authors: Huang Song , Chen Jie , He Ziqiang , Li Xiuquan , Li Zongshan , Zhang Longyi
Published: December 2024

Given the weight and corrosion resistance limitations of traditional steel gas cylinders, this study proposes the use of lightweight, high-strength, and corrosion-resistant aluminum alloy as an alternative material. The research specifically focuses on analyzing the impact of winding technology and materials on the stress and strain of the gas cylinder at different temperatures (600°C) and pressures (from 15Mpa to 22.5Mpa), with the aim of optimizing the design and manufacturing process of the gas cylinder to meet more stringent engineering requirements. The study indicates that under high temperature (600°C) and high pressure (15Mpa) conditions, Type B gas cylinders exhibit lower average equivalent stress (573.66Mpa) and average stress intensity (589.36Mpa) compared to Types A and C. The average deformation is 0.01313m/m, slightly higher than that of Type C, but overall, Type B performs better. When the gas cylinder’s volume increases, the average equivalent stress, stress intensity, and equivalent elastic strain all decrease, albeit with relatively minor overall changes. When the temperature rises to 1000°C, the average equivalent stress reaches 927.96Mpa, reflecting the impact of temperature on material expansion and internal stress. These findings are of significant practical importance for guiding the future design and manufacturing of high-pressure gas cylinders to meet higher performance and safety requirements.
Building SU-8 Microstructure Suitable for PDMS CGG from Bottom up
Authors: Chen Qiming , Fu Renxuan , Song Xianwen
Published: December 2024

According to the requirement for the concentration gradient generator (CGG) in the chip laboratory, a dose-modulated exposure from bottom-up technique was proposed to fabricate SU-8 microstructure. The SU-8 microstructure is used for PDMS CGG. For thick SU-8 photoresist layer, during a one-time exposure, it is easy to over-expose at the top and under-expose at the bottom, which then forms a T-shaped structure. The technique in this article using dose-modulated low power multiple exposure from bottom-up. At last, the photochemical reaction channel inside SU-8 is formed, and SU-8 is fully exposed. This technique effectively suppresses forming the T-shaped structure, and also suppress photoresist liftoff. In this work, after 55 times exposure, a right angle three-level SU-8 CGG structure with a height of 45 μm was fabricated. The width of the single microchannel is 50 μm. The PDMS CGG matches the SU-8 structure. The microchannels are clear with vertical sidewalls.
A Stamping Die That Reduces Machining Allowances
Authors: Lv Guimei , Liu Xiayun , Li Shuai
Published: December 2024

In the field of high-voltage three-phase asynchronous motor manufacturing, stator punching piece, rotor punching piece is a necessary part, rotor punching piece through the stacking, casting aluminium, wear shaft, manufactured into cast aluminium rotor, cast aluminium rotor machined with a lathe and then manufactured into a rotor, made from the cast aluminium rotor into a rotor, there will be a machining allowance, the size of the machining allowance determines the efficiency of the production, in order to improve the efficiency of the production, reduce machining allowances, when manufacturing stator punches and rotor punches,special stamping dies are required to ensure that processing allowances are reduced and production efficiency is increased.
Sensorless Speed Control of Induction Motor Drives Using Disturbance Observer and Adaptive PID Controller
Authors: Indriawati Katherin , Supriyanto Ricko
Published: December 2024

This study discusses the development of a sensorless speed control method for induction motors using an adaptive PID Controller. An approach is proposed that utilizes a disturbance observer to estimate the speed of the induction motor. Subsequently, an adaptive PID Controller is implemented to regulate speed control with real-time parameter adjustments based on the motor’s operating conditions. Experimental results show that the combination of these two methods enhances dynamic response performance, particularly in avoiding overshoot and steady-state error. By applying this technique, effective control is achieved without the need for additional sensor devices, leading to reduced costs and system complexity. This research makes an important contribution to the development of more efficient and reliable induction motor technology and opens avenues for further research in sensorless control applications.
Research on the Strategy of Wind Power Consumption Improvement Based on the Cooperative Scheduling of Thermal Power Units
Authors: Li Chao , Li Xin , Liu Jiahe , Miao Fengze , Hao Xuliang , Li Xiaolei , Liu Hongcheng , Wang Hao
Published: December 2024

In view of the structural contradiction between heating and wind power consumption of thermoelectric units during heating period, a thermal power cooperative dispatching support system is established. Based on platform layer, computing layer and collaboration layer, data acquisition and processing, unit regulation capacity calculation and cooperative scheduling are realized respectively. On the premise of ensuring the quality of data collection, according to the set of unit operation constraints, the system constructs a calculation model of peak regulation margin based on the operation feasible region of cogeneration units, and realizes the deep mining of the peak regulation capacity of generating units under certain heat supply. Through collaborative optimization of power load distribution in the region, the level of wind power consumption can be improved. The operation results of the system in Liaoning Provincial dispatching Center show that the thermoelectric units can not only meet the heating demand, but also maintain safe operation at a lower generation load level. Through collaborative optimization of load distribution, the overall peak regulation capacity of thermoelectric units has been increased by 14.8%, and the absorption capacity of clean energy has been greatly improved.
Real-Time Control Applications Using Rapid Modeling Based on Surface Electromyography
Authors: Gong Fenghao , Bai Dianchun , Liu Zhuo , Li Ruiji , Lin Zhongpeng
Published: December 2024

Surface electromyography (sEMG) directly reflects muscle activity and has been widely applied in areas such as prosthetics, rehabilitation, exoskeletons, and human-computer interaction. However, traditional sEMG modeling methods are often constrained by the complexity of data and computation time, making it difficult to meet real-time control requirements. This paper proposes a rapid modeling method based on sEMG, exploring its application in hand assistive devices and medical rehabilitation. By designing sEMG datasets, extracting transient features, and using deep learning algorithms (Vision Transformer and ConvNext), the method effectively reduces modeling time and improves classification accuracy. Experimental results demonstrate that this method is both efficient and accurate in real-time control applications, making it suitable for various real-time interactive systems.
PMSM Nonlinear Model Predictive Control Based on Analytical Formal Control Law
Authors: Ye Bin , Li Hui
Published: December 2024

Permanent Magnet Synchronous Motor (PMSM) is a system with multivariable, nonlinear, and strong coupling characteristics. Due to the uncertainty of model parameters and external load disturbances, traditional linear control methods often struggle to achieve effective control. Considering the significant advantages of Nonlinear Model Predictive Control (NMPC) in handling complex constraint optimization of nonlinear systems, as well as its ability to reduce computational burden and improve system robustness, Nonlinear Model Predictive Control Method with Analytical Formal Control Law (ANMPC) in this paper is used to design PMSM controller, and conducts simulation analysis on the prediction time domain and control order. The ANMPC method behaves well in speed tracking behavior, and the system has strong anti-interference ability.
Design of Ad Hoc Network System for Swarm Drone Based on SPMA+TDMA Hybrid Multi-Access
Authors: Guo Ming-ming , Li Jia , Wang Feng , Qie Qiu-yue , Wang Li-bo
Published: December 2024

According to the characteristics of swarm drone ad network, by studying the advantages and disadvantages of SPMA protocol and TDMA protocol, this design proposes the “SPMA + TDMA” hybrid multi-access technology scheme, completes the overall design of swarm drone terminal, solves the channel occupancy and conflict of a large number of swarm drones, and realizes high priority and low delay transmission.
Optimizing Thermo-Electric Generation with Quasi-Z-Source Converter in Energy Harvesting for Wearable Devices
Authors: Lotfy Mostafa Wageh , Hussein Aziza I.
Published: December 2024

Recent advances in semiconductors industry and microelectronics have created new opportunities for integrating various technologies in energy harvesting projects. These advancements have simplified the process of capturing energy from different sources, such as thermal energy, and converting it into electrical power. Thermo-Electric Generators (TEGs) are commonly used in many applications such as wearable devices. However Thermo-Electric Generators produce very low output voltages, which is insufficient for most low-power electronic circuits to operate. Therefore, a boost converter is essential to step up the voltage output from the TEG to a usable level. In this paper, a DC-DC converter with a high performance in terms of voltage gain is implemented. The proposed quasi-Z-source (q-ZSC) DC-DC converter not only offers high voltage gain but also several significant advantages. The proposed q-ZSC is capable of both boosting and regulating the voltage output efficiently, even under variable input conditions, making it highly suitable for low-power energy harvesting systems such as Thermo-Electric Generators . The design is simulated using MATLAB Simulink software, focusing on integrated circuits, with a strong emphasis on optimizing the circuit’s efficiency. This work underscores critical factors in improving energy harvesting circuits, enhancing their performance and effectiveness in low-power applications for wearable technology.
A New Type of Ball Screw Design and Loaded Experimental Research
Authors: Li Shuai
Published: December 2024

Aiming at the traditional ball screws with insufficient number of payload balls which are easily deformed by the load, a conservative design scheme of inner and outer double-turn large-capacity loaded ball screws is proposed. Separately on the large-capacity ball screw axial and radial load and equivalent strain analysis, the analysis results show that: when the screw is subjected to radial load, the deformation area of the screw is concentrated in the nut and the support position at both ends. Finally, it is concluded that in the case of unchanged screw diameter or nut conditions, increasing the payload ball can also increase the stiffness of the ballscrew, thus reducing the impact of the deformation of the screw due to the load. At the same time, the feed speed of the screw becomes faster and the required driving torque is reduced.
Advanced Numerical Modeling of Electrohydraulic Sheet Metal Formability
Authors: Boutana Ilhem
Published: December 2024

Electrohydraulic Forming (EHF) is a cutting-edge manufacturing technique that leverages high-voltage capacitor discharges within a water-filled chamber to generate pulsed pressure waves for the rapid shaping of sheet metal. This versatile process accommodates both free-form shaping and die-based forming, making it ideal for a wide range of metal-forming applications. In this paper, we introduce an innovative numerical model, developed using COMSOL Multiphysics, to simulate sheet metal deformation through the EHF method, with a focus on the localized pressure generated by electrical discharge. Leveraging the Johnson-Cook model for plastic deformation, we perform a preliminary analysis of the formability of various materials under free EHF conditions. Our findings provide valuable insights into optimizing EHF parameters for enhanced material formability and precision in industrial applications.
Identification of an Industrial Proportional Valve Using Levenberg-Marquardt Algorithm
Authors: Belguidoum Fawzi , Sari Bilal , Jia Jiajia
Published: December 2024

This paper presents the dynamic modeling and parameter identification of an industrial actuator known as a voice coil proportional valve. This actuator is crucial for precise position control in industrial hydraulic cylinders, particularly when high accuracy, smooth motion, high speed, and acceleration are required. Accurate parametric modeling of the system is essential for effective control and monitoring. However, identifying the physical parameters of this model is challenging due to its nonlinear parameter dependencies, rendering traditional least-squares methods unsuitable. To address this, the Levenberg-Marquardt algorithm is proposed as a solution for nonlinear parameter identification. Both simulations and experimental data are employed to validate the proposed continuous parametric model. Despite the presence of noisy data, the results demonstrate the effectiveness of the proposed approach.
Analysis of the Causes of Fouling in Ceramic Ultrafiltration Membrane in the Heating Network Water Supplement Treatment System of Thermal Power Plants
Authors: Xie Zheng , Liu Jin , Cui Desheng
Published: December 2024

This article is based on the analysis of ultrafiltration membrane technology and its application in environmental engineering water treatment, and deeply explores the specific application of ultrafiltration membrane technology in environmental engineering water treatment. Ultrafiltration membrane pollution is an important factor limiting the application of ultrafiltration membranes in water treatment, which directly leads to an increase in the operation and maintenance costs of ultrafiltration processes and a significant reduction in membrane service life. Therefore, the article analyzes ultrafiltration membrane fouling and blockage, in order to provide useful references for the progress of ultrafiltration membrane technology and its development in the field of water treatment[1].
Analysis of Self-Destruction Mechanisms for Two Rocket Safety Control Systems
Authors: Wang Haifeng , Wen Xun , Chang Yi , Wang Gang
Published: December 2024

The safety control self-destruction system is a key safeguard for rocket flight safety which would be highly reliable. This paper summarized the equipment composition, self-destruction modes, and processes of the safety control self-destruction systems for two commercial rockets. It provided their safety control intervals, safety control criteria, power supply, safety control circuits, and self-destruction methods. It analyzed the shortcomings and weak links of the two safety control self-destruction systems and proposed several suggestions for subsequent improvements. When a flight malfunction occurred, the Type A rocket successfully executed autonomous control self-destruction, whereas the Type B rocket’s self-destruction system failed. Upon analysis, it was found that in addition to the timing of the fault occurrence as an external, these were also many key internal factors. For instance, whether there is an independent autonomous control power supply and how the safety control circle is set up in terms of electrical aspects. Research indicates that these factors directly affect the outcome of self-destruction control after an incident.
Multifunctional Operation Strategy of Paralleled VSG Based on Droop Control and Improved Second-Order Generalized Integrator Phase-Locked Loop
Authors: Chen Sichao , Lian Deqiang , Cai Qi , Weng Liguo , Qin Bo , Wang Pengcheng , Lou Yinan
Published: December 2024

With global resource shortages and environmental degradation, the development of clean energy has become a key focus. The increasing integration of distributed renewable energy sources like solar and wind into the grid presents challenges due to their instability, affecting microgrid voltage and frequency. Frequency stability is crucial for the grid operation and user safety, with fluctuations potentially causing equipment failures. The Power Conversion System (PCS), as the core of energy storage systems, must provide traditional charge/discharge functions and off-grid power during outages for critical loads. Current PCS parallel control methods include interconnected and non-interconnected approaches, with the latter offering advantages such as module independence and reliability but prone to instability due to a lack of inertia. Introducing Virtual Synchronous Generators (VSG) can enhance stability against power disturbances and increase system capacity. However, improper control parameter settings in multi-unit VSG systems can lead to active power oscillations during grid voltage and frequency changes, affecting overall stability. Thus, effective solutions for multi-unit parallel stability in non-interconnected control are crucial. In response to the inadequacies of existing technologies in addressing stability issues in parallel control without interconnection lines, this paper proposes an improved VSG operation strategy. Aimed at finely controlling the VSG system by combining droop control and an improved second-order generalized integrator phase-locked loop, the strategy aims to enhance its stability and performance under parallel control without interconnection lines. The simulation results show that the control strategy can effectively solve the active power oscillation caused by the sudden change of voltage and frequency of the power grid, so as to ensure the stability of the whole system, improve the detection accuracy of the power grid, and reduce the THD of the multi-unit VSG system in the transient and steady state.
Design and Implement of a Super-Twisting ESO-Based Impedance Control for Lower Limb Exoskeleton
Authors: Zhang Wenhao , Ji Pingxin , Song Peng , Liu Hao , Li Qiang , Mo Xinmin
Published: December 2024

This brief proposes a super-twisting ESO-based impedance control for lower limb exoskeleton to promote the human-machine interaction-based coordination and stability with the unmodeled tire dynamics and external perturbations into consideration. The kinetics both in hip and knee joint is constructed and expected to match the authentic angle curve which depicts the moving organization in real-time. Then, by insetting a generalized super-twisting algorithm, the super-twisting ESO (STESO) is introduced to capture the immeasurable entire disturbances by utilizing the angle state merely. Subsequently, by quoting the impedance control theory, the global terminal angles can be calculated and adjusted basing the human-interaction force, even on the environment mapping. Finally, some theoretical analysis and simulations are collected and provided to demonstrate the correctness and effectiveness for proposed method.
Research on Target Price Estimation Model of Aircraft
Authors: Guo Hongfeng , Qiao Li , Shi Rongbo , Luo Yong
Published: December 2024

During the product design stage, the economic argumentation and the product technical demonstration are equally crucial. This paper tries to establish a target price estimation model by combining the analogy method, parametric method and engineering estimation method. After carrying out the target price estimation measurement at the level of product drawing number and comparing it with the actual projects cost, the estimated level and the actual cost deviation range is (-5.0%, +5.9%). The results show that the target price estimation model can support the economic argumentation and the cost control.
Solar-Powered and IOT-Aided Irrigation System for Small Farm-Scale Operation
Authors: Eya Candidus U. , Madu Malachy C. , Agomuo Hyginus , Nathan Nwokocha , Ogwuche Joseph Okwu , Ezea Obinna Fidelis
Published: December 2024

This article presents a Solar-powered and IOT-aided irrigation system for small farm-scale operation. The solar panel ensures a reliable and cost-efficient power source especially in remotest villages where there is no evidence of grid utility power supply. The system employs soil moisture sensors and a Wi-Fi module connected to a microcontroller for the supervision and control of the water pumping process, creating a connected irrigation solution enabled by the Internet of Things (IoT). This system instantly sends sensor data to the Blynk mobile application, enabling farmers to access and monitor the irrigation system through the app. Furthermore, the incorporation of IoT technology allows for the monitoring of flowrate, battery voltage, reservoir water volume, and soil sample water level. Inverted staircase and carrier-based modulation is used to generate firing pulses for Power MOSFETS switches. This system achieves improved water usage efficiency, streamlining farming operations and ultimately reducing electricity consumption and operational costs by harnessing solar energy. This research is applicable to both small-scale farms and, in the long run, larger agricultural lands.
Design of UWB/IMU Fusion Positioning System Based on Topological Constraints
Authors: Yao Haiyan , Guo Qiang , Zhang Xufeng , Liu Yi , Luo Penghao
Published: December 2024

Complex indoor scene localization has problems such as signal occlusion and multi-path effect, this paper analyses the topology formed by the motion trajectory of IMU and the coordinates of the UWB base station, and based on this topological constraints, it implements the judgement of line-of-sight/non-line-of-sight UWB measurements, and selects line-of-sight measurements to participate in localization computation. The heuristic extended Kalman filter algorithm (H-EKF) is used to establish the error model of IMU/UWB dual sensors, and the UWB and IMU are tightly coupled for fusion processing, and the Kalman filter information is corrected according to the results of the selection of range values to make full use of the useful information of multiple moments, improve the fusion accuracy, and achieve the alleviation of the non-visual range error.
Innovative Patterning of Silver Nanowires on Sandpaper for High-Sensitivity Industrial Wearable Pressure Sensors
Authors: Wang Li , Geng Yang , Zhou Huangyu , Ning Fanghao , Qin Tao
Published: December 2024

The rapid advancement of Industrial Internet technologies has highlighted the critical role of wearable electronic devices in enhancing intelligent production and human-machine interaction. However, challenges related to comfort, safety, and sensor accuracy persist. This study presents a novel and straightforward method for patterning silver nanowires (AgNWs) on sandpaper substrates, aimed at overcoming these challenges. The patterned AgNWs serve as electrodes in pressure sensors, utilizing a carbon nanotube-coated sponge as the sensing layer. This approach demonstrates significant improvements in sensor sensitivity, mechanical flexibility, and environmental sustainability. The resulting pressure sensor exhibits exceptional characteristics, including high sensitivity, a wide detection range, and low operating voltage, making it highly suitable for applications in industrial wearable electronics.
A Novel Three-Way MAGDM Model Under Q-Rung Orthopair Hesitant Fuzzy Environment
Authors: Chen Yuanyuan , Ma Xiuqin , Qin Hongwu , Wang Yibo
Published: December 2024

Q-rung orthopair hesitant fuzzy set (q-ROHFS) is a powerful instrument for addressing uncertainty problems. Nevertheless, the classification methods of three-way multi-attribute group decision-making (TWD-MAGDM) under this new model have been seldom researched, and the current TWD-MAGDM method in a hesitant fuzzy environment fails to consider the psychological behavior and fuzzy correlation of decision-maker, resulting in not enough distinction among classified objects. To resolve this issue, we present a novel TWD-MAGDM classification model for a q-rung orthopair hesitant fuzzy (q-ROHF) environment. Firstly, this paper considers the fuzzy correlation by allocating weight through Shapely and combines the prospect theory and Gaussian function to develop a preference function that can accurately describe the loss and gain. Based on this function, it presents a relative utility function that can more accurately measure the utility. Secondly, we provide a conditional probability that considers psychological factors and has enhanced recognition capabilities. Finally, a novel TWD-MAGDM classification model for q-ROHF is provided based on the new relative utility function and conditional probabilities. We subsequently verify the efficacy of the proposed approach.
Conformal Circular Mapping for Unbounded Multiple Connected Regions
Authors: Luo Dan , Lu Yibin
Published: December 2024

Multiple connected regions bounded by circles are crucial from the point of view of analyzing physical problems and reducing the amount of computation. However, finding a conformal mapping function that maps a multiple connected region to circular domain is challenging. Koebe’s iterative method provides a theoretically feasible path for the conformal mapping of a multiple connected region to a circular region. In this study, a numerical implementation of Koebe’s iterative method is accomplished using the charge simulation method, and an algorithm for conformal circular mapping of unbounded multiple connected regions is proposed. Through numerical experiments, this paper successfully verifies the effectiveness of the proposed algorithm.
The Construction of Probabilistic Boolean Networks: New Algorithms and Lower Bound
Authors: Fok Christopher H. , Ching Wai-Ki , Wong Chi-Wing
Published: December 2024

Boolean Networks (BN) and Probabilistic Boolean Networks (PBNs) are useful models for genetic regulatory networks, healthcare service systems, manufacturing systems and financial risk. This paper focuses on the construction problem of PBNs. We propose the Division Pre-processing algorithm (DPre), which breaks a non-negative integer matrix P with constant positive column sum into two non-negative integer matrices Q˜ and R˜, each with constant column sum, such that P = dQ˜ + R˜ for some positive integer d. We combine DPre with two existing PBN construction algorithms to form a novel PBN construction algorithm called the Single Division Pre-processed SER2-GER algorithm (SDS2G). Our computational experiments reveal that SDS2G gives significantly better performance compared with other existing PBN construction algorithms, and that SDS2G is fast. Lastly, we derive a new lower bound related to PBN construction, and this new theorem generalizes a lower bound theorem in a previous paper.
Classification Using U-Net CN on Multi-Resolution CT Scan Image
Authors: Surono Sugiyarto , Rivaldi Muhammad , Irsalinda Nursyiva
Published: December 2024

Image processing has become a central topic in the era of big data, particularly within computer vision, due to the growing volume and diverse resolutions of images. Low-resolution images introduce uncertainty, underscoring the need for high-performance classification methods. Convolutional Neural Networks (CNN), especially the U-Net architecture, are widely applied for pixel-level segmentation due to their encoder-decoder structure. This study applied U-Net on a CT scan image dataset to segment lung images, followed by a CNN classifier to classify lung cancer stages (I, II, IIIa, IIIb). The U-Net model outperformed standard CNNs, achieving 99% in accuracy, precision, sensitivity, and F1 score, compared to the conventional CNN’s 97%, 95%, 97%, and 96%, respectively.
A Meta-Path Guided Pre-Training Method for Sequential Recommendation
Authors: Zhang Wenbing , Chen Hongmei , Zhou Lihua , Xiao Qing
Published: December 2024

Sequential recommendation aims to predict users’ next preferred items according to their interaction sequences. Existing methods mainly utilize user-item interaction information, which may suffer from the issue of semantic information loss. In the paper, a Meta-Path guided Pre-training method for sequential Recommendation (MPPRec) is proposed to capture rich and meaningful semantic information between users and items. Specifically, MPPRec firstly learns the node embeddings guided by meta-paths in the pre-training phase. Then, the node embeddings are optimized according to task in the fine-tuning phase. Extensive experiments conducted on four real datasets demonstrate MPPRec outperforms the baseline methods.
Product Sales Forecasting Model Driven by Multi-Source Data Integration Based on XGBoost
Authors: Liang Xue-xia , Lu Bin , Deng Chao , Gu Yue , Chen Kai-di , Mo Yu-hua , Xu Liang-ben , Li Pai-yu , Liu Xi-peng , Liu Meng
Published: December 2024

In the rapidly evolving landscape of e-commerce, online shopping has gradually gained widespread acceptance. Yet, physical retail channels continue to exert a significant influence on product sales. Within this framework, sales forecasting occupies a pivotal position in traditional commerce and is indispensable for guiding corporate strategy formulation. However, most existing forecasting models fail to fully harness the potential impact of multi-source external information on consumer purchasing behavior. To address these challenges, this study proposes a novel sales forecasting model that synergizes the Extreme Gradient Boosting (XGBoost) algorithm with multi-source data integration techniques. Not only have we comprehensively collected an extensive range of external data, but we have also integrated the embedding and aggregation techniques of Point of Interest (POI) data to enrich the set of external information features available to the model. Leveraging feature engineering techniques, these heterogeneous data are transformed into formats amenable to model training. Relying on the nonlinear modeling capabilities of XGBoost and its efficacy in handling large-scale datasets, we trained and optimized the model. Empirical results indicate that our proposed method, predicated on multi-source data integration, significantly outperforms traditional models based on a single data source, thereby enhancing prediction accuracy and providing more precise inventory management strategy support for businesses.
Evaluating the Effectiveness of the Generalized Sigmoid in YOLOv8 for Drug Detection and Classification
Authors: Panphuech Anan , Lowmunkhong Songkiat , Onjun Ratapong , Janthawanno Patthra , Kaennakham Sayan
Published: December 2024

In this study, we investigate the potential of the Generalized Sigmoid (GS), σ(x;a,b) = (1 + e–a(x – b))–1 as an adaptive activation function within the YOLOv8 framework for drug detection and classification tasks. Medication errors, particularly in identifying pills and tablets, present serious challenges in healthcare due to visual similarities and environmental factors. We propose the use of the GS, which allows flexible parameter tuning, to enhance detection accuracy. Various configurations of the GS are evaluated against the widely-used SiLU and standard sigmoid functions. Our experiments reveal that optimal tuning of GS parameters, specifically with a = 1.50 and b = 1.50, improves model performance in terms of mean Average Precision (mAP) and overall classification accuracy. These findings suggest that the GS can surpass standard activation functions, offering a promising advancement in deep learning applications for healthcare.
Linguistic Text Mining
Authors: Postiglione Alberto
Published: December 2024

This paper explores the challenges of processing the increasing volume of natural language text, which often surpasses traditional methods’ real-time processing abilities. These texts are typically authored by individuals from diverse educational, cultural, and experiential backgrounds. The paper highlights the main linguistic and semantic issues that arise in the analysis of natural language text. Linguistic Text Mining is a computational approach that combines linguistic principles with computational techniques to extract high-quality information from natural language texts. Despite the frequent mentions of “Linguistic” and “Text-Mining” in scientific literature, no formal definition exists; this paper proposes one. It further explores LTMs potential in enhancing knowledge extraction by emphasizing linguistic features, such as multi-word units (MWUs). Traditional text analysis relies heavily on statistical methods, focusing on simple words, which are often polysemous, or on aggregating words without semantic context and this limits systems’ ability to interpret domain-specific semantics. By contrast, MWUs, like “credit card”, convey specific, unambiguous meanings, critical for identifying specialized domains. MWUs are typically organized within ontologies that represent distinct knowledge domains. Building on previous work, the study compares AUTOMETA, an ontology-based approach using finite automata for MWU identification, with large language model (LLM)-based and other ontology-driven Linguistic Text Mining methods. Findings suggest that integrating linguistic frameworks significantly improves information extraction, offering a deeper understanding of complex language structures.
Top-k Local Co-Location Pattern Mining Based on Weighted Voronoi Diagram
Authors: Jin Can , Wang Lizhen , Yang Peizhong , Wang Xiaoxu
Published: December 2024

Local co-location pattern (LCP) mining is an important branch of spatial co-location pattern mining, which aims to discover co-location patterns that prevalently co-occur in local regions. The LCPs can reveal the implicit association relationships among spatial features in local regions but not on a global scale. Existing LCP mining algorithms cannot effectively identify artificially divided local regions, and it is difficult to set an appropriate prevalence threshold for selecting prevalent LCPs. To address these problems, we propose a novel top-k LCPs mining algorithm based on weighted Voronoi diagram (called Top-k LCPM-WVD). This algorithm effectively identifies LCP distribution regions formed by human factors using the weighted Voronoi diagram, and proposes a top-k mining framework to efficiently mine the k most prevalent LCPs within regions. Extensive experimental evaluations are conducted on both real-world and synthetic datasets. Compared to the existing state-of-the-art algorithms, our proposed Top-k LCPM-WVD algorithm yields more interpretable LCPs with good efficiency.
ZJ19 Cigarette Crimper Joint Detector and Exclusion Device and Applications
Authors: Liu Tongshan , Chen Yuanyuan , Zhang Yali , Bi Andong , Xu Fang , Liu You
Published: December 2024

This study aimed to comprehensively analyze the types of joint cigarettes and the structure and working principle of the joint detector and exclusion device of the original equipment to identify specific reasons for the inability of the ZJ19 cigarette crimper [1] to effectively detect and exclude joint cigarettes. An implementation plan was determined through repeated experiments and numerous discussions. A built-in joint detector was designed and installed to address the inability of the original equipment to detect built-in joints [2], keeping the original joint detector unchanged [3], thus ensuring the detection of all joints. A filter was installed in the exclusion air path to address the issue of missing exclusion of splicing joint cigarettes during the production process, and improvements were made to the material of the removal block, reducing the failure rate of the excluded part. The addition of a secondary exclusion function further ensured the exclusion of all joint cigarettes, thereby improving product quality