System Module Research Articles

Transferable situation recognition system for scenario-independent context-aware surgical assistance systems: a proof of concept.

Surgical interventions and the intraoperative environment can vary greatly. A system that reliably recognizes the situation in the operating room should therefore be flexibly applicable to different surgical settings. To achieve this, transferability should be focused during system design and development. In this paper, we demonstrated the feasibility of a transferable, scenario-independent situation recognition system (SRS) by the definition and evaluation based on non-functional requirements. Based on a high-level concept for a transferable SRS, a proof of concept implementation was demonstrated using scenarios. The architecture was evaluated with a focus on non-functional requirements of compatibility, maintainability, and portability. Moreover, transferability aspects beyond the requirements, such as the effort to cover new scenarios, were discussed in a subsequent argumentative evaluation. The evaluation demonstrated the development of an SRS that can be applied to various scenarios. Furthermore, the investigation of the transferability to other settings highlighted the system's characteristics regarding configurability, interchangeability, and expandability. The components can be optimized step by step to realize a versatile and efficient situation recognition that can be easily adapted to different scenarios. The prototype provides a framework for scenario-independent situation recognition, suggesting greater applicability and transferability to different surgical settings. For the transfer into clinical routine, the system's modules need to be evolved, further transferability challenges be addressed, and comprehensive scenarios be integrated.

Adaptive Fault-Tolerant Tracking Control for Continuous-Time Interval Type-2 Fuzzy Systems

This paper investigated the tracking problem of mixed H∞ and L2−L∞ adaptive fault-tolerant control (FTC) for continuous-time interval type-2 fuzzy systems (IT2FSs). For the membership function mismatch and uncertainty between the modules of the nonlinear system, the IT2 fuzzy model is applied to linearly approximate it. The observer can sensitively estimate the system state, and the adaptive fault estimation functions can estimate adaptively the fault signals, which enables the designed adaptive FTC scheme to ensure the asymptotic stability of the closed-loop control system and achieve the desired mixed H∞ and L2−L∞ tracking performance. The designed adaptive control law can achieve the purpose of dynamic compensation for faults and disturbances, and the introduced lemmas further reduce the design conservatism by adjusting the slack parameters and matrices. Finally, a mass-spring-damping system is used to illustrate the effectiveness of the designed method.

Application of magnetic resonance imaging and artificial intelligence algorithms in cancer screening

In this society with a high incidence of cancer, cancer screening has become an important method to reduce the incidence and mortality of cancer. Traditional cancer screening methods such as CT have certain limitations and are difficult to adapt to large-scale and periodic cancer screening scenarios. Magnetic resonance imaging technology is an effective auxiliary method in CT methods, which can achieve high image resolution at lower doses and lower costs. Therefore, magnetic resonance imaging has become the most popular imaging method in clinical practice and a key research direction in the field of medical imaging. Therefore, this article intends to conduct in-depth research on the application of image feature extraction based on magnetic resonance imaging and artificial intelligence algorithms in cancer screening. This article introduces particle swarm optimization algorithm into the learning of artificial intelligence models and further improves it. And compared multiple algorithms, such as Chaos Particle Swarm Optimization, Genetic Particle Swarm Optimization, and Grey Wolf Algorithm, in order to verify the effectiveness and feasibility of the algorithm proposed in this paper. On this basis, the intelligent optimization algorithm was further improved and validated. Experimental results have shown that the new method proposed in this article has strong fault tolerance, and various functional modules of the cancer screening management system have been optimized and designed from five aspects: front-end, back-end, external, database, and infrastructure.

Polish Speech and Text Emotion Recognition in a Multimodal Emotion Analysis System

Emotion recognition by social robots is a serious challenge because sometimes people also do not cope with it. It is important to use information about emotions from all possible sources: facial expression, speech, or reactions occurring in the body. Therefore, a multimodal emotion recognition system was introduced, which includes the indicated sources of information and deep learning algorithms for emotion recognition. An important part of this system includes the speech analysis module, which was decided to be divided into two tracks: speech and text. An additional condition is the target language of communication, Polish, for which the number of datasets and methods is very limited. The work shows that emotion recognition using a single source—text or speech—can lead to low accuracy of the recognized emotion. It was therefore decided to compare English and Polish datasets and the latest deep learning methods in speech emotion recognition using Mel spectrograms. The most accurate LSTM models were evaluated on the English set and the Polish nEMO set, demonstrating high efficiency of emotion recognition in the case of Polish data. The conducted research is a key element in the development of a decision-making algorithm for several emotion recognition modules in a multimodal system.

The Efficiency Assessment of the Blockchain Networks Adaptive Algorithm as Part of a Multi-Consensus System on Communication Networks

The relevance of the approaches and solutions proposed in the work is due to the desire for distributed computing and decentralization of system modules using blockchain technology in order to increase the autonomy, security and independence of system components. The implementation of blockchain technology for decentralization is hampered by the lack of flexibility in terms of the algorithm for making a single decision in the asynchronous system ‒ consensus, which affects the amount of generated network traffic and the requirements for the hardware component. Due to the changing nature of the transmitted traffic, the load on the communication channel, the time of day of traffic transmission, the equipment, and the network protocols used, the development of a single universal consensus algorithm is not possible, since it depends on a very wide range of variable and specific parameters characteristic of different tasks. The introduction of adaptation mechanisms to current network conditions and a change in the consensus algorithm without losing information and with a satisfactory level of delays would provide sufficient flexibility for further implementation in existing telecommunication systems. The purpose of this paper is to evaluate the effectiveness of the proposed adaptive algorithm for choosing a consensus for blockchain networks.The essence of the presented algorithm is to change the consensus algorithm on a section of the blockchain network upon reaching certain network conditions, which allows regulating the amount of generated load on the communication network to reduce the loss of transaction blocks and the subsequent delay in their processing. The proposed efficiency assessment model is based on mathematical modeling methods, differential equation analysis, queueing theory and network graphs. The analysis of the results showed the efficiency of the proposed model when comparing the results of the analytical calculation and the experiment. The scientific novelty of the proposed approach is to developing an adaptive consensus selection algorithm, as opposed to developing a universal consensus algorithm, and the efficiency assessment model of the proposed algorithm on the communication network, taking into account a number of parameters characterizing the devices and the section of the communication network.The theoretical significance is in the universality of the proposed efficiency assessment model for calculating the synchronization speed of all nodes of the blockchain network with specified network parameters.The practical significance of the proposed algorithm and efficiency assessment method lies in the formation of new approaches and opportunities for integrating blockchain technology into modern communication networks, abstracting from the problem of consensus selection in changing conditions of the communication network section.

Beam emission spectroscopy diagnostic design and capabilities for two-dimensional turbulence measurements on Wendelstein 7-X

A beam emission spectroscopy (BES) diagnostic is designed for studying two-dimensional turbulent dynamics by measuring the Doppler-shifted Balmer-Alpha emission (n = 3 → 2) from neutral heating beams on Wendelstein 7-X (W7-X) stellarator. The BES viewing geometry has been determined in the conceptual design previously. However, the small Doppler shifts and small optical throughput compared to a typical BES diagnostic demand dedicated efforts on the optical assemblies and the detector module for the BES system. We present the detailed opto-mechanical design and specifications of BES, including a customized neutral beam viewing optical system, a semi-telecentric optical assembly, and a detector module for electronic amplification. The point spread function is calculated using the pyFIDASIM code with experimental parameters and W7-X magnetic configurations to estimate the BES spatial resolution and beam intensity. The as-manufactured interference filter is applied for the spectral isolated beam radiance calculation. Result shows that the BES system is capable of measuring the ion-scale turbulence for k ⊥ ρ i ≤ 0.4 at r/a = 0.75 with reasonable spatial and wavenumber resolutions. An integrated detector module is fabricated where two 8×4 avalanche photodiode detectors (APD) are embedded into the custom-designed pre-amplifier circuit to gain signals to the desired level. The detector noise measurement is performed and the signal-to-noise ratio (SNR) is evaluated. A detectable fluctuation level can be achieved as low as ñ e /n e ≈ 0.5% at frequency f ≤ 400 kHz with a bandwidth of 1 MHz.

Proof-of-Concept Development of the Distal Module of a Cystoscope Transurethral Continuum Surgical Robotic System

Proof-of-Concept Development of the Distal Module of a Cystoscope Transurethral Continuum Surgical Robotic System

Multifeatured Electronic Helmet to Enhance Road Safety and Rider’s Comfort

This paper presents a multi-featured electronic helmet designed to tackle critical road safety issues, including accidents, drunk driving, and over-speeding. The design incorporates a global system for mobile communications (GSM) and global positioning system (GPS) modules to accurately capture driver’s current location and send messages to predefined contacts. When encountering an accident, the helmet promptly notifies designated contacts and authorities, ensuring swift assistance. By integrating features for detecting over-speeding, accidents, and drunk driving, the helmet renders real-time alerts to both the driver’s family and traffic police, enhancing accountability and safety measures. Additionally, the helmet includes solar charging functionality for mobile devices receive 100% charged in 3.37 hours, thereby optimizing usability and emergency communication. A rain detection system protects mobile devices, while an internal warming mechanism caters to adverse weather conditions, and proffers enhanced comfort by maintaining internal form temperature between 26-27 ℃ and safety, especially in cold regions or for military personnel.

Construction of a prototype of the basic module of a scalable robotic system for simulation of composite surfaces for dynamic tests

The authors of the article developed a mathematical model of Stewart platform management. The angles of rotation of the servo shafts were obtained when setting various laws of motion of the mobile platform, in matrix mode. The hardware part of the prototype of the basic module of a scalable robotics system for modeling composite surfaces for dynamic tests was developed. The results of calculations of the maximum permissible load on the shafts of servos are presented. The CubeIDE settings for programming the STM32 microcontroller are given. The results of software development for the control of this prototype were obtained, namely, a library for controlling 6 servo drives under driver control was written. The problems that may arise during the above-described developments by future developers are considered, solutions to these problems are obtained. Detailed design features of this prototype are described, the control code of the servo drive is given; steps for further development of the final robotic system are considered

Integrating Gender-Affirming Care in a Medical Spanish Endocrine System Curriculum.

With a growing Hispanic population in the United States, medical education is adapting to provide the necessary language skills and cultural competence for effective health care. However, the incorporation of gender-affirming care in the context of medical education for Hispanic populations requires further emphasis. This curriculum presented a 3-week medical Spanish endocrine system module designed for first-year medical students. The module aimed to enhance students' ability to communicate effectively with Spanish-speaking patients about endocrine health while integrating principles of gender-affirming care. It included classroom sessions, standardized patient practice, and clinical practice with peer tutors. Pre- and postmodule surveys and assessments were conducted to evaluate the module's effectiveness. Out of 76 participants, 72 completed the postmodule evaluation. Survey results indicated significant increases in confidence levels across various aspects of patient interaction in Spanish, with statistically significant gains observed in all assessed areas. Knowledge test outcomes revealed enhanced proficiency in Spanish terminology related to the endocrine system, with scores increasing from an average of 22.3 premodule to 25.7 postmodule (p = .002), as measured by the paired t test. Additionally, students performed well in the diabetic consultation objective structured clinical examination station, with a high mean score of 86%, surpassing the satisfactory threshold. This curriculum highlights the success of a comprehensive educational approach in expanding medical students' language proficiency and ability to provide gender-affirming care to address health care disparities and improve patient outcomes among diverse populations.

Automated differentiation of calcifications and their clusters on the mammography image: the outcomes of the computer aided diagnosis system module

INTRODUCTION: Previously we developed the computer aided detection system (CAD) for mammography MammCheck II that increased the detection rate of small and difficult to detect breast carcinomas (BC). However this system was not specifically designed for calcification detection and discrimination. On the other hand, the calcifications had no influence on the CAD capability to detect BCs that appeared as a focal lesions.OBJECTIVE: To develop the approach for automated differentiation of benign and suspicious calcifications on the mammography images and assess its clinical value.MATERIALS AND METHODS: For the developed software testing we used a set of 390 mammography images with calcifications of all possible types (278 images with benign and 112 images with suspicious calcifications). For classification we used linear support vector machine (SVM) model, that was trained on the set of 126 images (70 — benign and 56 — suspicious). We developed two SVM models: with no vascular calcification analysis and with it. Statistics: for comparison between the normally distributed samples we used the Student’s T-test, for non-normally distributed — Wilcoxon signed-rank or Chi-square tests. For correlation testing of normally distributed samples the Paerson coefficient was calculated, for non-normally distributed samples — the Spearman or Kendall correlation coefficients. The statistical significance corresponded to Р-values <0,05.RESULTS: During the testing of the first model version with no vascular calcification analysis we discovered the similarity of small early vascular calcifications and the suspicious ones. As a result this model falsely classified 14 of 23 (60.87%) vascular calcification clusters as suspicious. Therefore the model was improved. The final discrimination results for all calcification types (both benign and suspicious) obtained with the help of improved model were the following: true positive conclusions — 375/390 (96.15%), false positive conclusions — 15/390 (3.84%). In both cases when suspicious calcifications were classified as benign the wrong results were een only on one mammography view. At the same time, on another view the suspicious calcifications were correctly classified.DISCUSSION: During the CAD development it seems important not only mark the suspicious areas but also suppress false positive markings corresponding to the obviously benign lesions. However it is important during this operation not to suppress the true positive markings. Therefore such systems are inevitably characterized by a certain shift to decreased prognostic value of suspicious markings at the expense of the highest possible prognostic value of benign markings. In our viewpoint, the developed approach meets this requirement. Moreover, its integration into the CAD allows to suppress the markings of soft tissue lesions associated with typical benign calcifications, appeared on the previous processing steps. This capability may decrease the false positive rate of the main CAD module.CONCLUSION: The developed approach to benign and suspicious calcification discrimination (version with vascular calcification analysis) on the mammography image provided the sensitivity — 98.21%, specificity — 95.32%, negative predictive value (benign marking) — 99.25%, positive predictive value (suspicious marking) — 89.43%.

Analysis of existing means of the cutting tool path visualization in the CNC systems

BACKGROUND: Currently, machines for processing metals and other materials are used in various industry sectors. Operation of these machines defined with the CNC is impossible without using the corresponding systems, which ensure performing real-time configuring of the system for solving various technological tasks by means of machine drives control. AIM: Analysis of functional capabilities of the visualization module of the AksiOMA Kontrol CNC system in comparison with other well-known same-type systems with consequent enlarging of capabilities of this module. Based on this, the study aim is formulated as follows: broadening the functional capabilities of the module of cutting tool motion path visualization in the AksiOMA Kontrol CNC system by means of development of the path analysis module. METHODS: For achieving the aim, the next task to broaden the functional capabilities of the module of cutting tool path visualization in the AksiOMA Kontrol CNC system is formulated as follows: analysis of existing means of cutting tool path visualization in the CNC systems. RESULTS: The study result is the fact that the visualization interface is critically important for operation, as it helps the operator to assess the abnormal situation quickly. Mistakes can be found at every stage of part machining setting-up. The mistakes can be made when positioning the part or the tool, at zero-point binding, at axes offset setting-up, etc. When machine equipment is set up, generally, difficulties take place if there is a different set-up for the other order. For these cases, in the CNC systems, such functional capabilities as processing visualization are necessary. This functionality is critically important, as it helps to find a mistake in time, to assess the danger level, and to fix it in time, that helps to prevent both the machine and the tool from failure and excessive mechanical impact. CONCLUSION: The study, which contains solving the tasks of analysis of cutting tool motion path in the AksiOMA Kontrol CNC system, is completed. The analysis conducted in the paper revealed that majority of CNC systems does not have the presented functional capabilities that does not help to conduct the complete analysis of the machining process.

Analysis of irradiation in OptiTouch system with optical detection

As part of the research and development project, a multi-touch multimedia system was implemented, working exclusively on the basis of optical technologies. The model of device with a diagonal of 42” was developed and made with 4K TV image technology and simultaneous detection in near infrared. The control of individual system modules was carried out on RaspberryPi microcomputers without typical operating system. The functionality of a conventional large-format display with unlimited multi-touch, QR code scanner, and a document scanner has been achieved in one housing. Luminance distribution tests were carried out in accordance with ANSI requirements and infrared radiation for detection work.

Искусственный интеллект написал сказку: имитация воздействия текстом на фоне естественного словосодержащего семиозиса (часть первая)

Artificial intelligence (AI) is developed and improved as a “"language model”" of natural intelligence (NI). A superficial understanding of the relationship between text and meaning-making may be misleading regarding the capabilities and actions of AI. In this article, the AI phenomenon is presented within the framework of a communicative rather than a linguistic paradigm. The theoretical basis of the communicative approach can be considered the concepts of semiotic impact and the cognitive state of a semiotic actor, which are the cause of the generation of signs and meaning-making in natural semiosis (including word-containing, grapheme-containing, or textual). Postulating a system of semantic-formal modules “"sign body-meaning”" in the linguistic paradigm provokes an incorrect interpretation of the AI phenomenon, as a result of which the sign sequence (text) itself, corresponding to autonomous linguistic rules, becomes a sign of thinking (intelligence). The linguistic interpretation of AI is a problem (misunderstanding of the causes and consequences of AI “speaking”), which is removed by using a communicative approach.

View Factors Approach for Bifacial Photovoltaic Array Modeling: Bifacial Gain Sensitivity Analysis

Abstract Bifacial modules are highly valued in the global photovoltaic market since they are able to receive sunlight from both sides and can generate up to 10–30% additional energy compared to monofacial ones. They are integrated into various sectors, including building and notably Agrivoltaics. In this work, a coupled optical–thermal–electrical model was developed in matlab to simulate the energy performance and bifacial gain for a ground-raised bifacial system. The model allows optimization as a function of the photovoltaic (PV) system and bifacial module characteristics. A fixed, south-facing bifacial PV arrays composed of three rows assumed installed in Agadir, Morocco, is considered. The optical model is based on an analytical determination of view factors using the cross-string rule. These enable the determination of irradiances received by both sides of modules, which are subsequently used to evaluate energy yield of the system. Model validation was carried out based on various statistical metrics by comparing our results with simulation results generated by various softwares. The comparison shows a very good agreement, notably with 3dbifacialvf (R2 = 1, root-mean-square error (RMSE) = 0.03 W/m2 and R2 = 0.96, RMSE = 12.4 W/m2) for front and rear side irradiance, respectively. The DC energy generated by the system differs by less than 1% compared to pvsyst results. Sensitivity analysis revealed that all system parameters, particularly ground albedo, positively affect the bifacial gain. The bifacial gain increased from 10.6% to 20.1% as the ground albedo increased from 0.25 to 0.5.

Optimization and Three-Dimensional Review of the Reform Path of College English Education System Driven by Information Technology in the New Era

Language learning cannot be separated from the environment, and the environment for second language acquisition is becoming more and more perfect and ideal. It makes the traditional single and limited English learning environment gradually move towards a three-dimensional and diversified learning environment. On the premise of the great development of higher education in China, this study aims to conduct research and discussion on higher English teaching. In combination with other successful or well functioning higher English teaching reforms, it studies and discusses some problems faced in the construction and implementation of vocational English teaching application system in China, and finds solutions and methods. Therefore, this study has practical significance for the reform and development of higher English education in China. This manuscript is based on the design of the college English teaching system module of Web technology to realize the sharing of information resources. In addition, with the deepening understanding of the importance of English teaching in colleges and universities, improving English level and English teaching level is the goal of colleges and universities. English teachers urgently need to understand the factors that affect students’ English level in order to teach students in accordance with their aptitude and find the best teaching methods. The experimental results show that the system realizes the management, query and sharing functions of open level information, and has high security and interactivity. The development of the system conforms to the development trend of network information technology and promotes the informatization and standardization of college English teaching management.

ARCHITECTURAL AND CIRCUIT MODEL OF NAVIGATION DEVICE FOR ULTRA-LIGHT LAUNCH VEHICLE

The paper considered the architectural and circuitry model of a navigation device for an ultra-lightweight launch vehicle designed to improve the accuracy and reliability of positioning and orientation in flight conditions. The study utilized modern approaches to the integration of global navigation satellite system (GNSS) and inertial navigation system (INS) to achieve high accuracy and stability of the system. The key components of the device including UM980 module, LSM6DSV32X inertial measurement module, STM32 F7 series microcontroller, E220-400T30S radio module, LMR50410XDBVR converter based power supply and RS422 interface were described in detail. The UM980 module, including SAW and LNA filter blocks, demonstrated the ability to efficiently process incoming RF signals. The NebulasIV main function block combined GNSS BB, GNSS RF, interfaces and power management unit (PMU) modules, supporting multiple communication interfaces such as UART, SPI and I²C, as well as RTK and PPS signals. The study analyzed the integration and accuracy aspects of the module in navigation systems. The signal processing scheme of the inertial navigation system module was also presented, including digital filters, free-fall and activity/inactivity detection functions, and interfaces for data communication. User bias functions and filter modes are considered to ensure the accuracy and stability of the navigation device. The work lays the groundwork for further improvements in navigation technology, especially in the context of increasing availability and accuracy for small scale space launches.

Analysis of the Structural Organization of the Human Finger Phalanges Using Anatomical Network Models

Despite the fact that the morphogenetic mechanisms of human finger transformation during ontogenesis are currently known, the issues of how they are organized into a complex integrated structure of the distal hand remains open. This question remains unanswered for several reasons, including the lack of consensus on conceptual definitions and approaches, as well as tools for assessing and comparing variations in several anatomical parts of the hand. The aim of the study was to investigate the structural organization of the human finger phalanges using anatomical network analysis (AnNA). Material and methods. In this study, the authors applied the IGRAPH package functions in the R data analysis programming environment for AnNA. Network modeling and layout were performed using the Fruchterman-Reingold algorithm. Analysis of the structure, as well as modularity and integration in the networks, was performed using the spin-glass algorithm. X-ray osteometric indices of the I–V fingers phalanx length were used to assess AnNA in 100 men and 100 women of the middle age without traumatic changes, deformations, and developmental deviations. Results. AnNA demonstrates a two-level organization of the distal hand in the form of a proximal module including the proximal phalanges and a distal module combining the middle and distal phalanges. When comparing the features of the network models of the distal hand, it was found that in women, the organization of the finger phalanges is characterised by higher morphological integration and modularity (modularity 0.43) than in men (modularity 0.38). orphological modularity and integration are organizing factors in the structure of the finger phalanges of the human distal hand. Conclusion. The study results demonstrate that the structural organization of the finger phalanges of the human hand is a system of individual anatomical modules of the phalanges.

Evidence and Axial Attention Guided Document-level Relation Extraction

Document-level Relation Extraction (DocRE) aims to identify semantic relations among multiple entity pairs within a document. Most of the previous DocRE methods take the entire document as input. However, for human annotators, a small subset of sentences in the document, namely the evidence, is sufficient to infer the relation of an entity pair. Additionally, a document usually contains multiple entities, and these entities are scattered throughout various location of the document. Previous models use these entities independently, ignore the global interdependency among relation triples. To handle above issues, we propose a novel framework EAAGRE (Evidence and Axial Attention Guided Relation Extraction). Firstly, we use human-annotated evidence labels to supervise the attention module of DocRE system, making the model pay attention to the evidence sentences rather than others. Secondly, we construct an entity-level relation matrix and use axial attention to capture the global interactions among entity pairs. By doing so, we further extract the relations that require multiple entity pairs for prediction. We conduct various experiments on DocRED and have some improvement compared to baseline models, verifying the effectiveness of our model.

Design and Development of Miniature Measuring Instrument for Parachute Cords Dynamic Load for Stepless Parachute Opening.

Spacecraft recovery technology is crucial in the field of aerospace, in which the parachute plays a key role in slowing down the descent speed of the spacecraft and realizing a smooth landing. In order to construct a dynamically adjustable parachute deployment strategy, it is necessary to measure the parachute dynamic load accurately in real-time. However, the existing sensor measurement scheme makes it difficult to meet the measurement requirements due to its large structure and complex wiring. In order to meet the current demand for real-time measurement of parachute cords dynamic load, a miniature measuring instrument is designed. According to the function and technical requirements of the miniature measuring instrument, the hardware modules of the acquisition system are selected and designed, and the integration debugging and performance optimization of the microcontroller module, A/D sampling module, signal acquisition circuit, and power supply module are carried out. The software of the parachute cords tension acquisition system based on the miniature measuring instrument is developed. The Load Cell is modeled by using SolidWorks 2022 and statically analyzed by using Ansys 2022 R1 Workbench finite element analysis software. Then the final structure of the Load Cell and the pasting position of the strain gauge are determined through the results analysis as well as experimental verification. The hardware module of the signal acquisition system for the miniature measuring instrument is then encapsulated. The force value of the miniature measuring instrument is calibrated and tested many times by using the microcomputer-controlled electronic universal testing machine. The experimental results show that the designed miniature measuring instrument has accurate data, strong stability, and good real-time performance, which meets the demand for real-time accurate measurement of miniature measuring instruments, and can provide reliable data for parachute cords parameter validation and stepless unfolding design.