Verification System Research Articles

Design and verification of high-precision dynamic temperature control system

In view of the fact that the current temperature environment simulation equipment is difficult to realize the temperature offset test of temperature-sensitive scientific payloads in deep space exploration, a high-precision dynamic temperature control system was designed and built, and then tested and verified. The system uses liquid nitrogen cold plate as the cold source, and realizes high-precision static 300 mm × 300 mm and dynamic temperature control on the contact surface of the payload through electric heating temperature control, heat pipe heat transfer and firmware heat conduction. The test results show that in the case of scientific payload-10 ∘C ∼ 45 ∘CWithin the working temperature range, the contact surface between the temperature control system and the scientificpayload can achieve high-precision temperature stability control, and the temperature fluctuation is better than ± 0.001 ∘C; at the same time, it can also realize ± 0.05 ∘C/1000 s ∼ 1 ∘C/1000 slinear control of the heating and cooling rate of the scientific payload contact surface. Compared with the temperature curve set by the temperature offset test, the maximum errors of the whole temperaturetracking are 0.003 ∘C and respectively 0.04 ∘C . The established temperature control system has the ability of high-precision temperature dynamic offset test, and has considerable application prospects in tasks such as deep space exploration payload development test.

Scaling up statistical model checking of cyber-physical systems via algorithm ensemble and parallel simulations over HPC infrastructures

Model-based formal verification of industry-relevant Cyber-Physical Systems (CPSs) is often a computationally prohibitive task. In most cases, the complexity of the models precludes any prospect of symbolic analysis, leaving numerical simulation as the only viable option. Unfortunately, exhaustive simulation of a CPS model over the entire set of plausible operational scenarios is rarely possible in practice, and alternative strategies such as Statistical Model Checking (SMC) must be used instead.In this article, we show that the number of model simulations (samples) required by SMC techniques to converge can be significantly reduced by considering multiple (an ensemble of) Adaptive Stopping Algorithms (SAs) at once, and that the simulations themselves (by far the most expensive step of the entire workload) can be efficiently sped up by exploiting massively parallel platforms.With three industry-scale CPS models, we experimentally show that the use of an ensemble of two state-of-the-art SAs (AA and EBGStop) may require dozens of millions fewer samples when compared to running a single algorithm, with reductions in sample size of up to 78%. Furthermore, we show that our implementation, by massively parallelizing system model simulations on a HPC infrastructure, yields speed-ups for the completion time of the verification tasks which are practically linear with respect to the number of computational nodes, thus achieving an efficiency of virtually 100%, even on very large platforms. This makes it possible to complete tasks of model-based SMC verification for complex CPSs in a matter of hours or days, whereas a naïve sequential execution would require from months to many years.

Verification of direct coupling code system using FRENDY version 2 and GENESIS for light water reactor lattices

ABSTRACT This study newly established a direct coupling code system consisting of the nuclear data processing code FRENDY version 2, and the three-dimensional heterogeneous transport code GENESIS (FRENDY-V2/GENESIS) for easy implementation of the random-sampling-based uncertainty quantification considering the implicit effect due to nuclear cross-section (XS) perturbations. The multi-group macroscopic XSs prepared for GENESIS were generated by FRENDY version 2, where the Dancoff factor was calculated by the neutron current method. Then the background XSs were evaluated based on the Carlvik two-term rational approximation. The infinite multiplication factor (k-infinity) and the fission reaction rate distribution in UO2 and MOX lattice geometries were compared with MVP3 to verify the calculation accuracy of FRENDY-V2/GENESIS. The sensitivity analyses on the discretization conditions such as the ray tracing of the method of characteristics were also carried out. Through several comparisons between FRENDY-V2/GENESIS and MVP3, FRENDY-V2/GENESIS with the SHEM 361-group structure calculates the k-infinity within approximately 50 pcm and the fission reaction rate distribution within approximately 0.1% by the root mean square, respectively. Consequently, the applicability of FRENDY-V2/GENESIS was verified, and FRENDY-V2/GENESIS can be used to discuss the implicit effect due to multi-group XS perturbations.

First order Büchi automata and their application to verification of LTL specifications

Büchi automata have applications in formal verification, e.g., in deciding whether a system satisfies given properties. We provide a definition of Büchi automata based on first order logics for representing infinite state systems, and investigate rules for proving emptiness and non-emptiness of such automata. We then apply these rules to solve the problem of verifying correctness of concurrent transition systems, leading to a relatively complete approach for proving and disproving LTL (Linear Temporal Logic) specifications. This approach overcomes weaknesses of existing work based on well-founded sets in the sense that the relative completeness does not depend on additional specification for ensuring progress of non-stuttering transitions. On the practical aspect, we provide a set of examples with an experimental verification condition generation tool to demonstrate the potential applicability of the approach for the verification of concurrent systems.

Design and verification of a novel energy-efficient pump-valve primary-auxiliary electro-hydraulic steering system for multi-axle heavy vehicles

Multi-axle heavy vehicles employ a variable-length tie rod steering system to achieve precise multi-mode steering. However, the single-axle steering system need integrate two sets of electro-hydraulic control systems (EHCSs), resulting in the energy consumption significant increase. This paper proposes a novel energy-efficient pump-valve primary-auxiliary electro-hydraulic steering system (PVPA EHSS) which compose of a pump-controlled dual-steering cylinders primary system and a valve-controlled variable-length tie rod cylinder auxiliary system. The proposed system utilizes a single pump to drive both the primary and auxiliary EHCSs simultaneously, enabling high-precision and high-efficiency steering with multi steering modes. Additionally, to suppress the flow disturbance of the auxiliary system branch flow on the single-pump-controlled steering primary system, the interaction between the flow of the auxiliary system and the flow of the primary system in each steering phase is studied. A pump flow feedforward-angle feedback composite control strategy incorporating branch flow prediction is proposed to mitigate the disturbance and ensure the accurate steering of left and right tires. The experimental results demonstrate that compared to the traditional variable-length tie rod steering system, the proposed system reduces energy consumption by 58.66 %, and achieves precise adaptation of the left and right tire angles in multi steering modes.

Atmospheric Precursors of Skillful SST Prediction in the Northeast Pacific

Abstract Forecasts of sea surface temperature anomalies (SSTAs) provide essential information to stakeholders of marine resources in coastal ecosystems, such as the California Current Large Marine Ecosystem (CCLME), at management-relevant monthly-to-annual time scales. Diagnosing dynamical sources of predictability and the mechanisms differentiating skill among forecasts is required for verification and improvement in operational forecasting systems. Using retrospective forecasts (1982–2020) from a four-member subset of the North American Multi-Model Ensemble (NMME), we evaluate the conditional skill of SSTA forecasts in the CCLME at monthly resolution for lead times up to 10.5 months. Forecasts from ensemble members with relatively small SSTA errors at shorter lead times retain higher skill at longer lead times, with the most substantial and long-lasting increases for forecasts initialized in the fall and early spring. The “best” low-error SSTA forecasts are characterized by increased skill in the prediction of North Pacific atmospheric circulation [sea level pressure (SLP) and 200-hPa geopotential height] the month prior to the evaluation of SSTA errors in the CCLME and exhibit more realistic progressions of anomalous SLP. The Pacific meridional mode (PMM) emerges as a diagnostic of skillful North Pacific atmosphere–ocean coupling, as forecasts that correctly simulate the PMM and its associated SLP variability increase the SSTA prediction skill in the CCLME in the fall through spring. Predictable coupled ocean–atmosphere modes provide a target for enhancing predictability with early detection of the onset of a deterministic progression emerging from stochastic atmospheric variability. Significance Statement Global forecast systems provide near-term climate predictions that inform the management of marine resources, such as those of the California Current Large Marine Ecosystem. In this study, we probe the processes which lead forecasts to succeed or fail at predicting sea surface temperatures in the California Current at seasonal time scales among retrospective forecasts from the North American Multimodel Ensemble. We demonstrate that forecasts which best simulate sea surface temperatures at the earliest lead times sustain advantages in forecast skill and find that correctly simulating extratropical atmospheric circulation increases the predictive skill of sea surface temperatures in the northeast Pacific in the following lead times. Our results offer North Pacific atmospheric circulation as a target for forecast model improvement that would additionally enhance ocean forecasts.

Ensemble Adversarial Defenses and Attacks in Speaker Verification Systems

Ensemble Adversarial Defenses and Attacks in Speaker Verification Systems

Fatigue life assessment and verification of turbine joints: current status and prospects

The research status of fatigue life assessment technology for turbine joint structures is introduced. The progress, shortcomings and development trends of existing research are discussed from the aspects of multi-field load analysis, crack initiation life assessment, crack propagation simulation and test technology. The evaluation methods of service life and damage tolerance of turbine joint structures are discussed in detail. The results show that the existing analysis and test methods can basically realize the fatigue life assessment of turbine joints, but due to various limitations, the engineering applicability needs to be improved urgently. Robust load reduction analysis methods, life assessment methods based on physical mechanisms and data-driven, load history-related crack propagation life assessment methods and test technologies under complex thermal environments are still needed to establish a fatigue life assessment and verification system for advanced aero-engine turbine joint structures.

Fuzzy PID Composite Control of Hydrostatic Center Frame

To control the oil film stiffness of a hydrostatic center frame precisely, an electrohydraulic servo oil film thickness control system was designed. It employs multiple groups of controllable oil cavities to regulate and control the oil film thickness. A mathematical model of the control system was established, and system model identification and verification were performed. A two-stage self-correcting fuzzy proportional-integral-derivative (PID) control strategy was devised and used in the model obtained by identification. An online fuzzy inference algorithm was designed for real-time online adjustment of the fuzzy control rules. Finally, a MATLAB simulation model was established. Compared with conventional fuzzy PID control, two-stage self-correcting fuzzy PID composite control has faster dynamic response characteristics, smaller overshooting, and higher steady-state accuracy. It significantly improves the synchronous control of the film thickness in the oil film control process.

MelCochleaGram-DeepCNN: Sequentially Fused Spectrogram and the DeepCNN Classifiers-based Audio Spoof Detection System

Automatic Speaker Verification (ASV) systems are crucial in various fields, enabling speaker identification for authentication, fraud detection, and forensic applications. While the simplicity and effectiveness of speech biometrics are driving the demand for ASV systems, their increasing popularity raises concerns about vulnerability to speech attacks. To enhance the security of these systems, the work in this paper proposes a spectrogram-based solution that leverages the robustness of spectrograms in audio analysis and feature extraction. The proposed model consists of two main components: frontend and backend. In the frontend, it introduces a novel spectrogram MelCochleaGram (MCG) by fusing Mel Spectrogram and Cochleagram, sequentially. For the backend implementation, pre-trained deep learning models, including ResNet50, ResNet50V2, and InceptionV3, are employed using the Keras framework. These models are individually paired with MCG to detect deepfake and replay attacks. To validate the effectiveness of the proposed system, thorough experimentation is conducted on two datasets: the DEepfake CROss-lingual (DECRO) evaluation dataset and the Voice Spoofing Detection Corpus (VSDC). The proposed combination of MCG with ResNet50 has achieved an Equal Error Rate (EER) of 0.2%, and 1.2% for deepfake detection over DECRO English and Chinese datasets, respectively. Also, for replay attack detection, the proposed combination has produced an EER of 1.4%.

Realization of an optimized cylindrical uniform magnetic field coil via flexible printed circuit technology

Abstract The design and fabrication method of magnetic field coils with high uniformity is essential for atomic magnetometers. In this paper, a novel design strategy for cylindrical uniform coils is first proposed, which combines the target-field method (TFM) with an optimized slime mold algorithm (SMA) to determine optimal structure parameters. Then, the realization method for the designed cylindrical coil by using the flexible printed circuit (FPC) technology is presented. Compared with traditional fabrication methods, this method has advantages in excellent flexibility and bending property, making the coils easier to be arranged in limited space. Moreover, the manufacturing process of the FPC technology via a specific cylindrical uniform magnetic field coil is discussed in detail, and the successfully realized coil is well tested in a verification system. By comparing the uniformity performance of the experimental coil with the simulation one, the effectiveness of the FPC technology in producing cylindrical coils has been well validated.

Design and experimental verification of propulsion system for a Mars quadcopter

Due to the Mars rotorcraft can conduct extensive surface exploration of Mars and carry sampler for collecting samples on the Martian surface, it is gradually becoming the mainstream exploration devices for Mars missions. In response to the thin atmosphere on Mars, with the flight duration and sample-carrying capacity of the quadcopter as constraints, we design the propulsion system parameters for the Mars quadcopter with the function of sampling on the Martian surface. A method for evaluating rotor performance indicators, including mass and Mach number at the tip of the blade, is proposed. Based on the evaluation index and the steady RANS method for predicting the lift and drag characteristics of the rotor, an appropriate rotor diameter for the Mars quadrotor is selected. The method combining NSGA-II and two-dimensional steady RANS is employed to optimize the airfoil of the Mars quadcopter blade under the condition of a chord length of 40 mm, a Mach number of 0.43, an angle of attack of 20°, and a Reynolds number based on chord of 6080. Experimental verification for the lift-to-drag characteristics of the single rotor is conducted in an environment simulating the atmospheric density on the Martian surface. The results show that the blade after optimization can generate a thrust of 5.95 N and consume power of 164.9 W, at the rotational speed of 3650 r/min. Based on the test bench with the function of sliding up and down for testing aerodynamic performance of quadcopter, the temperature of the motor and battery discharge characteristics of the Mars quadcopter are conducted. The results of the test show that the quadrotor can provide a thrust-to-weight ratio of 1.66 for the Mars quadcopter while meeting the design requirement of 3 min.

Biometric CNN Model for Verification Based on Blockchain and Hyperparameter Optimization

Nowadays, fingerprints as biometrics are among the most popular means of identity verification for various applications. However, they are susceptible to theft, tampering, or alteration by attackers after storage. Hence, it is critical to guarantee the privacy of these fingerprint templates because standard privacy techniques are not secure enough. Additionally, fingerprint templates are verified using a deep learning model to distinguish between authentic and fake fingerprints, making them more protected and secure by storing them inside a blockchain, which has become the most common secure technique in recent years. This paper implements the proposed efficient and secure biometric system for verification based on blockchain technology and hyperparameter optimization. First, for the storing phase, each user’s authentic fingerprint template, private, and public keys are saved in the block and linked to the previous block in the chain by a hash function. If a hacker attempts to assault a fingerprint, all prior blocks must be changed. Second, for the authentication phase, the user logs in with his fingerprint and looks up the required template in the chain. If the required fingerprint exists, it creates a new block with the login details, and the number 1 is returned, which means that the authentication is valid; if it does not exist, it is verified to see if it is authentic or fake using the proposed biometric convolutional neural network (CNN). The proposed CNN uses the Grid Search (GS) algorithm to tune hyperparameters to distinguish between authentic and fake fingerprints. The SOCOFing dataset is used for evaluating our experiment. According to the experimental results, the proposed CNN model achieved the highest accuracy of 99.52%. As a result of the blockchain, our system can return authentication information after looking up the chain in 300 ms.

Identification of Customer Through Voice Biometric System in Call Centres

In recent times, there has been a growing emphasis on adjusting communication strategies to foster strong customer relationships. This shift is driven by intensified competition, market maturation, and swift advancements in business technology. Consequently, companies have established call centers to efficiently handle customer support and fulfil customer inquiries. A pivotal aspect of enhancing service quality within these call centers involves accurately identifying customers during their interactions. The primary objective of this study is to introduce a methodology for identifying customers within call centers by analyzing their voice characteristics. Voice authentication (VA) has gained prominence in critical security operations, including banking transactions and conversations within call centers. The susceptibility of automatic speaker verification systems (ASVs) to deceptive spoofing attacks has prompted the development of countermeasures (CMs). These countermeasures are designed to differentiate between authentic and fabricated speech. ASVs and CMs collectively constitute contemporary VA systems, positioned as robust access control mechanisms. To achieve this goal, various customer identification systems within call centers have been examined, along with an analysis of audio signal attributes. Ultimately, the manuscript presents a novel approach to customer identification through voice biometrics. Notably, this method excels in recognizing customers even when provided with limited voice data. Empirical findings demonstrate that the suggested speaker identity confirmation method outperforms alternative techniques utilizing different algorithms, exhibiting a higher recognition rate. The present research work is based on two important perspectives of the call centres: a. call center agents experience and b. customer experience. The data collected separately from customers and agents for understanding the effective usage of voice biometric system in call centres. The data represented and satisfies the effectiveness of voice biometric system from both the perspectives. From the data it is also cleared that, the implementation of voice biometric system in call centres still have long way to go but will be a major technological change for the industries worldwide.

Quantum Probabilistic Model Checking for Time-Bounded Properties

Probabilistic model checking (PMC) is a verification technique for analyzing the properties of probabilistic systems. However, existing techniques face challenges in verifying large systems with high accuracy. PMC struggles with state explosion, where the number of states grows exponentially with the size of the system, making large system verification infeasible. While statistical model checking (SMC) avoids PMC’s state explosion problem by using a simulation approach, it suffers from runtime explosion, requiring numerous samples for high accuracy. To address these limitations in verifying large systems with high accuracy, we present quantum probabilistic model checking (QPMC), the first method leveraging quantum computing for PMC with respect to time-bounded properties. QPMC addresses state explosion by encoding PMC problems into quantum circuits that superpose states within qubits. Additionally, QPMC resolves runtime explosion through Quantum Amplitude Estimation, efficiently estimating the probabilities of specified properties. We prove that QPMC correctly solves PMC problems and achieves a quadratic speedup in time complexity compared to SMC.

StarMalloc: Verifying a Modern, Hardened Memory Allocator

We present StarMalloc, a verified, efficient, security-oriented, and concurrent memory allocator. Using the Steel separation logic framework, we show how to specify and verify a multitude of low-level patterns and delicate security mechanisms, by relying on a combination of dependent types, SMT, and modular abstractions to enable efficient verification. We produce a verified artifact, in C, that implements the entire API surface of an allocator, and as such works as a drop-in replacement for real-world projects, notably the Firefox browser. As part of StarMalloc, we develop several generic datastructures and proof libraries directly reusable in future systems verification projects. We also extend the Steel toolchain to express several low-level idioms that were previously missing. Finally, we show that StarMalloc exhibits competitive performance by evaluating it against 10 state-of-the-art memory allocators, and against a variety of real-world projects, such as Redis, the Lean compiler, and the Z3 SMT solver.

Redundancy Design of FADS System for Complex Leading- Edge Aircraft Based on Neural Network

The flush airdata sensing system (FADS) calculates flight parameters such as angle of attack, sideslip angle, Mach number, incoming flow pressure and static pressure based on the pressure measurement of the aircraft surface. It can effectively solve the problem that the leading edge of the pitot tube protruding from the fuselage cannot adapt to the severe aerodynamic heating faced by hypersonic aircraft during the cruise phase, and at the same time meet the aircraft's demand for stealth performance. At present, there is little analysis and research on the use of neural network methods and FADS systems for complex leading edge aircraft. In view of the subsonic/transonic conditions of hypersonic aircraft returning autonomously during the landing phase, the redundancy design and verification of the head FADS system of complex leading edge aircraft are carried out considering the influence of thin leading edge and inlet components. 15 pressure measuring holes are opened in the head of the complex leading edge aircraft. Through a large number of refined numerical simulations, the pressure database of the aircraft under different incoming flow conditions is established, and the typical working conditions are verified by wind tunnel tests. For the complex leading edge aircraft, 4 sets of neural network algorithms are established based on pressure data and redundant design research is carried out, including 1 set of 9-hole algorithm and 3 sets of redundant algorithms. Among them, the 9-hole algorithm has a higher accuracy, with the solution error of the angle of attack within 0.07∘, the solution error of the sideslip angle within 0.3∘, the solution error of the Mach number within 0.0012, and the relative error of the solution of the incoming flow pressure and static pressure within 1.5%. In addition, a system solution process with a certain fault tolerance was established, which can continue to maintain the effective output of the incoming flow parameters in the event of failure of any single pressure measuring hole.

Design and experimental verification of an S-shaped continuous weft insertion system for soft–hard blended preform narrow channels

To address the limitations of the existing weft insertion technology in inserting carbon fiber bundles into the narrow channels of soft–hard blended preform, a proposed solution is to use a continuous weft insertion trajectory based on an S-shaped path for narrow channels. A weft insertion system that meets the process requirements has been designed. The analysis of the functional requirements for the continuous weft insertion system has identified five key nodes for the system, and the motion paths of each mechanism have been established. Through design methods such as analytical methods, rigid inversion methods, and mechanical analysis, the modular design of the system and the planning of the timing sequence for multiple mechanisms have been completed. Weft insertion experiments have been conducted on a continuous weft insertion system experimental platform, and the results demonstrate that the weft insertion system can effectively introduce carbon fiber bundles into the narrow channels, forming the expected S-shaped continuous weft insertion trajectory. This study verifies the feasibility of the designed weft insertion system and the accuracy of the continuous weft insertion theory, providing a viable solution for continuous weft insertion in the narrow channels of soft–hard blended preforms.

432 - A review of accuracy of optical surface imaging systems for setup verification during breast radiotherapy treatment

432 - A review of accuracy of optical surface imaging systems for setup verification during breast radiotherapy treatment

Formalization of topology and electrical circuit verification for computer-aided design systems

Formalization of topology and electrical circuit verification for computer-aided design systems