Verification Methodology Research Articles

Quantitative simulation and validation of energy carbon emission efficiency changes in Chinese urban agglomerations

In the context of the global energy dilemma, enhancing energy efficiency has inevitably become a pivotal strategy for mitigating energy waste and promoting sustainable development. Urban agglomerations, as growth poles leading high-quality regional economic development, play a significant role in this process. Within these urban agglomerations, the aggregation of various factors and the substitution of energy resources substantially influence the energy carbon emission efficiency (ECEE) of surrounding cities during their development and maturation phases. This study initially employs a three-stage Data Envelopment Analysis (DEA) to quantitatively analyze the ECEE values of 19 urban agglomerations from 2006 to 2020. It then establishes a methodology for calculating the joint intensity (JI) and joint threshold (JT) of ECEE within these urban agglomerations. Finally, a validation process is executed using MATLAB simulation and verification methodology to fit and authenticate the evolutionary patterns of ECEE in Chinese urban agglomerations. The primary objective of this research is to model the evolution of ECEE, thereby exploring the sustainable development pathways for urban agglomerations in China. The research findings indicate that: (1) The results from the three-stage DEA demonstrate that, after removing the influences of external environmental factors and random errors, the comprehensive technical efficiency (TE) of energy carbon emissions for the 19 urban agglomerations in China experienced a wave-like increase, rising from 0.410 to 0.506 between 2006 and 2020. (2) The calculation results of the constructed JI model indicate that the JT values of ECEE for national-level, regional-level, and local-level urban agglomerations are 1006.92, 226.60, and 160.14, respectively. The national-level urban agglomerations have significantly higher JT values and JI than the other two levels of urban agglomerations. (3) The results of the Matlab simulation verification show that 16 urban agglomerations fit well with the wave-like ascending evolutionary pattern. However, four urban agglomerations exhibit an opposite fitting effect due to the influence of their pillar industries or the small number of cities within these accumulations, making them unrepresentative. Consequently, the evolutionary curve of ECEE in Chinese urban agglomerations generally exhibits a wave-like upward trend over time.

Higher-Order Model Checking of Effect-Handling Programs with Answer-Type Modification

Model checking is one of the successful program verification methodologies. Since the seminal work by Ong, the model checking of higher-order programs―called higher-order model checking, or HOMC for short―has gained attention. It is also crucial for making HOMC applicable to real-world software to address programs involving computational effects. Recently, Dal Lago and Ghyselen considered an extension of HOMC to algebraic effect handlers, which enable programming the semantics of effects. They showed a negative result for HOMC with algebraic effect handlers―it is undecidable. In this work, we explore a restriction on programs with algebraic effect handlers which ensures the decidability of HOMC while allowing implementations of various effects. We identify the crux of the undecidability as the use of an unbounded number of algebraic effect handlers being active at the same time. To prevent it, we introduce answer-type modification (ATM), which can bound the number of algebraic effect handlers that can be active at the same time. We prove that ATM can ensure the decidability of HOMC and show that it accommodates a wide range of effects. To evaluate our approach, we implemented an automated verifier EffCaml based on the presented techniques and confirmed that the program examples discussed in this paper can be automatically verified.

The impact of a cashless electronic payment system on hyperinflation in Bangladesh

The increase of electronic payment methods, or payments that don't include the use of currency has transformed financial transactions. Non-cash transactions are convenient, simple, and fast, among other benefits. Furthermore, payments without cash have an effect on Bangladesh's currency management. The practicality that comes with using transactions without cash causes the velocity of money to increase. The society has seen a decline in payments in cash, yet the velocity of currency causes an intense pace when transactions without cash are used. It is thought that increased money transmission capacity will have hyperinflation implications. The purpose of this study is to ascertain how the cashless payment method affects hyperinflation. This research utilized an analytical approach and additional information from the beginning of 2021 to the end of 2023 that had been collected through Bangladesh Bank using verification methodologies. Multiple linear regression analysis is the process of research. The findings indicated that the factors related to digital currency experienced significant adverse effects, the factors related to debit cards, credit cards, online banking, or mobile banking had a major beneficial effect, the parameters related to credit cards had a meaningless unfavourable impact, and the variables related to rates of interest had an important beneficial effect.

Gendered disinformation in Spanish-language fact-checking: origin, methodology, and perspectives

The recent surge in disinformation targeting gender themes poses a substantial threat to women’s equality in democratic systems. This study investigates the efforts of three fact-checking platforms prominent in Ibero-America (Maldita.es and Newtral in Spain and Chequeado in Argentina) in countering antifeminist fake news. Employing a dual methodology, we conducted a content analysis of pieces published on gender issues over one year and semi-structured interviews with representatives from these platforms. The findings unveil a consistent production of texts addressing contemporary feminist affairs. Disinformers target both the feminist movement and its historical grievances, including gender-based violence. Fact checks emerge as the primary format for combating these hoaxes, with explainers gaining against increasingly complex disinformation narratives. The verification methodology emphasizes consulting official sources and expert testimony. Interviewees acknowledge that there is still much progress to be made in gender-related fact-checking.

Enhancing Agricultural Soil Carbon Sequestration: A Review with Some Research Needs

The US rejoined the Paris Agreement in 2021 with a targeted 50–52% reduction in net GHG emissions in 2030 relative to 2005. Within the US’s nationally determined contributions, several land-based mitigation options were submitted, targeting the removal of 0.4–1.3 GtCO2 yr−1 in 2030 compared to the net flux in 2010. Acknowledging disagreement has existed on both technological and economic feasibility levels of soil C sequestration adoption and practices, this review explores and evaluates the research findings and needs for six concepts: (1) permanence; (2) additionality; (3) leakage; (4) uncertainty; (5) transaction costs; and (6) heat-trapping ability of different gases. These concepts are crucial for the effective implementation of soil C sequestration projects since they help establish robust and integrated methodologies for measurement, verification, and issuance of carbon credits. In turn, they help ensure that environmental, social, and economic benefits are accurately assessed and credibly reported, enhancing the integrity of carbon markets and contributing to global climate mitigation efforts. This review also evaluates the existing and potential market opportunities for agricultural production with C sequestration and “climate- smart” farming practices. Current barriers to, research needs for, and policy considerations regarding soil C sequestration strategies are also stated.

Generative AI Assertions in UVM-Based System Verilog Functional Verification

This paper investigates the potential of leveraging artificial intelligence to automate and optimize the verification process, particularly in generating System Verilog assertions for an Advance Peripheral Bus verification environment using Universal Verification Methodology. Generative artificial intelligence, such as ChatGPT, demonstrated its ability to produce accurate and valuable assertions by employing text-based prompts and image-fed inputs, significantly reducing the required manual effort. This research presents a way of generating System Verilog assertions using the ChatGPT prompt, presenting an image to the Large Language Models, and requesting the assertions needed for the respective protocol. This approach shows the potential for artificial intelligence to revolutionize functional verification by automating complex tasks, ultimately ensuring faster and more reliable System-on-Chip development. The assertions generated by the Large Language Models are integrated into an existing Advance Peripheral Bus verification environment. This process involves running the assertions on a free EDA Playground platform with all three simulators (Cadence Incisive, Mentor Questa, and Synopsys Verilog Compiler Simulator). The main conclusions are that using ChatGPT-4.0 for generating System Verilog assertions significantly reduces the time and effort required for functional verification, demonstrating its potential to enhance efficiency and accuracy in verifying complex System-on-Chip designs.

AI-Powered Neural Network Verification: System Verilog Methodologies for Machine Learning in Hardware

This research focuses on verifying neural network models using System Verilog, with two primary applications: visual edge detection and neuron behavior modeling. In modern chip design, hardware verification plays a crucial role in ensuring that complex neural models perform as expected. A neuron model based on Hubel and Wiesel’s feed-forward network architecture was proposed and tested using integrator and threshold modules implemented in Verilog. The proposed verification methodology employs self-checking test benches, supported by functional coverage and simulation, for comprehensive validation. The results demonstrate efficient verification with high coverage, paving the way for future advancements in hardware neural networks.

ReSG: A Data Structure for Verification of Majority-based In-memory Computing on ReRAM Crossbars

Recent advancements in the fabrication of Resistive Random Access Memory (ReRAM) devices have led to the development of large-scale crossbar structures. In-memory computing architectures relying on ReRAM crossbars aim to mitigate the processor-memory bottleneck that exists with current complementary metal-oxide semiconductor technology. With this motivation, several synthesis and mapping approaches focusing on the realizations of Boolean functions in the ReRAM crossbars have been proposed earlier. Thus far, the verification of the designs realized on ReRAM crossbars is done either through manual inspection or using simulation-based approaches. Since manual inspections and simulation-based approaches are limited to smaller designs, they cannot be applied to the verification of complex designs on large-scale ReRAM crossbars. Motivated by this, we propose, for the first time, an automatic equivalence checking flow that determines the equivalence between the original function specification (e.g., Majority-inverter Graph ) and the crossbar micro-operations file formats. We consider two crossbar structures, zero-transistor, one-memristor (0T1R) and one-transistor, one-memristor (1T1R) to implement the micro-operations. While the micro-operations file format exists for 0T1R crossbar structures, no representations for micro-operations to be executed in 1T1R crossbars exist yet. In this work, we introduce the micro-operation file format for 1T1R crossbar structures to efficiently represent the micro-operations as ReRAM crossbar netlists. Afterwards, we introduce two intermediate data structures, ReRAM Sequence Graph for 0T1R crossbars (ReSG-0T1R) and for 1T1R crossbars (ReSG-1T1R) , that are derived from the 0T1R and 1T1R crossbar micro-operations file formats, respectively. These ReSGs are then translated into Boolean Satisfiability (SAT) formula, and then the verification is done by checking the generated SAT formulae against the golden functional specification (represented in Verilog) using Z3 Satisfiability solver. Experimental evaluations confirm the effectiveness of the proposed verification methodology on MCNC and ISCAS benchmarks.

In silico Approaches for Exploring the Pharmacological Activities of Benzimidazole Derivatives: A Comprehensive Review.

This article reviews computational research on benzimidazole derivatives. Cytotoxicity for all compounds against cancer cell lines was measured and the results revealed that many compounds exhibited high inhibitions. This research examines the varied pharmacological properties like anticancer, antibacterial, antioxidant, anti-inflammatory and anticonvulsant activities of benzimidazole derivatives. The suggested method summarises In silico research for each activity. This review examines benzimidazole derivative structure-activity relationships and pharmacological effects. In silico investigations can anticipate structural alterations and their effects on these derivative's pharmacological characteristics and efficacy through many computational methods. Molecular docking, molecular dynamics simulations and virtual screening help anticipate pharmacological effects and optimize chemical design. These trials will improve lead optimization, target selection, and ADMET property prediction in drug development. In silico benzimidazole derivative studies will be assessed for gaps and future research. Prospective studies might include empirical verification, pharmacodynamic analysis, and computational methodology improvement. This review discusses benzimidazole derivative In silico research to understand their specific pharmacological effects. This will help scientists design new drugs and guide future research. Latest, authentic and published reports on various benzimidazole derivatives and their activities are being thoroughly studied and analyzed. The overview of benzimidazole derivatives is more comprehensive, highlighting their structural diversity, synthetic strategies, mechanisms of action, and the computational tools used to study them. In silico studies help to understand the structure-activity relationship (SAR) of benzimidazole derivatives. Through meticulous alterations of substituents, ring modifications, and linker groups, this study identified the structural factors influencing the pharmacological activity of benzimidazole derivatives. These findings enable the rational design and optimization of more potent and selective compounds.

A Scalable Formal Verification Methodology for Data-Oblivious Hardware

A Scalable Formal Verification Methodology for Data-Oblivious Hardware

ESG 경영에 대한 중국 소비자 인식 조사 및 소비행동에 관한 연구

This study investigated Chinese consumers' awareness of ESG management and empirically analyzed the impact of consumer awareness of ESG management on consumption behavior. An online survey was conducted targeting general adult consumers living in first-tier cities in China. Of the 531 total respondents, 336 consumers who were aware of ESG management were used in the final analysis, and the SPSS 29 and AMOS 26 programs were used for statistical analysis. The results of the study are as follows. First, the level of awareness and perception of ESG management by Chinese consumers was found to be very high. Second, the impact of Chinese consumers' awareness of ESG management on consumption behavior was found to have a statistically significant positive effect. Third, Chinese consumers' awareness of ESG management had a significant moderating effect by gender on the relationship between consumption behavior and ESG management. Male consumers' awareness of ESG management was found to be relatively higher than that of female consumers, and both groups were found to have an impact on consumption behavior. In the case of women, eco-friendly consumption behavior was found to be higher than that of men, and men's ethical consumption behavior was found to be higher. Based on the above research results, the implications for raising Chinese consumers’ awareness of ESG management and companies are as follows. First, it is necessary to establish management strategies that take into account the level of Chinese consumers’ awareness of ESG management. Second, ESG management is closely related to consumers’ living environment and consumption behavior, but research on consumer awareness of this is insufficient, and research on ESG consumption behavior related to ESG management is needed. Third, as shown in the results of this study, Chinese consumers’ awareness of ESG management affects consumption behavior, so consumer-centered ESG management activities are needed. Fourth, it is necessary to secure transparency and reliability through disclosure of evaluation agencies and verification methodologies for ESG management.

Impact of Workload, Training, and Inspirations for Worker Performance at R-Hotel Rancamaya Bogor

The purpose of this study is to ascertain how employee performance at R-Hotel Rancamaya Bogor is impacted by workload, training, and motivation. Primary and secondary data make up the study's data 104 employees completed questionnaires that yielded primary data. On the other hand, secondary data came from pertinent company and other sources. This study used a survey approach along with a type of verification and descriptive research methodology. The questionnaire makes use of traditional assumption testing, reliability tests, and validity tests. Prior to doing multiple regression testing, the Likert scale is employed. This is done in order to ascertain how one dependent variable is affected by the four independent variables that were employed. Based on the findings of validity and reliability tests, which demonstrate that all indicators are deemed valid and reliable, the study's conclusions are drawn. Workload (X1), training (X2), and motivation (X3) all have an impact on employee performance (Y) at R-Hotel Rancamaya Bogor at the same time. Employee performance is impacted by all independent variables, however somewhat.

Digital Twins Verification and Validation Approach through the Quintuple Helix Conceptual Framework

The concept of digital twins has been in the field for a long time, constantly challenging the specification, modeling, design, implementation, and exploitation of complex cyber–physical systems. Despite the various foundations, standards, and platforms in systems engineering, there are ongoing challenges with verification and validation methodology. This study aims to establish a generic framework that addresses the various aspects of digital twinning. The multifaceted nature of the problem requires raising the abstraction level in both the real (actual) and virtual domains, effective dissemination of information resources, and a design inspired by verification and validation. The proposed framework combines the quintuple helix model with the problem and operational domains of a real (actual) twin, the solution and implementation domains of a virtual twin, and the execution domain as the bridge that links them. Verification and validation dimensions follow the meta object facility abstraction layers (instance, model, meta-model, and meta-meta-model) mapping over five helices. Embedding the complexity reduction mechanisms in the proposed framework builds a suite for extendible and verifiable digital twinning in simulation and real-time scenarios. The application of main conceptual framework mechanisms in a real-world example study aids the verification of this research’s intentions. The validation is a matter of further research endeavors.

Reduced floating-point precision in regional climate simulations: an ensemble-based statistical verification

Abstract. The use of single precision in floating-point representation has become increasingly common in operational weather prediction. Meanwhile, climate simulations are still typically run in double precision. The reasons for this are likely manifold and range from concerns about compliance and conservation laws to the unknown effect of single precision on slow processes or simply the less frequent opportunity and higher computational costs of validation. Using an ensemble-based statistical methodology, Zeman and Schär (2022) could detect differences between double- and single-precision simulations from the regional weather and climate model COSMO. However, these differences are minimal and often only detectable during the first few hours or days of the simulation. To evaluate whether these differences are relevant for regional climate simulations, we have conducted 10-year-long ensemble simulations over the European domain of the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) in single and double precision with 100 ensemble members. By applying the statistical testing at a grid-cell level for 47 output variables every 12 or 24 h, we only detected a marginally increased rejection rate for the single-precision climate simulations compared to the double-precision reference based on the differences in distribution for all tested variables. This increase in the rejection rate is much smaller than that arising from minor variations of the horizontal diffusion coefficient in the model. Therefore, we deem it negligible as it is masked by model uncertainty. To our knowledge, this study represents the most comprehensive analysis so far on the effects of reduced precision in a climate simulation for a realistic setting, namely with a fully fledged regional climate model in a configuration that has already been used for climate change impact and adaptation studies. The ensemble-based verification of model output at a grid-cell level and high temporal resolution is very sensitive and suitable for verifying climate models. Furthermore, the verification methodology is model-agnostic, meaning it can be applied to any model. Our findings encourage exploiting the reduction of computational costs (∼30 % for COSMO) obtained from reduced precision for regional climate simulations.

Seismic Strengthening of Elevated Reinforced Concrete Tanks: Analytical Framework and Validation Techniques

The prevalence of elevated reinforced concrete tanks is widespread across Italian water distribution networks, particularly in flat or low-relief areas. Primarily constructed by the late 1970s, these tanks often suffer from outdated hydraulic efficiency, unable to cope with the increasing urban water demands. With rising construction costs, the economic advantage has shifted toward underground tanks, leading to the decommissioning of many elevated tanks. Despite being obsolete, elevated tanks from the 1960s and 1970s still stand in densely urbanized regions. However, demolishing them may prove less cost-effective than retrofitting to restore their original structural capacity. The widespread presence of these structures, coupled with their susceptibility to decay from weathering and poor maintenance, necessitates a comprehensive assessment of their resilience against gravitational and lateral forces, including seismic activity. Consequently, there is a pressing need to develop an analysis and verification methodology, particularly focused on seismic resilience, tailored to existing elevated tanks. These structures, distinct from conventional reinforced concrete frames, are primarily designed to withstand vertical forces, emphasizing the importance of optimizing material usage in their retrofitting efforts.

Verification of Kastner Visibility of Hilal Observation Results at Condrodipo Rukyat Center in 1444 H

The Kastner Hilal visibility method is one of numerous contemporary observation techniques developed with the objective of monitoring the appearance of Hilal with greater precision. This paper presents a discussion of Hilal observations conducted at the Condrodipo Rukyat Center. The visibility results are analyzed using curve graphs, facilitating the assessment and validation of the observations. The findings demonstrate that employing the Kastner mathematical model can corroborate visibility with a substantial degree of concurrence, regardless of atmospheric constraints and sky conditions. However, the results of observer reports in the field are often inconsistent with model predictions, especially in conditions of low Hilal altitude and naked eye observations. Therefore, more rigorous scientific verification and reliable methodologies are needed to confirm observations for the integrity of the determination of the beginning of the lunar month.

Finite element procedure for thermomechanical and structural integrity analysis of beam intercepting devices subjected to free electron laser

High-energy particles, including photons (x-ray, γ-ray, bremsstrahlung), electrons, and protons, possess the capability to penetrate materials and deposit energy within them. The degree of absorption depends on both the energy and type of particles, as well as the properties of the materials with which they interact. This energy deposition can manifest either at the material's surface or throughout its volume, potentially resulting in various failure modes.The primary aim of this paper is to establish a structured analysis methodology for evaluating the structural integrity of beam-intercepting devices when subjected to high-energy particles. The paper also reviews some of the underlying physics, pertinent to the scope of the thermomechanical analysis, potential failure modes, and introduces verification and validation methodologies. Engineers and researchers can utilize the guidelines presented in this paper to effectively plan the development of beam intercepting devices, thereby ensuring their reliability and performance in the presence of high-energy particle exposure.

Predictable Verification using Intrinsic Definitions

We propose a novel mechanism of defining data structures using intrinsic definitions that avoids recursion and instead utilizes monadic maps satisfying local conditions. We show that intrinsic definitions are a powerful mechanism that can capture a variety of data structures naturally. We show that they also enable a predictable verification methodology that allows engineers to write ghost code to update monadic maps and perform verification using reduction to decidable logics. We evaluate our methodology using Boogie and prove a suite of data structure manipulating programs correct.

Artificial Intelligence Application in the Field of Functional Verification

The rising interest in Artificial Intelligence and the increasing time invested in functional verification processes are driving the demand for AI solutions in this field. Functional verification is the process of verifying that the Register Transfer Layer (RTL) implementation behaves according to the specifications provided. This is performed using a hardware verification language (HVL) such as SystemVerilog combined with the Universal Verification Methodology (UVM). Reading, identifying the key elements from multiple documentations, creating the verification plan, building the verification environment, implementing the tests defined, and achieving 100% coverage are usually the steps performed in order to complete the verification process. The verification process is considered finalized when functional coverage is at 100%. There are multiple ideas on how the process can be aided by AI, such as underlining the essential information from documentation, which would help in understanding faster how the Register Transfer Layer implementation works, thus vastly reducing time. In this paper, to greatly reduce the time spent on functional verification, two Convolutional Neural Network (CNN) architectures are implemented to properly classify the information across different documents; both approaches have significant and promising results. The database used for this classification task was created by the researchers using different documentations available.

MBFair: a model-based verification methodology for detecting violations of individual fairness

MBFair: a model-based verification methodology for detecting violations of individual fairness