Identifying Counterexamples Without Variability in Software Product Line Model Checking

Product detection based on state abstraction technologies in the software product line(SPL)is more complex when compared to a single system.This variability constitutes a new complexity,and the counterexample may be valid for some products but spurious for others.In this paper,we found that spurious products are primarily due to the failure states,which correspond to the spurious counterexamples.The violated products correspond to the real counterexamples.Hence,identifying counterexamples is a critical problem in detecting violated products.In our approach,we obtain the violated products through the genuine counterexamples,which have no failure state,to avoid the tedious computation of identifying spurious products dealt with by the existing algorithm.This can be executed in parallel to improve the efficiency further.Experimental results showthat our approach performswell,varying with the growth of the system scale.By analyzing counterexamples in the abstract model,we observed that spurious products occur in the failure state.The approach helps in identifying whether a counterexample is spurious or genuine.The approach also helps to check whether a failure state exists in the counterexample.The performance evaluation shows that the proposed approach helps significantly in improving the efficiency of abstraction-based SPL model checking.

Positional Error Model of Line Segments with Modeling and Measuring Errors Using Brownian Bridge

Spatial linear features are often represented as a series of line segments joined by measured endpoints in surveying and geographic information science.There are not only the measuring errors of the endpoints but also the modeling errors between the line segments and the actual geographical features.This paper presents a Brownian bridge error model for line segments combining both the modeling and measuring errors.First,the Brownian bridge is used to establish the position distribution of the actual geographic feature represented by the line segment.Second,an error propagation model with the constraints of the measuring error distribution of the endpoints is proposed.Third,a comprehensive error band of the line segment is constructed,wherein both the modeling and measuring errors are contained.The proposed error model can be used to evaluate line segments’overall accuracy and trustability influenced by modeling and measuring errors,and provides a comprehensive quality indicator for the geospatial data.

Machine Learning for Hybrid Line Stability Ranking Index in Polynomial Load Modeling under Contingency Conditions

In the conventional technique,in the evaluation of the severity index,clustering and loading suffer from more iteration leading to more com-putational delay.Hence this research article identifies,a novel progression for fast predicting the severity of the line and clustering by incorporating machine learning aspects.The polynomial load modelling or ZIP(constant impedances(Z),Constant Current(I)and Constant active power(P))is developed in the IEEE-14 and Indian 118 bus systems considered for analysis of power system security.The process of finding the severity of the line using a Hybrid Line Stability Ranking Index(HLSRI)is used for assisting the concepts of machine learning with J48 algorithm,infers the superior affected lines by adopting the IEEE standards in concern to be compensated in maintaining the power system stability.The simulation is performed in the WEKA environment and deals with the supervisor learning in order based on severity to ensure the safety of power system.The Unified Power Flow Controller(UPFC),facts devices for the purpose of compensating the losses by maintaining the voltage characteristics.The finite element analysis findings are compared with the existing procedures and numerical equations for authentications.

Transmission Line Modelling of Geomagnetic Induction in the Ocean/Earth Conductivity Structure

During geomagnetic disturbances, electric fields induced in the Earth and in power systems, pipelines and submarine cables can interfere with the operation of these systems. Calculations for submarine cables are complicated by the need to consider not just the induction directly into the cable but also the earth potentials produced at the coast at each end of the cable. To determine the coast potentials, we present a new model of the ocean and earth conductivity structure that spans the whole length of a cable from one coast to another. Calculations are based on the generalised thin sheet approach introduced by Ranganayaki and Madden but converted to a transmission line model that can be solved using standard circuit theory techniques. It is shown how the transmission line model can be used to calculate the earth potential profile from one side of an ocean or sea to the other. Example calculations are presented for a shallow sea, a shallow ocean, and a deep ocean that are simplified approximations to the North Sea, Tasman Sea and Pacific Ocean and show that the peak potentials occur at the coast. An examination is also made of how the width of a shallow sea and the width of the continental shelf affect these coast potentials. The modelling technique and example results provide a guide for more detailed modelling of geomagnetic induction along the routes of specific submarine cables.

An Optimization Approach of IoD Deployment for Optimal Coverage Based on Radio Frequency Model

Recently,Internet of Drones(IoD)has garnered significant attention due to its widespread applications.However,deploying IoD for area coverage poses numerous limitations and challenges.These include interference between neighboring drones,the need for directional antennas,and altitude restrictions for drones.These challenges necessitate the development of efficient solutions.This research paper presents a cooperative decision-making approach for an efficient IoDdeployment to address these challenges effectively.The primary objective of this study is to achieve an efficient IoDdeployment strategy thatmaximizes the coverage regionwhile minimizing interference between neighboring drones.In deployment problem,the interference increases as the number of deployed drones increases,resulting in bad quality of communication.On the other hand,deploying a few drones cannot satisfy the coverage demand.To accomplish this,an enhanced version of a concise population-based meta-heuristic algorithm,namely Improved Particle SwarmOptimization(IPSO),is applied.The objective function of IPSO is defined based on the coverage probability,which is primarily influenced by the characteristics of the antennas and drone altitude.A radio frequency(RF)model is derived to evaluate the coverage quality,considering both Line of Sight(LOS)and Non-Line of Sight(NLOS)down-link coverage probabilities for ground communication.It is assumed that each drone is equipped with a directional antenna to optimize coverage in a given region.Extensive simulations are conducted to assess the effectiveness of the proposed approach.Results demonstrate that the proposed method achieves maximum coverage with minimum transmission power.Furthermore,a comparison is made against Collaborative Visual Area Coverage Approach(CVACA),and a game-based approach in terms of coverage quality and convergence speed.The simulation results reveal that our approach outperforms both CVACA and the gamebased schemes in terms of coverage and convergence speed.Comparisons validate the superiority of our approach over existing methods.To assess the robustness of the proposed RFmodel,we have considered two distinct ranges of noise:range1 spanning from−120 to−90 dBm,and range2 spanning from−90 to−70 dBmfor different numbers of UAVs.In summary,this research presents a cooperative decision-making approach for efficient IoD deployment to address the challenges associatedwith area coverage and achieves an optimal coveragewithminimal interference.

A novel approach to the dynamic response analysis of Euler-Bernoulli beams resting on a Winkler soil model and subjected to impact loads

This work presents a novel approach to the dynamic response analysis of a Euler-Bernoulli beam resting on a Winkler soil model and subjected to an impact loading.The approach considers that damping has much less importance in controlling the maximum response to impulsive loadings because the maximum response is reached in a very short time,before the damping forces can dissipate a significant portion of the energy input into the system.The development of two sine series solutions,relating to different types of impulsive loadings,one involving a single concentrated force and the other a distributed line load,are presented.This study revealed that when a simply supported Euler-Bernoulli beam,resting on a Winkler soil model,is subject to an impact load,the resulting vertical displacements,bending moments and shear forces produced along the span of the beam are considerably affected.In particular,the quantification of this effect is best observed,relative to the corresponding static solution,via an amplification factor.The computed impact amplification factors,for the sub-grade moduli used in this study,were in magnitude greater than 2,thus confirming the multiple-degree-of-freedom nature of the problem.

Cytotoxicity and genotoxicity assessment of Euphorbia hirta in MCF-7cell line model using comet assay

Objective:To evaluate the cytotoxicity and genotoxicity activity of Euphorbia hirta(E.hirta)in MCF-7 cell line model using comet assay.Methods:The cytotoxicity of E.hirta extract was investigated by employing brine shrimp lethality assay and the genotoxicity of E.hirta was assessed by using Comet assay.Results:Both toxicity tests exhibited significant toxicity result.In the comet assay,the E.hirta extract exhibited genotoxicity effects against MCF-7 DNA in a time-dependent manner by increasing mean percentage of DNA damage.The extract of E.hirta showed significant toxicity against brine shrimp with an LC_(50)value of 620.382μg/mL(24 h).Comparison with positive control potassium dichroniate signifies that cytotoxicity exhibited by the methanol extract might have moderate activity.Conclusion:The present work confirmed the cytotoxicity and genotoxicity of E.hirta.However,the observed toxicity of E.hta extracts needs to be confirmed in additional studies.

Characterization of gastric cancer models from different cell lines orthotopically constructed using improved implantation techniques

AIM:To develop orthotopic gastric cancer mouse models from different cell lines and characterize the tumor features to assist further in preclinical trials and clinical treatment strategies.METHODS:Human gastric cancer SGC-7901 and BGC823 cell suspensions were injected subcutaneously into nude mice to develop solid tumors,and tumor tissue pieces were then implanted under the serous coat of the stomach.An autopsy was performed on all animals of the SGC-7901 and BGC-823 models to observe the primary tumor growth and metastases using pathological and immunohistochemical methods.RESULTS:Both models showed large tumors in situ resulting in pressure and infiltration of the adjacent organs.The gastric cavity became smaller,along with stenosis of the cardia or pylorus.There were biological and statistical differences between the two models.The metastasis rate in involved organs (lymph nodes,kidney,spleen,testis) was significantly higher in the BGC-823 model compared to the SGC-7901 model (P < 0.05 or P < 0.01).The median survival of the BGC-823 model was shorter than that of SGC-7901 (23 d vs 84 d,P < 0.05).Histopathologically,the primary tumor and metastatic lesions of the two models showed obvious atypia and mucus in the cytoplasm.Compared with the SGC-7901 model,BGC-823 appeared more poorly differentiated (absence of adenoid structure),had a smaller volume,and richer capillary structure.Immunohistochemical staining revealed cytokeratin 20 and epithelial membrane antigen expression was positive in the SGC-7901 tumors,while negative in BGC-823 ones.CONCLUSION:Models using the SGC-7901 and BGC-823 cell lines were established which could function in gastric cancer research on carcinogenesis mechanism and drug discovery.The two models showed different tumor behavior and the latter was more malignant than the former.

Genetic Analysis of Stripe Disease Resistance in Rice Restorer Line C224 Using Major Gene plus Polygene Mixed Effect Model

The inheritance of stripe disease resistance in a rice restorer line C224 was analyzed using the mixed effect model of major gene plus polygene for quantitative traits.In addition,the resistance was investigated in seven crosses of C224 with maintainer lines.The results showed that the stripe resistance of C224 was controlled by two major genes with additive-dominance-epistasis effects plus polygenes with additive-dominance effects （E-1 model）.These two genes had additive effects of-12.47% and-24.75%,respectively,showing negative dominance effects.There were significant epistasis and interaction effects between the two major genes.The heritability of the two major genes was 92.12%,while that of polygenes was 2.74%,indicating that the stripe resistance had dominant major gene effect.Of the seven crosses,five displayed high or medium resistance to the stripe disease.

A Numerical Study of a TOGA-COARE Squall-Line Using a Coupled Mesoscale Atmosphere-Ocean Model

An atmosphere-ocean coupled mesoscale modeling system is developed and used to investigate the interactions between a squall line and the upper ocean observed over the western Paci?c warm pool during the Tropical Ocean/Global Atmosphere Coupled Ocean and Atmosphere Response Experiment (TOGA-COARE). The modeling system is developed by coupling the Advanced Regional Prediction Sys- tem (ARPS) to the Princeton Ocean Model (POM) through precipitation and two-way exchanges of mo- mentum, heat, and moisture across the air-sea interface. The results indicate that the interaction between the squall-line and the upper ocean produced noticeable di?erences in the sensible and latent heat ?uxes, as compared to the uncoupled cases. Precipitation, which is often ignored in air-sea heat ?ux estimates, played a major role in the coupling between the mesoscale convective system and the ocean. Precipitation a?ected the air-sea interaction through both freshwater ?ux and sensible heat ?ux. The former led to the formation of a thin stable ocean layer underneath and behind the precipitating atmospheric convection. The presence of this stable layer resulted in a more signi?cant convection-induced sea surface temperature (SST) change in and behind the precipitation zone. However, convection-induced SST changes do not seem to play an important role in the intsensi?cation of the existing convective system that resulted in the SST change, as the convection quickly moved away from the region of original SST response.

RECONFIGURABLE PRODUCTION LINE MODELING AND SCHEDULING USING PETRI NETS AND GENETIC ALGORITHM

In response to the production capacity and functionality variations, a genetic algorithm （GA） embedded with deterministic timed Petri nets（DTPN） for reconfigurable production line（RPL） is proposed to solve its scheduling problem. The basic DTPN modules are presented to model the corresponding variable structures in RPL, and then the scheduling model of the whole RPL is constructed. And in the scheduling algorithm, firing sequences of the Petri nets model are used as chromosomes, thus the selection, crossover, and mutation operator do not deal with the elements in the problem space, but the elements of Petri nets model. Accordingly, all the algorithms for GA operations embedded with Petri nets model are proposed. Moreover, the new weighted single-objective optimization based on reconfiguration cost and E/T is used. The results of a DC motor RPL scheduling suggest that the presented DTPN-GA scheduling algorithm has a significant impact on RPL scheduling, and provide obvious improvements over the conventional scheduling method in practice that meets duedate, minimizes reconfiguration cost, and enhances cost effectivity.

Critical Length Criterion and the Arc Chain Model for Calculating the Arcing Time of the Secondary Arc Related to AC Transmission Lines

The prompt extinction of the secondary arc is critical to the single-phase reclosing of AC transmission lines, including half-wavelength power transmission lines. In this paper, a low- voltage physical experimental platform was established and the motion process of the secondary arc was recorded by a high-speed camera. It was found that the arcing time of the secondary arc rendered a close relationship with its arc length. Through the input and output power energy analysis of the secondary arc, a new critical length criterion for the arcing time was proposed. The arc chain model was then adopted to calculate the arcing time with both the traditional and the proposed critical length criteria, and the simulation results were compared with the experimental data. The study showed that the arcing time calculated from the new critical length criterion gave more accurate results, which can provide a reliable criterion in term of arcing time for modeling and simulation of the secondary arc related with power transmission lines.

Model of Three-Phase Transmission Line with the Theory of Modal Decomposition Implied

This paper shows the development of transmission line model, based on lumped element circuit that provides answers directly in the time and phase domain. This model is valid to represent the ideally transposed line, the phases of each of the small line segments are separated in their modes of propagation and the voltage and current are calculated at the modal domain. However, the conversion phase-mode-phase is inserted in the state equations which describe the currents and voltages along the line of which there is no need to know the user of the model representation of the theory in the line modal domain.

Sequencing of Mixed Model Assembly Lines Based on Improved Shuffled Frog Leaping Algorithm

Shuffled frog leaping algorithm( SFLA) was used to solve multi-objective sequencing problem of mixed model assembly line( MMAL). Local convergence can be avoided and optimal solution can be obtained to a certain extent. However,the multi-objective sequencing problem of MMAL is an non-deterministic polynomial hard( NP-hard) problem and the shortcomings are slow convergence rate and low precision. To solve the shortcomings for optimization objectives of minimizing total utility time and keeping average consumption rate of parts, a chaos differential evolution SFLA( CDESFLA) is proposed in this study. Because SFLA is easy to fall into local optimum,the evolution operator of differential evolution algorithms is introduced in SFLA as a local search strategy,and differential mutation operator is introduced in chaotic sequence to prevent premature convergence. The examples show that the proposed CDESFLA is better for convergence accuracy than SFLA,genetic algorithm( GA) and particle swarm optimization( PSO)

Numerical Study of a West African Squall Line Using a Regional Climate Model

The squall line of 21-22 August 1992, documented during the HAPEX-Sahel campaign, is simulated using the regional atmospheric model (MAR). The simulated results are compared to observational data. The aim of this work is both to test the capacity of this model to reproduce tropical disturbances in West Africa and to use this model as a meteorological one. It allows simulating high moisture content in the lower layers. The MAR simulates well updrafts whereas downward currents are neglected. This result may be due to convective scheme used to parameterize the convection in the model. The forecast of stability indexes used to define violent storms shows that the model is able to reproduce the squall line. Despite some differences with the observational data, the model shows its ability to reproduce major characteristics of the mesoscale convective disturbances.

A numerical model of coastline deformation for sandy beach at downstream of a jetty

A reformed numerical model based on the 'one-line theory' for beach deformation is presented. In this model, the change of beach slope during coastline procession is considered.A wave numerical model combined with wave refraction, diffraction and reflection is used to simulate wave climate to increase numerical accuracy.The results show that the numerical model has a good precision based on the adequate field data. The results can be applied to practical engineering.

Validation of the Actuator Line Model for Simulating Flows past Yawed Wind Turbine Rotors

The Actuator Line/Navier-Stokes model is validated against wind tunnel measurements for flows past the yawed MEXICO rotor and past the yawed NREL Phase VI rotor. The MEXICO rotor is operated at a rotational speed of 424 rpm, a pitch angle of ?2.3。, wind speeds of 10, 15, 24 m/s and yaw angles of 15。, 30。 and 45。. The computed loads as well as the velocity field behind the yawed MEXICO rotor are compared to the detailed pressure and PIV measurements which were carried out in the EU funded MEXICO project. For the NREL Phase VI rotor, computations were carried out at a rotational speed of 90.2 rpm, a pitch angle of 3。, a wind speed of 5 m/s and yaw angles of 10。and 30。. The computed loads are compared to the loads measured from pressure measurement.

Investigation of Tools, Techniques and Languages for Model Driven Software Product Lines (SPL): A Systematic Literature Review

Software development is a complex and difficult task that requires the investment of sufficient resources and carries major risk of failure. Model Driven Engineering (MDE) focuses on creating software models and automating code generation from the models. Model Driven Software Development (MDSD) offers significantly more effective approaches. These approaches improve the way of building software. Model driven approaches partially increase developer productivity, decrease the cost of software construction, improve software reusability, and make software more maintainable. This paper investigates the methods where Model Driven Software Development is integrated with Software Product Line (SPL). This SLR has been conducted to identify 71 research works published since 2014. We have collected 18 tools, 14 techniques and 17 languages used for MDSD for SPL. We analyze which technique is suitable for SPL. We compare the techniques on the basis of features provided by these tools to understand the better-quality results.

A Land Surface Model(IAP94) for Climate Studies PartI:Formulation and Validation in Off-line Experiments

The IAP (Institute of Atmospheric Physics) land-surface model (IAP94) is described. This model is a comprehensive one with detailed description for the processes of vegetation, snow and soil. Particular attention has been paid to the cases with three water phases in the surface media. On the basis of the mixture theory and the theory of fluid dynamics of porous media, the system of universal conservational equations for water and heat of soil, snow and vegetation canopy has been constructed. On this background, all important factors that may affect the water and heat balance in media can be considered naturally, and each factor and term possess distinct physical meaning. In the computation of water content and temperature, the water phase change and the heat transportation by water flow are taken into account. Moreover, particular attention has been given to the water vapor diffusion in soil for arid or semi-arid cases, and snow compaction. In the treatment of surface turbulent fluxes, the difference between aerodynamic and thermal roughness is taken into account. The aerodynamic roughness of vegetation is calculated as a function of canopy density, height and zero-plane displacement. An extrapolation of log linear and exponential relationship is used when calculating the wind profile within canopy. The model has been validated against field measurements in off-line simulations. The desirable model′s performance leads to the conclusion that the IAP94 is able to reproduce the main physical mechanisms governing the energy and water balances in the global land surface. Part II of the present study will concern the validation in a 3-D experiment coupled with the IAP Two-Level AGCM.

BLIND AND COMPLETE MODELING OF LINEAR SYSTEMS USING THIRD ORDER CUMULANTS

This paper presents a novel approach to structure determination of linear systems along with the choice of system orders and parameters. AutoRegressive （AR）, Moving Average （MA） or AutoRegressive-Moving Average （ARMA） model structure can be extracted blindly from the Third Order Cumulants （TOC） of the system output ts, where the unknown system is driven by an unobservable stationary independent identically distributed （i.i.d.） non-Gaussian signal. By means of the system order recursion, whether the system has an AR structure or has AR part of an ARMA structure is firstly investigated. MA features in the TOC domain is then applied as a threshold to decide if the system is an MA model or has MA part of an ARMA model. Numerical simulations illustrate the generality of the proposed blind structure identification methodology that may serve as a guideline for blind, linear system modeling.