Artificial Intelligence Model for Software Reusability Prediction System

The most significant invention made in recent years to serve various applications is software.Developing a faultless software system requires the soft-ware system design to be resilient.To make the software design more efficient,it is essential to assess the reusability of the components used.This paper proposes a software reusability prediction model named Flexible Random Fit(FRF)based on aging resilience for a Service Net(SN)software system.The reusability predic-tion model is developed based on a multilevel optimization technique based on software characteristics such as cohesion,coupling,and complexity.Metrics are obtained from the SN software system,which is then subjected to min-max nor-malization to avoid any saturation during the learning process.The feature extrac-tion process is made more feasible by enriching the data quality via outlier detection.The reusability of the classes is estimated based on a tool called Soft Audit.Software reusability can be predicted more effectively based on the pro-posed FRF-ANN(Flexible Random Fit-Artificial Neural Network)algorithm.Performance evaluation shows that the proposed algorithm outperforms all the other techniques,thus ensuring the optimization of software reusability based on aging resilient.The model is then tested using constraint-based testing techni-ques to make sure that it is perfect at optimizing and making predictions.

Quantifying Reusability of Object Oriented Design: A Testability Perspective

The quality factor of class diagram is critical because it has a significant influence on overall quality of the product, delivered finally. Testability analysis, when done early in the software creation process, is a criterion of critical importance to software quality. Reusability is an important quality factor to testability. Its early measurement in object oriented software especially at design phase, allows a design to be reapplied to a new problem without much extra effort. This research paper proposes a research framework for quantification process and does an extensive review on reusability of object oriented software. A metrics based model “Reusability Quantification of Object Oriented Design” has been proposed by establishing the relationship among design properties and reusability and justifying the correlation with the help of statistical measures. Also, “Reusability Quantification Model” is empirically validated and contextual significance of the study shows the high correlation for model acceptance. This research paper facilitates to software developers and designer, the inclusion of reusability quantification model to access and quantify software reusability for quality product.

Software Reusability Classification and Predication Using Self-Organizing Map (SOM)

Due to rapid development in software industry, it was necessary to reduce time and efforts in the software development process. Software Reusability is an important measure that can be applied to improve software development and software quality. Reusability reduces time, effort, errors, and hence the overall cost of the development process. Reusability prediction models are established in the early stage of the system development cycle to support an early reusability assessment. In Object-Oriented systems, Reusability of software components (classes) can be obtained by investigating its metrics values. Analyzing software metric values can help to avoid developing components from scratch. In this paper, we use Chidamber and Kemerer (CK) metrics suite in order to identify the reuse level of object-oriented classes. Self-Organizing Map (SOM) was used to cluster datasets of CK metrics values that were extracted from three different java-based systems. The goal was to find the relationship between CK metrics values and the reusability level of the class. The reusability level of the class was classified into three main categorizes (High Reusable, Medium Reusable and Low Reusable). The clustering was based on metrics threshold values that were used to achieve the experiments. The proposed methodology succeeds in classifying classes to their reusability level (High Reusable, Medium Reusable and Low Reusable). The experiments show how SOM can be applied on software CK metrics with different sizes of SOM grids to provide different levels of metrics details. The results show that Depth of Inheritance Tree (DIT) and Number of Children (NOC) metrics dominated the clustering process, so these two metrics were discarded from the experiments to achieve a successful clustering. The most efficient SOM topology [2 × 2] grid size is used to predict the reusability of classes.

Towards cultivar-oriented gene discovery for better crops

The continued expansion of the world population,increasingly inconsistent climate and shrinking agricultural resources present major challenges to crop breeding.Fortunately,the increasing ability to discover and manipulate genes creates new opportunities to develop more productive and resilient cultivars.Many genes have been described in papers as being beneficial for yield increase.However,few of them have been translated into increased yield on farms.In contrast,commercial breeders are facing gene decidophobia,i.e.,puzzled about which gene to choose for breeding among the many identified,a huge chasm between gene discovery and cultivar innovation.The purpose of this paper is to draw attention to the shortfalls in current gene discovery research and to emphasise the need to align with cultivar innovation.The methodology dictates that genetic studies not only focus on gene discovery but also pay good attention to the genetic backgrounds,experimental validation in relevant environments,appropriate crop management,and data reusability.The close of the gaps should accelerate the application of molecular study in breeding and contribute to future global food security.

Biocatalytic enhancement of laccase immobilized on ZnFe_(2)O_(4) nanoparticles and its application for degradation of textile dyes

Efficient and convenient treatment of industrial dyeing wastewater is of great significance to guarantee human and animal health.This work presented the enhanced catalytic activity at pH 3.0 of laccase immobilized on amino-functionalized ZnFe_(2)O_(4) nanoparticles(ZnFe_(2)O_(4)-laccase)and its application for the degradation of textile dyes.Due to the existence of a large number of oxygen vacancies on the surface of the ZnFe_(2)O_(4) nanoparticles,negative ions accumulated on the magnetic carriers,which resulted in a harsh optimal pH value of the ZnFe_(2)O_(4)-laccase.Laccase activity assays revealed that the ZnFe_(2)O_(4)-laccase possessed superior pH and thermal stabilities,excellent reusability,and noticeable organic solvent tolerance.Meanwhile,the ZnFe_(2)O_(4) laccase presented efficient and sustainable degradation of high concentrations of textile dyes.The initial decoloration efficiencies of malachite green(MG),brilliant green(BG),azophloxine,crystal violet(CV),reactive blue 19(RB19),and procion red MX-5B were approximately 99.1%,95.0%,93.3%,87.4%,86.1%,and 85.3%,respectively.After 10 consecutive reuses,the degradation rates of the textile dyes still maintained about 98.2%,92.5%,83.2%,81.5%,79.8%and 65.9%,respectively.The excellent dye degradation properties indicate that the ZnFe_(2)O_(4)-laccase has a technical application in high concentrations of dyestuff treatment.

Superwetting Ag/α-Fe_(2)O_(3) anchored mesh with enhanced photocatalytic and antibacterial activities for efficient water purification

Superwetting materials have drawn unprecedented attention in the treatment of oily wastewater due to their preferable anti-fouling property and selective oil/water separation.However,it is still a challenge to fabricate multifunctional and environmentally friendly materials,which can be stably applied to purify the actual complicated wastewater.Here,a Ag/Ag/α-Fe_(2)O_(3) heterostructure anchored copper mesh was intentionally synthesized using a facile two-step hydrothermal method.The resultant mesh with superhydrophilicity and underwater superoleophobicity was capable of separating various oil/water mixtures with superior separation efficiency and high permeationflux driven by gravity.Benefiting from the joint effects of the smaller band gap of Ag/α-Fe_(2)O_(3) heterojunction,inherent antibacterial capacity of Ag/α-Fe_(2)O_(3) and Ag nanoparticles,favorable conductive substrate,as well as the hierarchical structure with superwettability,such mesh presented remarkably enhanced degradation capability toward organic dyes under visible light irradiation and antibacterial activity against both Escherichia coli(E.coli)and Staphylococcus aureus(S.aureus)compared with the pure Ag/α-Fe_(2)O_(3) coated mesh.Impressively,the mesh exhibited bifunctional water purification performance,in which organic dyes were eliminated simultaneously from water during oil/water separation in onefiltration process.More importantly,this mesh behaved exceptional chemical resistance,mechanical stability and long-term reusability.Therefore,this material with multifunctional integration may hold promising potential for steady water purification in practice.

Leveraging React Components in Business Process Management (BPM) Applications

As organizations increasingly embrace digital transformation, the integration of modern web technologies like React.js with Business Process Management (BPM) applications has become essential. React components offer flexibility, reusability, and scalability, making them ideal for enhancing user interfaces and driving user engagement within BPM environments. This article explores the benefits, challenges, and best practices of leveraging React components in BPM applications, along with real-world examples of successful implementations.

Enhancing the reusability and interoperability of artificial neural networks with DEVS modeling and simulation

Artificial neural networks(ANNs),a branch of artificial intelligence,has become a very interesting domain since the eighties when back-propagation(BP)learning algorithm for multilayer feed-forward architecture was introduced to solve nonlinear problems.It is used extensively to solve complex nonalgorithmic problems such as prediction,pattern recognition and clustering.However,in the context of a holistic study,there may be a need to integrate ANN with other models developed in various paradigms to solve a problem.In this paper,we suggest discrete event system specification(DEVS)be used as a model of computation(MoC)to make ANN models interoperable with other models(since all discrete event models can be expressed in DEVS,and continuous models can be approximated by DEVS).By combining ANN and DEVS,we can model the complex configuration of ANNs and express its internal workings.Therefore,we are extending the DEVS-based ANN proposed by Toma et al.[A new DEVS-based generic art-ficial neural network modeling approach,The 23rd European Modeling and Simulation Symp.(Simulation in Industry),Rome,Italy,2011]for comparing multiple configuration parameters and learning algorithms and also to do prediction.The DEVS models are described using the high level language for system specification(HiLLS),[Ma¨ıga et al.,A new approach to modeling dynamic structure systems,The 29th European Modeling and Simulation Symp.(Simulation in Industry),Leicester,United Kingdom,2015]a graphical modeling language for clarity.The developed platform is a tool to transform ANN models into DEVS computational models,making them more reusable and more interoperable in the context of larger multi-perspective modeling and simulation(MAS).

Graphene oxide/hydrotalcite modified polyethersulfone nanohybrid membrane for the treatment of lead ion from battery industrial effluent

In the present study, polyethersulfone based nanohybrid membranes were effectively fabricated by incorporating graphene oxide(GO) and hydrotalcite(HT) nanosheets into the membrane structure. HT was prepared to overcome the irreversible agglomeration behavior of GO at a high concentration which affects the performance of the membranes. In particular, the shedding of HT in formamide provides a two-dimensional nanosheet with a higher positive charge density to prevent the restacking of GO nanosheets. Here, exfoliated GO and HT with different combinations(1:1, 1:2 and 1:3) were infused in the membrane matrix to treat lead-acid battery effluent effectively. Finally, the hybrid membranes were characterized for hydrophilicity, mechanical strength and pure water flux. In combination with the superior properties of GO and HT, the prepared hybrid membranes can be used as effectively to improve the separation and permeation performance. The phase inversion process eliminated the leaching of nanoparticles from the membrane matrix. The reusability of the hybrid membrane was achieved using0.1 mol·L^(-1)NaOH solution and reused without significant reduction in lead removal efficiency. The cost analysis of the membrane was also estimated from the lab study. Therefore, the present study suggested the selective and sustainable treatment of lead from a real-life effluent.

Robust and Reusable Fuzzy Extractors from Non-Uniform Learning with Errors Problem

Afuzzy extractor can extract an almost uniformrandom string from a noisy source with enough entropy such as biometric data.To reproduce an identical key from repeated readings of biometric data,the fuzzy extractor generates a helper data and a random string from biometric data and uses the helper data to reproduce the random string from the second reading.In 2013,Fuller et al.proposed a computational fuzzy extractor based on the learning with errors problem.Their construction,however,can tolerate a sub-linear fraction of errors and has an inefficient decoding algorithm,which causes the reproducing time to increase significantly.In 2016,Canetti et al.proposed a fuzzy extractor with inputs from low-entropy distributions based on a strong primitive,which is called digital locker.However,their construction necessitates an excessive amount of storage space for the helper data,which is stored in authentication server.Based on these observations,we propose a new efficient computational fuzzy extractorwith small size of helper data.Our scheme supports reusability and robustness,which are security notions that must be satisfied in order to use a fuzzy extractor as a secure authentication method in real life.Also,it conceals no information about the biometric data and thanks to the new decoding algorithm can tolerate linear errors.Based on the non-uniform learning with errors problem,we present a formal security proof for the proposed fuzzy extractor.Furthermore,we analyze the performance of our fuzzy extractor scheme and provide parameter sets that meet the security requirements.As a result of our implementation and analysis,we show that our scheme outperforms previous fuzzy extractor schemes in terms of the efficiency of the generation and reproduction algorithms,as well as the size of helper data.

Direct production of hydrogen peroxide over bimetallic CoPd catalysts:Investigation of the effect of Co addition and calcination temperature

A series of CoPd/KIT-6 bimetallic catalysts with various Co:Pd molar ratios at different calcination temperatures were prepared and used for the direct synthesis of H_(2)O_(2) from H_(2) and O_(2).These catalysts were characterized by nitrogen adsorption-desorption,low and wide-angle X-ray diffraction(XRD),X-ray photoelectron spectroscopy(XPS),transmission electron microscopy(TEM),scanning electron microscopy(SEM),elemental mapping and energy-dispersive X-ray(EDX)methods.It was found that the particle size,electronic interactions,morphology,and textural properties of these catalysts as well as their catalytic activity in the reaction of H_(2) with O_(2) were affected by Co addition and different calcination temperatures.Also,the results showed that while the H_(2)O_(2) selectivity depends on Pd^(2+) species,the H_(2) conversion is related to Pd0 active sites.Among these catalysts,CoPd/KIT-6 calcined at 350℃(CoPd/KIT-350 catalyst)showed the best catalytic activity with 50%of H_(2)O_(2) selectivity and 51%conversion of H_(2).

A360 Bot Framework: Empowering Smart Robotic Process Automation Solutions

This research paper explores the significance of the “A360 Bot Framework” in Automation 360 (A360) platform. A360 is Automation Anywhere’s cloud-based automation platform designed to make business processes more efficient. It’s known for its user-friendly interface, which allows both technical and non-technical users to use it effectively. Automation 360 is versatile, offering a range of tools to automate tasks, manage complex workflows, and integrate various applications. It empowers users to create customized solutions for their specific needs. Being cloud-based it ensures scalability, security, and real-time updates, making it a top choice in the fast-paced digital world. As demand for A360 rises, having a structured way to develop bots becomes crucial. The paper introduces the “A360 Bot Framework” as a guiding approach for bot developments. This framework ensures consistency and scalability, especially when working with both professional developers and non-technical users. It outlines key elements like setting up work folders, managing logs, dealing with errors, and ensuring secure bot execution. Ultimately, the “A360 Bot Framework” is presented as a foundational structure that enhances consistency, resiliency, and development efficiency. By following predefined practices and templates, bot developers can mitigate risks and streamline debugging processes. This framework accelerates the bot development lifecycle, allowing developers to focus on specific functionalities and value-added features. The research paper aims to provide insights into the benefits of adopting the A360 Bot Framework and its potential to revolutionize A360 bot development practices, leading to more efficient and effective automation solutions.

Maximizing the Efficiency of Automation Solutions with Automation 360: Approaches for Developing Subtasks and Retry Framework

I present a solution that explores the use of A360 subtasks as a comparable concept to functions in programming. By leveraging subtasks as reusable and maintainable functions, users can efficiently develop customized high-quality automation solutions. Additionally, the paper introduces the retry framework, which allows for the automatic retrying of subtasks in the event of system or unknown exceptions. This framework enhances efficiency and reduces the manual effort required to retrigger bots. The A360 Subtask and Retry Framework templates provide valuable assistance to both professional and citizen developers, improving code quality, maintainability, and the overall efficiency and resiliency of automation solutions.

Watt Linkage–Based Legged Deployable Landing Mechanism for Reusable Launch Vehicle: Principle, Prototype Design, and Experimental Validation

The reusable launch vehicle (RLV) presents a new avenue for reducing cost of space transportation. The landing mechanism, which provides landing support and impact absorption, is a vital component of the RLV at final stage of recovery. This study proposes a novel legged deployable landing mechanism (LDLM) for RLV. The Watt-II six-bar mechanism is adopted to obtain the preferred configuration via the application of the linkage variation approach. To endow the proposed LDLM with advantages of large landing support region, lightweight, and reasonable linkage internal forces, a multi-objective optimization paradigm is developed. Furthermore, the optimal scale parameters for guiding the LDLM prototype design is obtained numerically using the non-dominated sorting genetic algorithm-II (NSGA-II) evolutionary algorithm. A fully-functional scaled RLV prototype is developed by integrating the gravity-governed deploying scheme to facilitate unfolding action to avoid full-range actuation, a dual-backup locking mechanism to enhance reliability of structure stiffening as fully deployed, and a shock absorber (SA) with multistage honeycomb to offer reliable shock absorbing performance. The experimental results demonstrate that the proposed LDLM is capable of providing rapid and smooth deployment (duration less than 1.5 s) with mild posture disturbance to the cabin (yaw and pitch fluctuations less than 6°). In addition, it provides satisfactory impact attenuation (acceleration peak less than 10g (g is the gravitational acceleration)) in the 0.2 m freefall test, which makes the proposed LDLM a potential alternative for developing future RLV archetype.

Efficient heavy metal recycling and water reuse from industrial wastewater using new reusable and inexpensive polyphenylene sulfide derivatives

Heavy metal(HM)pollution is a serious environment problem.Recovering HM from industrial wastewater by efficient adsorbents is a sustainable method due to recycling HM and acquiring reusable water.However,popular efficient adsorbents are usually expensive or non-reusable.In this paper,methods of efficient HM recycling and water reuse from industrial wastewater were developed using efficient adsorbents,new polyphenylene sulfide derivatives,which are recyclable and stable in an acidic,alkaline or oxidative aqueous solution.Moreover,they can efficiently and quickly adsorb HM ions.The maximum adsorption capacities of these adsorbents for HM ions are at the range from 51.3-184.2 mg·g^(-1).The adsorption equilibrium times of them for HM ions are at the range from 10 to 80 min.Therefore,this paper suggests sustainable methods of HM recovery and water reuse from industrial wastewater.

A Footpad Structure with Reusable Energy Absorption Capability for Deep Space Exploration Lander:Design and Analysis

The footpad structure of a deep space exploration lander is a critical system that makes the initial contact with the ground,and thereby plays a crucial role in determining the stability and energy absorption characteristics during the impact process.The conventional footpad is typically designed with an aluminum honeycomb structure that dissipates energy through plastic deformation.Nevertheless,its effectiveness in providing cushioning and energy absorption becomes significantly compromised when the structure is crushed,rendering it unusable for reusable landers in the future.This study presents a methodology for designing and evaluating structural energy absorption systems incorporating recoverable strain constraints of shape memory alloys(SMA).The topological configuration of the energy absorbing structure is derived using an equivalent static load method(ESL),and three lightweight footpad designs featuring honeycomb-like Ni-Ti shape memory alloys structures and having variable stiffness skins are proposed.To verify the accuracy of the numerical modelling,a honeycomb-like structure subjected to compression load is modeled and then compared with experimental results.Moreover,the influence of the configurations and thickness distribution of the proposed structures on their energy absorption performance is comprehensively evaluated using finite element simulations.The results demonstrate that the proposed design approach effectively regulates the strain threshold to maintain the SMA within the constraint of maximum recoverable strain,resulting in a structural energy absorption capacity of 362 J/kg with a crushing force efficiency greater than 63%.

A reconfigurable dynamic Bayesian network for digital twin modeling of structures with multiple damage modes

Dynamic Bayesian networks(DBNs)are commonly employed for structural digital twin modeling.At present,most researches only consider single damage mode tracking.It is not sufficient for a reusable spacecraft as various damage modes may occur during its service life.A reconfigurable DBN method is proposed in this paper.The structure of the DBN can be updated dynamically to describe the interactions between different damages.Two common damages(fatigue and bolt loosening)for a spacecraft structure are considered in a numerical example.The results show that the reconfigurable DBN can accurately predict the acceleration phenomenon of crack growth caused by bolt loosening while the DBN with time-invariant structure cannot,even with enough updates.The definition of interaction coefficients makes the reconfigurable DBN easy to track multiple damages and be extended to more complex problems.The method also has a good physical interpretability as the reconfiguration of DBN corresponds to a specific mechanism.Satisfactory predictions do not require precise knowledge of reconfiguration conditions,making the method more practical.

LLSDA: Design and Implementation of Lightning Location Data Analysis and Visualization

Visualizing lightning location data is necessary in analyzing and researching lightning activity patterns.This article uses C#and the cross-platform.NET framework to develop a lightning location data analysis class library and the data-driven client to help lightning researchers improve work efficiency by avoiding repeated wheel invention.Lightning Location System Data Analyzer(LLSDA)is a suite of software tools that includes a.NET class library for software developers and a desktop application for end users.It supports a wide range of lightning location data formats,such as the University of Washington Global Lightning Location System(WWLLN)and Beijing Huayun Dongfang ADTD Lightning Location System data format,and maintains scalability.The class library can easily read,parse,and analyze lightning location data,and combined with third-party frameworks can realize grid analysis.The desktop application can be combined with MeteoInfo(a GIS open-source project)for secondary development.

An efficient synthesis of ampicillin on magnetically separable immobilized penicillin G acylase

Penicillin G acylase(PGA) was immobilized on the magnetic hydrophilic polymer microspheres with average pore size of 17.1 nm,specific surface area of 128.2 m2/g and saturate magnetization of 6.4 emu/g.The 96.7%ampicillin yield with 1.60 of the synthesis/hydrolysis(S/H) ratio from 6-aminopenicillanic acid(6-APA) and D-(-)-alpha-phenylglycine methyl ester(D-PGME) can be achieved using the resultant magnetic biocatalyst in ethylene glycol,where only 82.1%yield with 1.40 of the S/H ratio was obtained using the free PGA under the identical reaction conditions.The immobilized PGA can be separated magnetically and recycled for five times without obvious loss of its catalytic activity.

A new approach to the synthesis of diacetals(diketals) pentaerythritol catalyzed by SO_3H-functionalized ionic liquids

In this article,an efficient,simple and environmentally friendly approach to the synthesis of diacetals(diketals) pentaerythritol using SOH-functionalized ionic liquids(ILs) as catalysts was reported.The ILs show high catalytic activity and reusability with good to excellent yields of the desired products.Hammett method has been used to determine the acidity order of these ionic liquids and the results are consistent with the catalytic activities observed in acetalization reaction.Maximum product yield of 93%was observed on using[PSPy][OTf]as catalyst and it can be reused at least 8 times without obvious activity loss.