Reusable Requirements Research Articles

Mechanical properties of lander bionic buffer structure based on additive manufacturing

In order to meet the energy absorption requirements of the landing buffer, this paper starts with the buffer filling material of the buffer, draws on the Kelvin structure and spiral structure, and applies the engineering bionics principle to design and establish two structural models: a soccerball-like bionic structure and a multi-spiral bionic structure. Considering the energy absorption and reusability requirements of the lander buffer structure, the bionic structure sample is prepared by additive manufacturing technology and NiTi alloy with shape memory effect. The mechanical properties, energy absorption and recoverability of the sample are analyzed and verified by simulation and experiment. The results show that the accuracy of the numerical simulation is verified by comparing the force-displacement curves of the simulation test and the isometric static pressure test; the multi-spiral bionic structure has better mechanical properties, and its maximum energy absorption is 3096.23 J; the recovery rates of the two structures are as high as 98.02%and respectively 97.12%, and the recovery rate of the soccerball-like bionic structure is slightly higher. This study uses additive manufacturing to prepare the leg-type lander buffer bionic structure, which provides a reference for the bionic design of the lander buffer structure.

A drug-mediated organic electrochemical transistor for robustly reusable biosensors.

Reusable point-of-care biosensors offer a cost-effective solution for serial biomarker monitoring, addressing the critical demand for tumour treatments and recurrence diagnosis. However, their realization has been limited by the contradictory requirements of robust reusability and high sensing capability to multiple interactions among transducer surface, sensing probes and target analytes. Here we propose a drug-mediated organic electrochemical transistor as a robust, reusable epidermal growth factor receptor sensor with striking sensitivity and selectivity. By electrostatically adsorbing protonated gefitinib onto poly(3,4-ethylenedioxythiophene):polystyrene sulfonate and leveraging its strong binding to the epidermal growth factor receptor target, the device operates with a unique refresh-in-sensing mechanism. It not only yields an ultralow limit-of-detection concentration down to 5.74 fg ml-1 for epidermal growth factor receptor but, more importantly, also produces an unprecedented regeneration cycle exceeding 200. We further validate the potential of our devices for easy-to-use biomedical applications by creating an 8 × 12 diagnostic drug-mediated organic electrochemical transistor array with excellent uniformity to clinical blood samples.

Cross-linking polybutadiene rubber via a thiol-ene reaction with polycysteine as a degradable cross-linker

Covalently cross-linked rubber materials are widely used in elastic applications due to their excellent mechanical properties. However, the irreversibility of covalent cross-linking suffers from poor material recyclability. As a degradable polypeptide-based cross-linker for polybutadiene, poly(l-cysteine) (polyCys) was synthesized via papain-catalyzed chemoenzymatic polymerization. The resulting polyCys had intact thiol groups that cross-linked polybutadiene via the thiol-ene reaction. The cross-linking reaction of polybutadiene was performed in the presence of polyCys and a radical initiator and resulted in insoluble polybutadiene gel formation. Based on Raman spectroscopy analysis, the cross-linking reaction was confirmed by the consumption of thiol groups of polyCys. From the dynamic viscoelastic analyses of the cross-linked polybutadienes, the viscoelasticity drastically changed from that of raw polybutadiene, with the disappearance of the slow relaxation mode at low frequencies. The complete network formation was confirmed by E′ and E′′ showing the power law over the whole frequency range, as determined by the time-course experiments of the dynamic viscoelastic properties. The cross-linked polybutadiene was degradable by acid hydrolysis, resulting in the regeneration of soluble polybutadiene. Polypeptide cross-linked polybutadiene materials are promising candidates for the application of polybutadiene-based rubber materials with the requirements of both material integrity and reusability.

Oxygen-induced dual-signal point-of-care testing aptasensor for aflatoxin B1 detection using platinum nanoparticle catalysis in visual fluorometry and gravimetry

Point-of-care testing (POCT) has experienced rapid development owing to its advantages of rapid testing, low cost and strong operability, making it indispensable for analyte detection in outdoor or rural areas. In this study, we propose a novel method for the detection of aflatoxin B1 (AFB1) using a dual-signal readout approach within a unified system. This method employs dual channel modes, namely visual fluorescence and weight measurements, as the signal readouts. Specifically, a pressure-sensitive material is utilized as a visual fluorescent agent, its signal can be quenched in the presence of high oxygen pressure. Additionally, an electronic balance, commonly used for weight measurement, is adopted as another signal device, where the signal is generated through the catalytic decomposition of H2O2 by platinum nanoparticles. The experimental results demonstrate that the proposed device enables accurate AFB1 detection within the concentration range of 1.5–32 μg mL−1, with a detection limit of 0.47 μg mL−1. Moreover, this method has been successfully applied for practical AFB1 detection with satisfactory results. Notably, this study pioneers the use of a pressure-sensitive material as a visual signal in POCT. By addressing the limitations of single-signal readout approaches, our method fulfills requirements of intuitiveness, sensitivity, quantitative analysis and reusability.

Preparation of pitch-based carbon materials by pyrolysis and their electrocatalytic activity in oxygen reduction reaction

Electrocatalytic in-situ production of hydrogen peroxide (H2O2) has attracted continuous attention due to its advantages of cleanliness and safety. However, this method is difficult to meet the requirements of high activity and excellent reusability, which limits its wide application. In this work, cheap pitch was used as carbon source and Co(NO3)2 was used as catalyst precursor to convert its products into carbon nanotubes (CNTs) with high aspect ratio through catalytic pyrolysis. Subsequently, anthraquinone was used to covalently modify CNTs as electrocatalytic electrodes. The experimental results showed that CNTs covalently modified by anthraquinone significantly increased the activity of H2O2 production. The results showed that the improved activity of the optimal electrode was due to the increase of the initial potential of oxygen reduction and the ultimate current density.

Screen-printing of core-shell Mn3O4@C nanocubes based sensing microchip performing ultrasensitive recognition of allura red

Allura red (AR) is a member of azo dyes is commonly used as an additive in foods and soft drinks. However, due to the special harm of the azo structure to the human body, the dosage control of AR becomes particularly necessary. The present detection methods are time-consuming, expensive and complicated. In order to address the above issues, a core-shell nanocubes constructed sensor has been developed to determine the ultrawide detection range and selective recognition of AR with a long-term reusability. The core-shell architecture is composed of carbon material of 12.64 nm thickness covering 600 nm Mn3O4 nanocube. This nanocomposite combines the advantages of Mn3O4@C, possessing high electrocatalysis and chemical stability. As confirmed in using sports drinks as real samples, the as-prepared AR sensor exhibites excellent selectivity with an ultra-wide linear range from 0.1 to 1748.4 μM, and meanwhile, this sensor can also meet the requirements of remarkable anti-interference and reusability over 30 days.

Towards ubiquitous requirements engineering through recommendations based on context histories.

The growing technological advance is causing constant business changes. The continual uncertainties in project management make requirements engineering essential to ensure the success of projects. The usual exponential increase of stakeholders throughout the project suggests the application of intelligent tools to assist requirements engineers. Therefore, this article proposes Nhatos, a computational model for ubiquitous requirements management that analyses context histories of projects to recommend reusable requirements. The scientific contribution of this study is the use of the similarity analysis of projects through their context histories to generate the requirement recommendations. The implementation of a prototype allowed to evaluate the proposal through a case study based on real scenarios from the industry. One hundred fifty-three software projects from a large bank institution generated context histories used in the recommendations. The experiment demonstrated that the model achieved more than 70% stakeholder acceptance of the recommendations.

Integrated Thermal Protection System Design for Hypersonic Vehicle Based on New Thermal–Mechanical Method

With the development of hypersonic vehicles, considerable attention has been paid to thermal protection systems (TPSs). Among the different types of TPS, integrated TPS (ITPS) has attracted extensive interest because of its light weight, cost effectiveness, bearing capacity, and easy maintenance. However, ITPS, with its complex structure and reusable requirement, is facing challenges and it is worth devoting much effort to this. In an effort to overcome these challenges, we develop a novel approximate analytical method based on separation of variables and orthogonal expansion technique, which is presented for the prediction of heat transfer. The approximate analytical method has the ability to consider the effects of temperature-dependent thermal material properties, convection and radiation. Moreover, a C0 higher-order layer-wise finite-element model combined with homogenization techniques and a simplified three-dimensional (3D) finite-element model based on the periodic structure characteristic are proposed to estimate the thermal–mechanical response and stability of ITPS effectively. In addition, an optimization procedure based on the proposed methods for ITPS is developed. Implementation of the optimization is demonstrated by applying it to design the ITPS of space shuttles and hypersonic vehicles. By comparing with conventional thermal protection systems (CTPSs), ITPS exhibits an outstanding advantage in weight and an acceptable disadvantage in size. The objective of this paper is to establish an accurate and efficient design method aiming at determination of the optimal performance of ITPS, and puts forward the foundation for the development of a hypersonic vehicle.

Effective Hybrid Content-Based Collaborative Filtering Approach for Requirements Engineering

Requirements engineering (RE) is among the most valuable and critical processes in software development. The quality of this process significantly affects the success of a software project. An important step in RE is requirements elicitation, which involves collecting project-related requirements from different sources. Repositories of reusable requirements are typically important sources of an increasing number of reusable software requirements. However, the process of searching such repositories to collect valuable project-related requirements is time-consuming and difficult to perform accurately. Recommender systems have been widely recognized as an effective solution to such problem. Accordingly, this study proposes an effective hybrid content-based collaborative filtering recommendation approach. The proposed approach will support project stakeholders in mitigating the risk of missing requirements during requirements elicitation by identifying related requirements from software requirement repositories. The experimental results on the RALIC dataset demonstrate that the proposed approach considerably outperforms baseline collaborative filtering-based recommendation methods in terms of prediction accuracy and coverage in addition to mitigating the data sparsity and cold-start item problems.

Optimization of supercritical CO2 extraction by response surface methodology, composition analysis and economic evaluation of bamboo green wax

Bamboo processing is faced with increasing requirements of resource reusability in China. A large amount of waste bamboo green produced in bamboo processing needs to be recycled. Waste bamboo green contains a large number of environmentally friendly wax components. In this study, supercritical CO2 extraction was used to extract bamboo green waste to obtain natural wax. Response surface methodology (RSM) was used to optimize the extraction process and the yield of bamboo green wax under pressure of 20–30 MPa, temperature of 318–328 K, and time of 30–90 min. The extracted bamboo green wax was characterized by gas chromatography and mass spectrometry (GC-MS). RSM optimization shows that under the conditions of 26 MPa, 328 K, and 56 min, the yield of bamboo green wax was the highest at 2.327%. The compositions of esters, fatty acids, sterols and so on in bamboo green wax were characterized by GC-MS. Differential scanning calorimetry (DSC) shows that the melting point of bamboo green wax is 334 K. At last, the economic evaluation of bamboo green wax was made to analyze its potential application prospect. It is supposed that bamboo green waste is a resource for natural wax with potential application value.

Utilization of a double-cross-linked amino-functionalized three-dimensional graphene networks as a monolithic adsorbent for methyl orange removal: Equilibrium, kinetics, thermodynamics and artificial neural network modeling

Herein, it is aimed to develop a high-performance monolithic adsorbent to be utilized in methyl orange (MO) adsorption. Therefore, amino-functionalized three-dimensional graphene networks (3D-GNf) fulfilling the requirements of reusability and high capacity have been fabricated via hydrothermal self-assembly approach followed by a double-crosslinking strategy. The potential utilization of 3D-GNf as an adsorbent for removal MO has been assessed using both batch-adsorption studies and an artificial neural network (ANN) approach. Graphene oxide sheets have been amino-functionalized and cross-linked, by ethylenediamine (EDA) during hydrothermal treatment, following the glutaraldehyde has used as a double-crosslinking agent to facilitate the crosslinking of architecture. The successful fabrication of 3D-GNf has been confirmed by field-emission scanning electron microscopy (FESEM), Fourier transform infrared (FT-IR), Raman and X-ray photoelectron spectroscopy (XPS). Moreover, N2 adsorption/desorption isotherms have revealed the high specific surface area (1015 m2 g−1) with high pore volume (1.054 cm3 g−1) and hierarchical porous structure of 3D-GNf. The effect of initial concentration, contact time, and temperature on adsorption capacity have been thoroughly studied, and the kinetics, isotherms, and thermodynamics of MO adsorption have been modelled. The MO adsorption has been well defined by the pseudo-second-order kinetic model and Langmuir isotherm model with a monolayer adsorption capacity of 270.27 mg g−1 at 25 °C. The thermodynamic findings have revealed MO adsorption has occurred spontaneously with an endothermic process. The Levenberg-Marquardt backpropagation algorithm has been implemented to train the ANN model, which has used the activation functions of tansig and purelin functions at the hidden and output layers, respectively. An optimum ANN model with high-performance metrics (coefficient of determination, R2 = 0.9995; mean squared error, MSE = 0.0008) composed of three hidden layers with 5 neurons in each layer was constructed to forecast MO adsorption. The findings have shown that experimental results are consistent with ANN-based data, implying that the suggested ANN model may be used to forecast cationic dye adsorption.

Reusability of existing structural steel

AbstractUsing reclaimed structural steel on a project is an effective strategy to cut the environmental impacts associated with the production of new steel. This practice cannot be generalised to all structural steel however, as not all components can be effectively or safely reused. This paper focuses on single‐storey buildings, which are particularly attractive for reclaiming and reusing structural steel. Functional reusability requirements are set out below, in particular, the requirements related to the adequacy and reliability assessment of the reclaimed steel, to ensure that (i) the reclaimed material satisfies the performance requirements, which are essential for the mechanical, physical, dimensional, and/or other relevant properties of steel materials to ensure their adequacy to be used in structural design to EN 1993, (ii) the salvaged material meets the quality requirements from nominal specifications to ensure their reliability to be used in the structural design to EN 1993, and (iii) structures made from reclaimed steel have continued integrity.

Health Data, Information, and Knowledge Sharing for Addressing the COVID-19

SummaryObjectives: To introduce the 2021 International Medical Informatics Association (IMIA) Yearbook by the editors. Methods: The editorial provides an introduction and overview to the 2021 IMIA Yearbook whose special topic is “Managing Pandemics with Health Informatics - Successes and Challenges”. The Special Topic, the keynote paper, and survey papers are discussed. The IMIA President's statement and the IMIA dialogue with the World Health Organization are introduced. The sections’ changes in the Yearbook Editorial Committee are also described. Results: Health informatics, in the context of a global pandemic, led to the development of ways to collect, standardize, disseminate and reuse data worldwide: public health data but also information from social networks and scientific literature. Fact checking methods were mostly based on artificial intelligence and natural language processing. The pandemic also introduced new challenges for telehealth support in times of critical response. Next generation sequencing in bioinformatics helped in decoding the sequence of the virus and the development of messenger ribonucleic acid (mRNA) vaccines. Conclusions: The Corona Virus Disease 2019 (COVID-19) pandemic shows the need for timely, reliable, open, and globally available information to support decision making and efficiently control outbreaks. Applying Findable, Accessible, Interoperable, and Reusable (FAIR) requirements for data is a key success factor while challenging ethical issues have to be considered.

A Framework for Loadable Airborne Systems

The software loading occurs when a new software version corrects previously identified errors to include new functionalities to airborne systems, such as those embedded in aircraft. The available literature has not yet scientifically addressed the characteristics of Loadable Airborne Systems (LASs). Although the RTCA DO-178 introduced the concept of field-loadable software, which is the possibility to update the software without the need to remove the equipment or system from its installation on the aircraft, the industry does not yet have an organized framework of reusable requirements and tests. The objective of this work is to present a new framework for LASs. This framework contains a set of reusable requirements and general test procedures for software loading, involving manual and automatic checks. We believe that our framework can help smaller companies, especially market entrants, to incorporate software loading capacity into system development. This work also includes the identification of threats involving safety and security.

Enhancing Software Feature Extraction Results Using Sentiment Analysis to Aid Requirements Reuse

Recently, feature extraction from user reviews has been used for requirements reuse to improve the software development process. However, research has yet to use sentiment analysis in the extraction for it to be well understood. The aim of this study is to improve software feature extraction results by using sentiment analysis. Our study’s novelty focuses on the correlation between feature extraction from user reviews and results of sentiment analysis for requirement reuse. This study can inform system analysis in the requirements elicitation process. Our proposal uses user reviews for the software feature extraction and incorporates sentiment analysis and similarity measures in the process. Experimental results show that the extracted features used to expand existing requirements may come from positive and negative sentiments. However, extracted features with positive sentiment overall have better values than negative sentiments, namely 90% compared to 63% for the relevance value, 74–47% for prompting new features, and 55–26% for verbatim reuse as new requirements.

Globally Optimal Redundancy Resolution with Dynamic Programming for Robot Planning: A ROS Implementation

Dynamic programming techniques have proven much more flexible than calculus of variations and other techniques in performing redundancy resolution through global optimization of performance indices. When the state and input spaces are discrete, and the time horizon is finite, they can easily accommodate generic constraints and objective functions and find Pareto-optimal sets. Several implementations have been proposed in previous works, but either they do not ensure the achievement of the globally optimal solution, or they have not been demonstrated on robots of practical relevance. In this communication, recent advances in dynamic programming redundancy resolution, so far only demonstrated on simple planar robots, are extended to be used with generic kinematic structures. This is done by expanding the Robot Operating System (ROS) and proposing a novel architecture meeting the requirements of maintainability, re-usability, modularity and flexibility that are usually required to robotic software libraries. The proposed ROS extension integrates seamlessly with the other software components of the ROS ecosystem, so as to encourage the reuse of the available visualization and analysis tools. The new architecture is demonstrated on a 7-DOF robot with a six-dimensional task, and topological analyses are carried out on both its state space and resulting joint-space solution.

PARKEY : ticket-less parking system using license plate recognition approach

As of recent practice, the majority of current parking systems are still implementing the same traditional method of giving entry to parking visitors which is by giving out a physical ticket. This has caused several problems for mall visitors. Therefore, it is planned to propose a system that can eliminate the problems and provide further improvement to the current systems. Our proposed system named PARKEY is a Ticket-less Parking System that has been designed to provide a new method of parking entry and exiting while implementing new features in the parking system. The objective of the project is to provide a working ticket-less entry and exit system by using a virtual ticket with the help of image recognition technology. With the proposed system being developed, it will help to solve problems that are present in the current systems and give an implementation of a parking system that is up to par with the current standard of technology. Before the system was developed, interviews, observation, and requirement reuse were used as methods to elicit requirements that will provide useful insights for the development of the system. Before the system was developed, interviews, observation, and requirement reuse were used as methods to elicit requirements that will provide useful insights for the development of the system. This includes providing questions to users, making observations to current systems deployed, and studying existing systems ranging from older systems to newer, similar systems. Using the stated elicitation techniques, some findings were gathered and are beneficial to the development of the system. The use of observation to current parking systems helps provides data that will be used as a benchmark for the proposed system to identify how quick the proposed system reaction time should be to provide an on-par performance with the current systems. Interviews with several potential users were done to gather information on their experience from the current parking systems and their opinions on what can be improved and expectations of the proposed system. Other than that, studying the currently available systems gives a better understanding of the drawbacks and limitations of the current systems and provides some functionalities from those systems that can be combined and implemented to benefit the proposed system’s improvement during development. The developed proposed system applies a combined usage of a web application, license plate recognition technology, and an e-wallet based payment system to tackle current parking system problems.

A hybrid collaborative filtering recommendation algorithm for requirements elicitation

Requirements elicitation is one of the most critical and difficult tasks in software development. Requirements reuse has shown to be an effective and efficient elicitation technique that can enhance the quality of the requirements elicitation process and, as a result, lead to a project's success. However, the information overload problem, which is caused by the rapidly growing number of reusable software requirements in large requirements repositories, hinders the effectiveness of the requirements reuse process. Recommender systems proved to be a well-known solution to such problems. This paper focuses on the adoption of recommender systems to mitigate the problem of information overload that is inherent in the requirements elicitation process, specifically by assisting requirement engineers in retrieving relevant reusable requirements from large-scale requirements repositories. The validation results on the RALIC dataset illustrate that the proposed algorithm outperforms and mitigates the drawbacks of the benchmark collaborative filtering-based recommendation approaches.

A hybrid collaborative filtering recommendation algorithm for requirements elicitation

Requirements elicitation is one of the most critical and difficult tasks in software development. Requirements reuse has shown to be an effective and efficient elicitation technique that can enhance the quality of the requirements elicitation process and, as a result, lead to a project's success. However, the information overload problem, which is caused by the rapidly growing number of reusable software requirements in large requirements repositories, hinders the effectiveness of the requirements reuse process. Recommender systems proved to be a well-known solution to such problems. This paper focuses on the adoption of recommender systems to mitigate the problem of information overload that is inherent in the requirements elicitation process, specifically by assisting requirement engineers in retrieving relevant reusable requirements from large-scale requirements repositories. The validation results on the RALIC dataset illustrate that the proposed algorithm outperforms and mitigates the drawbacks of the benchmark collaborative filtering-based recommendation approaches.

Repository Construction and Reuse of Software Requirement

Software reuse is not limited to reusing code used a lot but can be used in all steps and activities related to software production. In particular, the reuse of requirements has various benefits by reusing reliable requirements, and the development of requirements is an early stage of software development and may have higher efficiency than the utilization of reuse in later stages if reuse is utilized from the initial stage. However, despite its many advantages, the study on the reuse of requirements is insufficient. Therefore, to explore the possibility of the requirements reuse, we conducted a total of four stages in this paper: selection of targets and stakeholders, construction of requirements repository, reuse of requirements repository, and result analysis, and a case study of requirements repository construction and reuse was conducted. We have confirmed the fact that the reuse of requirements possible with a high proportion in practice through the application of actual case and we have also confirmed the possibility of research on the reuse of requirements. If we deal with the reliable requirements by increasing the utilization of requirements reuse, the possibility of the project's success will also be greatly increased.