Classification and Comprehension of Software Requirements Using Ensemble Learning

The software development process mostly depends on accurately identifying both essential and optional features.Initially,user needs are typically expressed in free-form language,requiring significant time and human resources to translate these into clear functional and non-functional requirements.To address this challenge,various machine learning(ML)methods have been explored to automate the understanding of these requirements,aiming to reduce time and human effort.However,existing techniques often struggle with complex instructions and large-scale projects.In our study,we introduce an innovative approach known as the Functional and Non-functional Requirements Classifier(FNRC).By combining the traditional random forest algorithm with the Accuracy Sliding Window(ASW)technique,we develop optimal sub-ensembles that surpass the initial classifier’s accuracy while using fewer trees.Experimental results demonstrate that our FNRC methodology performs robustly across different datasets,achieving a balanced Precision of 75%on the PROMISE dataset and an impressive Recall of 85%on the CCHIT dataset.Both datasets consistently maintain an F-measure around 64%,highlighting FNRC’s ability to effectively balance precision and recall in diverse scenarios.These findings contribute to more accurate and efficient software development processes,increasing the probability of achieving successful project outcomes.

An Investigation on Open-RAN Specifications:Use Cases,Security Threats,Requirements,Discussions

The emergence of various technologies such as terahertz communications,Reconfigurable Intelligent Surfaces(RIS),and AI-powered communication services will burden network operators with rising infrastructure costs.Recently,the Open Radio Access Network(O-RAN)has been introduced as a solution for growing financial and operational burdens in Beyond 5G(B5G)and 6G networks.O-RAN promotes openness and intelligence to overcome the limitations of traditional RANs.By disaggregating conventional Base Band Units(BBUs)into O-RAN Distributed Units(O-DU)and O-RAN Centralized Units(O-CU),O-RAN offers greater flexibility for upgrades and network automation.However,this openness introduces new security challenges compared to traditional RANs.Many existing studies overlook these security requirements of the O-RAN networks.To gain deeper insights into the O-RAN system and security,this paper first provides an overview of the general O-RAN architecture and its diverse use cases relevant to B5G and 6G applications.We then delve into specifications of O-RAN security threats and requirements,aiming to mitigate security vulnerabilities effectively.By providing a comprehensive understanding of O-RAN architecture,use cases,and security considerations,thisworkserves as a valuable resource for future research in O-RAN and its security.

Requirements ranking based on crowd-sourcing high-end product USs

Based on the characteristics of high-end products,crowd-sourcing user stories can be seen as an effective means of gathering requirements,involving a large user base and generating a substantial amount of unstructured feedback.The key challenge lies in transforming abstract user needs into specific ones,requiring integration and analysis.Therefore,we propose a topic mining-based approach to categorize,summarize,and rank product requirements from user stories.Specifically,after determining the number of story categories based on py LDAvis,we initially classify“I want to”phrases within user stories.Subsequently,classic topic models are applied to each category to generate their names,defining each post-classification user story category as a requirement.Furthermore,a weighted ranking function is devised to calculate the importance of each requirement.Finally,we validate the effectiveness and feasibility of the proposed method using 2966 crowd-sourced user stories related to smart home systems.

Autoantibodies against beta cells to predict early insulin requirements in pediatric patients with clinically diagnosed type 2 diabetes

BACKGROUND Autoimmunity has emerged as a probable disease modifier in patients with clinically diagnosed type 2 diabetes mellitus(T2DM),that is,patients who have insulin resistance,obesity,and other cardiovascular risk factors,suggesting that the presence of glutamic acid decarboxylase(anti-GAD65),islet antigen 2(anti-IA2),and zinc transporter 8(anti-Zn8T)antibodies could have deleterious effects on beta cell function,causing failure and earlier requirement for insulin treatment.AIM To evaluate anti-GAD65,anti-IA2 and anti-Zn8T as predictors of early insulin requirement in adolescents with a clinical diagnosis of T2DM.METHODS This was a case–control study in patients with clinically diagnosed with T2DM(68 cases and 64 controls with and without early insulin dependence respectively),male and female,aged 12–18 years.Somatometry,blood pressure,glucose,insulin,C-peptide,glycated hemoglobin A1c,and lipid profiles were assessed.ELISA was used to measure anti-GAD65,anti-IA2,and anti-Zn8T antibodies.Descriptive statistics,Pearson'sχ2 test,Student's t test,and logistic regression was performed.P<0.05 was considered statistically significant.RESULTS There were 132 patients(53.8%female),with a mean age was 15.9±1.3 years,and there was a disease evolution time of 4.49±0.88 years.The presence of anti-GAD65,anti-IA2,and anti-Zn8T positivity was found in 29.5%,18.2%,and 15.9%,respectively.Dividing the groups by early or no insulin dependence showed that the group with insulin had a higher frequency of antibody positivity:anti-GAD65 odds ratio(OR):2.42(1.112–5.303,P=0.026);anti-IA2:OR:1.55(0.859–2.818,P=0.105);and anti-Zn8T:OR:7.32(2.039–26.279,P=0.002).CONCLUSION Anti-GAD65 positivity was high in our study.Anti-GAD65 and anti-Zn8T positivity showed a significantly depleted beta cell reserve phenotype,leading to an increased risk of early insulin dependence.

How to implement a knowledge graph completeness assessment with the guidance of user requirements

In the context of big data, many large-scale knowledge graphs have emerged to effectively organize the explosive growth of web data on the Internet. To select suitable knowledge graphs for use from many knowledge graphs, quality assessment is particularly important. As an important thing of quality assessment, completeness assessment generally refers to the ratio of the current data volume to the total data volume.When evaluating the completeness of a knowledge graph, it is often necessary to refine the completeness dimension by setting different completeness metrics to produce more complete and understandable evaluation results for the knowledge graph.However, lack of awareness of requirements is the most problematic quality issue. In the actual evaluation process, the existing completeness metrics need to consider the actual application. Therefore, to accurately recommend suitable knowledge graphs to many users, it is particularly important to develop relevant measurement metrics and formulate measurement schemes for completeness. In this paper, we will first clarify the concept of completeness, establish each metric of completeness, and finally design a measurement proposal for the completeness of knowledge graphs.

Research Progress on Nutritional Requirements of Carp

Carp is a temperate freshwater fish native to Asia,distributed in all regions of the world except Australia and South America.With the improvement of comprehensive and healthy breeding technology of carp,the unit yield has been greatly increased mainly due to the exten-sive use of compound feed.In this study,the nutritional requirements of carp were summarized from the aspects of protein,amino acids,fat,carbohydrate,calcium and phosphorus,vitamins and taurine.This study provides a certain theoretical reference for scientific formula of carp feed.

Security and Privacy in Solar Insecticidal Lamps Internet of Things:Requirements and Challenges

Solar insecticidal lamps(SIL) can effectively control pests and reduce the use of pesticides. Combining SIL and Internet of Things(IoT) has formed a new type of agricultural IoT,known as SIL-IoT, which can improve the effectiveness of migratory phototropic pest control. However, since the SIL is connected to the Internet, it is vulnerable to various security issues.These issues can lead to serious consequences, such as tampering with the parameters of SIL, illegally starting and stopping SIL,etc. In this paper, we describe the overall security requirements of SIL-IoT and present an extensive survey of security and privacy solutions for SIL-IoT. We investigate the background and logical architecture of SIL-IoT, discuss SIL-IoT security scenarios, and analyze potential attacks. Starting from the security requirements of SIL-IoT we divide them into six categories, namely privacy, authentication, confidentiality, access control, availability,and integrity. Next, we describe the SIL-IoT privacy and security solutions, as well as the blockchain-based solutions. Based on the current survey, we finally discuss the challenges and future research directions of SIL-IoT.

Operational requirements analysis method based on question answering of WEKG

The weapon and equipment operational requirement analysis(WEORA) is a necessary condition to win a future war,among which the acquisition of knowledge about weapons and equipment is a great challenge. The main challenge is that the existing weapons and equipment data fails to carry out structured knowledge representation, and knowledge navigation based on natural language cannot efficiently support the WEORA. To solve above problem, this research proposes a method based on question answering(QA) of weapons and equipment knowledge graph(WEKG) to construct and navigate the knowledge related to weapons and equipment in the WEORA. This method firstly constructs the WEKG, and builds a neutral network-based QA system over the WEKG by means of semantic parsing for knowledge navigation. Finally, the method is evaluated and a chatbot on the QA system is developed for the WEORA. Our proposed method has good performance in the accuracy and efficiency of searching target knowledge, and can well assist the WEORA.

Macroscopic Traversable Wormholes: Minimum Requirements

While wormholes are just as good a prediction of Einstein’s theory as black holes, they are subject to severe restrictions from quantum field theory. To allow for the possibility of interstellar travel, a macroscopic wormhole would need to maintain sufficiently low radial tidal forces. It is proposed in this paper that the assumption of zero tidal forces, i.e., the limiting case, is sufficient for overcoming the restrictions from quantum field theory. The feasibility of this approach is subsequently discussed by 1) introducing the additional conditions needed to ensure that the radial tidal forces can indeed be sufficiently low and 2) by viewing traversable wormholes as emergent phenomena, thereby increasing the likelihood of their existence.

The Customer Requirements Analysis Method of Engineering Products Based on Multiple Preference Information

To effectively evaluate the fuzziness of the market environment in product planning,a customer requirements analysis method based on multiple preference information is proposed.Firstly,decision-makers use a preferred information form to evaluate the importance of each customer requirement.Secondly,a transfer function is employed to unify various forms of preference information into a fuzzy complementary judgment matrix.The ranking vector is then calculated using row and normalization methods,and the initial importance of customer requirements is obtained by aggregating the weights of decision members.Finally,the correction coefficients of initial importance and each demand are synthesized,and the importance of customer requirements is determined through normalization.The development example of the PE jaw crusher demonstrates the effectiveness and feasibility of the proposed method.

On the Assessment of Generative AI in Requirements Analysis and Modeling Tasks with UML:An Exploratory Study

Generative AI is rapidly employed by software developers to generate code or other software artifacts.However,the analysis and assessment of generative AI with respect to requirements analysis and modeling tasks,especially with UML,has received little attention.This paper investigates the capabilities of generative AI to aid in the creation of three types of UML models:UML use case models,class diagrams,and sequence diagrams.For this purpose,we designed an AI-aided UML modeling task in our course on software requirements modeling.50 undergraduates who majored in Software Engineering at Wuhan University completed the modeling task and the corresponding online survey.Our findings show that generative AI can help create these three types of UML models,but its performance is limited to identifying essential modeling elements of these UML models.

IoT for Streetlighting-Requirements for Modelling of Management Services-Part I

Energy conservation is the effort to reduce the overconsumption of energy by the usage of less energy services.Energy conservation could be user oriented or industry sector oriented.One of these sectors is the streetlighting-major energy consumer in the town-forming nearly 30%of each country’s consumption.Intelligent designed management of streetlighting not only reduces the energy consumption of the town,but also increases the public safety and the wellbeing.The article focuses the management of IoT for streetlighting in smart city.This is the first stage of project“Service management for IoT in streetlighting”.While the basic management principles are efficiency and fairness,the requirements of all actors must be defined.On the base of requirements,the authors synthesize the management functions with selected granularity.The chosen methodology is unified modelling language(UML):use case diagrams.The models are intended to business developers,university professors,and students.

An Approach towards Goal-Oriented Requirements Ontology: Consistency and Completeness Based Requirements Analysis

The paper presents a new approach to managing software requirement elicitation techniques with a high level of analyses based on domain ontology techniques, where we established a mapping between user scenario, structured requirement, and domain ontology techniques to improve many attributes such as requirement consistency, completeness and eliminating duplicate requirements to reduce risk of overrun time and budgets. One of the main targets of requirement engineering is to develop a requirement document with high quality. So, we proposed a user interface to collect all vital information about the project directly from the regular user and requirement engineering;After that, the proposal will generate an ontology based on semantic relations and rules. Requirements Engineering tries to keep requirements throughout a project’s life cycle consistent necessities clear, and up to date. This prototype allows mapping requirement scenarios into ontology elements for semantically interrupted. The general points of our prototype are to guarantee the identification requirements and improved nature of the Software Requirements Specification (SRS) by solving incomplete and conflicting information in the requirements specification.

Validation and performance of three scoring systems for predicting primary non-function and early allograft failure after liver transplantation

Background: Primary non-function(PNF) and early allograft failure(EAF) after liver transplantation(LT) seriously affect patient outcomes. In clinical practice, effective prognostic tools for early identifying recipients at high risk of PNF and EAF were urgently needed. Recently, the Model for Early Allograft Function(MEAF), PNF score by King's College(King-PNF) and Balance-and-Risk-Lactate(BAR-Lac) score were developed to assess the risks of PNF and EAF. This study aimed to externally validate and compare the prognostic performance of these three scores for predicting PNF and EAF. Methods: A retrospective study included 720 patients with primary LT between January 2015 and December 2020. MEAF, King-PNF and BAR-Lac scores were compared using receiver operating characteristic(ROC) and the net reclassification improvement(NRI) and integrated discrimination improvement(IDI) analyses. Results: Of all 720 patients, 28(3.9%) developed PNF and 67(9.3%) developed EAF in 3 months. The overall early allograft dysfunction(EAD) rate was 39.0%. The 3-month patient mortality was 8.6% while 1-year graft-failure-free survival was 89.2%. The median MEAF, King-PNF and BAR-Lac scores were 5.0(3.5–6.3),-2.1(-2.6 to-1.2), and 5.0(2.0–11.0), respectively. For predicting PNF, MEAF and King-PNF scores had excellent area under curves(AUCs) of 0.872 and 0.891, superior to BAR-Lac(AUC = 0.830). The NRI and IDI analyses confirmed that King-PNF score had the best performance in predicting PNF while MEAF served as a better predictor of EAD. The EAF risk curve and 1-year graft-failure-free survival curve showed that King-PNF was superior to MEAF and BAR-Lac scores for stratifying the risk of EAF. Conclusions: MEAF, King-PNF and BAR-Lac were validated as practical and effective risk assessment tools of PNF. King-PNF score outperformed MEAF and BAR-Lac in predicting PNF and EAF within 6 months. BAR-Lac score had a huge advantage in the prediction for PNF without post-transplant variables. Proper use of these scores will help early identify PNF, standardize grading of EAF and reasonably select clinical endpoints in relative studies.

Analysis of Test Methods for Parts to Follow Relative Requirements

Testing the parts of mechanical products and ensuring their accuracy to the design requirements are essential to products’ quality, market competitiveness and manufacturers’ maximum economical benefits from these products. One of the latest subjects of study in the area of precision measurement is the testing of parts to follow the relative requirements, viz. design requirements for the size tolerance of size features and related geometrical tolerances of the central feature, including the envelope requirement, maximum material requirement and least material requirement. The article analyzes test methods for parts to follow the envelope requirement or maximum material requirement, as well as further requirements of geometrical tolerances for its central feature. The method is effective in improving product quality and rejecting unqualified parts.

Professional Requirements for Contemporary Teachers

The rapid development of high-tech based information technology marks the era of a knowledge-based economy. This form of economy, characterized by knowledge, has raised new demands for most teachers. To rise to the challenge, teachers must maintain innovative attitudes and practical abilities that will meet the social requirements. The writer examines the professional requirements for contemporary teachers in this paper.

Dietary requirements of synthesizable amino acids by animals:a paradigm shift in protein nutrition

Amino acids are building blocks for proteins in all animals. Based on growth or nitrogen balance, amino acids were traditionally classified as nutritionally essential or nonessential for mammals, birds and fish. It was assumed that all the ＂nutritionally nonessential amino acids （NEAA）＂ were synthesized sufficiently in the body to meet the needs for maximal growth and optimal health. However, careful analysis of the scientific literature reveals that over the past century there has not been compelling experimental evidence to support this assumption. NEAA （e.g., glutamine, glutamate, proline, glycine and arginine） play important roles in regulating gene expression, cell signaling, antioxidative responses, fertility, neurotransmission, and immunity. Additionally, glutamate, glutamine and aspartate are major metabolic fuels for the small intestine to maintain its digestive function and to protect the integrity of the intestinal mucosa. Thus, diets for animals must contain all NEAA to optimize their survival, growth, development, reproduction, and health. Furthermore, NEAA should be taken into consideration in revising the ＂ideal protein＂ concept that is currently used to formulate swine and poultry diets. Adequate provision of all amino acids （including NEAA） in diets enhances the efficiency of animal production. In this regard, amino acids should not be classified as nutritionally essential or nonessential in animal or human nutrition. The new Texas A＆M University＇s optimal ratios of dietary amino acids for swine and chickens are expected to beneficially reduce dietary protein content and improve the efficiency of their nutrient utilization, growth, and production performance.

Specifying Requirements of Real-Time System with Rules and Templates

This paper presents a model specifying requirements of real-time systems. Different from existing researches, this model mainly uses rules and templates to represent hierarchical FSMs (Finite State Machine). In this model, one rule corresponds to one state transition of FSM and one template corresponds to one FSM. Rules and information with respect to a FSM can be written in a template. So templates include not only state diagrams, but also information that can not be described by FSM, such as performance requirements. The specification using this model consists of a collection of templates and it is easy for users to understand and to review. After introduced the related researches and principles of the model, this paper specifies requirements of a real-time system with this model, and discusses characters of this model in the end.

Practical starter pig amino acid requirements in relation to immunity,gut health and growth performance

Immune system activation begins a host of physiological responses. Infectious agents are recognized by monocytes and macrophages which in turn stimulate cytokine production. It is the hormone-like factors called cytokines that orchestrate the immune response. The classic responses observed with immune system activation and cytokine production include： anorexia, fever, lethargy, recruitment of other immune cells, and phagocytosis. While production of immune system components is known to require some amino acids, increases in amino acid requirements are more than offset by the associated decrease in protein accretion and increased muscle protein degradation that also accompanies immune system activation. However, the biggest impact of cytokine production is a decrease in feed intake. Therefore, as feed intake decreases, the energy needed to drive protein synthesis is also decreased. This suggests that diets should still be formulated on a similar calorie：lysine ratio as those formulated for non-immune challenged pigs. The evidence is sparse or equivocal for increasing nutrient requirements during an immune challenge. Nutritionists and swine producers should resist the pressure to alter the diet, limit feed, or add expensive feed additives during an immune challenge. While immune stimulation does not necessitate changes in diet formulation, when pigs are challenged with non-pathogenic diarrhea there are potential advantages on gut health with the increased use of crystalline amino acids rather than intact protein sources （i.e., soybean meal）. This is because reducing crude protein decreases the quantity of fermentable protein entering the large intestine, which lowers post weaning diarrhea. It also lowers the requirement for expensive specialty protein sources or other protein sources such as soybean meal that present immunological challenges to the gut. The objective of this review is two-fold. The first is to discuss immunity by nutrition interactions, or lack thereof, and secondly, to review amino acid requirement estimates for nursery pigs.

Applying CBR to Machine Tool Product Configuration Design Oriented to Customer Requirements

Product customization is a trend in the current market-oriented manufacturing environment. However, deduction from customer requirements to design results and evaluation of design alternatives are still heavily reliant on the designer＇s experience and knowledge. To solve the problem of fuzziness and uncertainty of customer requirements in product configuration, an analysis method based on the grey rough model is presented. The customer requirements can be converted into technical characteristics effectively. In addition, an optimization decision model for product planning is established to help the enterprises select the key technical characteristics under the constraints of cost and time to serve the customer to maximal satisfaction. A new case retrieval approach that combines the self-organizing map and fuzzy similarity priority ratio method is proposed in case-based design. The self-organizing map can reduce the retrieval range and increase the retrieval efficiency, and the fuzzy similarity priority ratio method can evaluate the similarity of cases comprehensively. To ensure that the final case has the based on grey correlation analysis is proposed to evaluate similar cases best overall performance, an evaluation method of similar cases to select the most suitable case. Furthermore, a computer-aided system is developed using MATLAB GUI to assist the product configuration design. The actual example and result on an ETC series machine tool product show that the proposed method is effective, rapid and accurate in the process of product configuration. The proposed methodology provides a detailed instruction for the product configuration design oriented to customer requirements.