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.

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.

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.

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.

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.

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.

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.

Empirical Analysis of Software Success Rate Forecasting During Requirement Engineering Processes

Forecasting on success or failure of software has become an interesting and,in fact,an essential task in the software development industry.In order to explore the latest data on successes and failures,this research focused on certain questions such as is early phase of the software development life cycle better than later phases in predicting software success and avoiding high rework?What human factors contribute to success or failure of a software?What software practices are used by the industry practitioners to achieve high quality of software in their day-to-day work?In order to conduct this empirical analysis a total of 104 practitioners were recruited to determine how human factors,misinterpretation,and miscommunication of requirements and decision-making processes play their roles in software success forecasting.We discussed a potential relationship between forecasting of software success or failure and the development processes.We noticed that experienced participants had more confidence in their practices and responded to the questionnaire in this empirical study,and they were more likely to rate software success forecasting linking to the development processes.Our analysis also shows that cognitive bias is the central human factor that negatively affects forecasting of software success rate.The results of this empirical study also validated that requirements’misinterpretation and miscommunication were themain causes behind software systems’failure.It has been seen that reliable,relevant,and trustworthy sources of information help in decision-making to predict software systems’success in the software industry.This empirical study highlights a need for other software practitioners to avoid such bias while working on software projects.Future investigation can be performed to identify the other human factors that may impact software systems’success.

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.

Requirement Engineering for E-Coaching in Higher Education

This paper presents a requirement engineering for developing an e-coaching environment in the higher education sector. This research demonstrates that IT experts encounter challenges in establishing a system that matches a university’s expectations, as they are usually uncertain about its goals and system requirements. The paper illustrates a business goal-focused requirement induction technique, which encompasses demonstrating the business procedures through Business Process Modelling Notation (BPMN), assessing the university goals via the tree diagram, and drawing out the system requirements from the university objectives through UML state diagrams. A case study of supporting the development of a new IT course is used as a case study and applied using BPMN.

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.

基于MBSE的地空导弹总体方案设计

为了适应未来大型复杂系统设计与功能分析需求,在导弹设计中引入基于模型的系统工程(MBSE)思想,提出了基于MBSE的地空导弹总体设计流程。首先,明确地空导弹利益相关者的需求,定义导弹任务场景;基于设计需求开展功能分析,利用导弹任务场景进行功能分解,完成需求到功能的转化;根据导弹的系统功能映射出导弹架构组成,开展地空导弹系统的逻辑架构设计和物理架构设计,最终得到导弹总体设计方案,并针对导弹方案进行验证及优化,初步实现了地空导弹的总体设计过程。

基于有限谓词追踪的民机系统需求一致性检查方法

针对民机安全关键系统在正向研发过程中,系统级需求的正确性难以在设计早期全部完成确认的问题,提出一种基于有限谓词追踪的功能需求一致性检查体系。首先,引入一阶逻辑中的谓词追踪,建立系统内部功能需求与交互功能需求形式化规约方法。其次,针对单条、多条需求内容正确性以及需求关系一致性,构建需求一致性检查形式化规约,开展需求自冲突、集冲突与需求关系一致性检验,并生成可解释的检查反例进行需求迭代。最后,以机载平视显示(head-up display,HUD)系统飞行信息符号生成与显示功能为例,验证该方法的正确性与有效性。研究结果表明,基于有限谓词追踪的功能需求一致性检查方法能够提高需求一致性检查效率、降低研发成本,为民机系统级需求确认提供支持。

服装个性化定制中信息技术的应用与展望

随着人们个性化需求的不断增加,服装个性化定制已成为时尚发展趋势之一。信息技术在推动服装个性化定制发展中扮演着重要的角色,可以收集和处理用户的个性化信息,并将其转化为具体的设计和生产方案。文章首先对服装产业信息技术的研究进展进行总结,阐述新一代信息技术在服装产业的应用情况;其次分析了信息技术在服装个性化定制领域的应用现状,按照定制流程分别总结信息技术在提高生产效率、降低成本和满足用户需求方面的优势及不足;最后根据目前服装个性化定制在数据共享、协同设计和柔性生产等方面的需求,从建模技术和系统平台构建两个方面对服装个性化定制发展进行展望。

上海地区梨品种需冷量及需热量研究

以上海地区4个梨品种为研究对象,采用不同模型测试其需冷量及需热量。结果表明:梨品种的需冷量在≤7.2℃模型下为191—518 h、0—7.2℃模型下为171—394 h、犹他模型下为138—192 C·U(‘翠冠’除外),‘翠冠’需冷量最低,其次为‘沪晶梨18号’和‘沪晶梨67号’,需冷量最高的是‘早生新水’;需热量在生长度小时模型下为10456—10781 GDH·℃,‘早生新水’需热量最低,其次为‘翠冠’,需热量最高的为‘沪晶梨18号’和‘沪晶梨67号’;有效积温模型为187—240 D·℃,‘翠冠’的需热量最低,其他品种间无明显差异。上海地区的梨品种的需冷量估算,优先推荐使用0—7.2℃模型,犹他模型更适用于需冷量高的梨品种,生长度小时模型比有效积温模型更适合梨需热量估算。

2023年版《理工科类大学物理课程教学基本要求》内容细化修订解读

本文介绍了对2010年版《理工科类大学物理课程教学基本要求》修订的意义和过程,并对2023年版《理工科类大学物理课程教学基本要求》中修订内容进行了解读。

基于预防医学专业核心价值的课程思政教育研究

目前,疾病防控与健康促进对预防医学专业教育教学改革提出了新要求。在分析预防医学专业教育的问题、开展课程思政教育必要性的基础上,构建预防医学专业核心价值体系,包括价值取向(维护和保障人民健康)、伦理道德(为了每个人健康生活)、时代使命(构建大卫生大健康的公共卫生体系)、职业要求(建设健康中国、服务大众健康)。围绕专业核心价值挖掘各门课程中的课程思政元素;开展多种课程思政教育实践方法,包括将思政教育元素融入微视频中、融入课堂教学改革中,开展主题活动实践,与创新创业教育深度融合;并统筹协调各专业课程之间的教育实践方法;从学生的课程总结、考试、章节测验中检验课程思政教育效果。基于以上努力,取得了良好的课程思政教育成效。

数据和需求双重驱动的高校图书馆精细化科研评价服务研究--以北京师范大学图书馆为例

文章以北京师范大学图书馆为例,介绍了数据和需求双重驱动的精细化科研评价服务实践和取得的创新与突破,梳理了全生命周期科研成果数据管理方案,总结了基于管理决策需求、学科和学院需求、学术研究需求、人才评估需求和社会用户需求形成的多元科研评价需求体系,以及在此基础上提供的评价服务。旨在分享交流高校图书馆科研评价服务的经验,为提高服务质量,促进高校加强科研管理,以及进一步开展相关问题研究提供思路和参考。