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.

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.

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.

Water quantity-quality combined evaluation method for rivers＇ water requirements of the instream environment in dualistic water cycle： A case study of Liaohe River Basin

In this article the meaning of the quantity and quality of environmental flows of river in dualistic water cycle is discussed, and compared with the meaning of unitary water cycle. Based on the analysis of the relationship between environmental flows of river requirements, the efficiency of water resource usage, the consumption coefficient, and the concentration of waste water elimination, the water quantity and water quality calculation method of the environmental flows of river requirements in dualistic water cycle is developed, and the criteria for environmental flows of river requirements are established, and therefore the water quantity-quality combined evaluation of natural river flows requirements are realized Taking the Liaohe River as a model, the environmental flows of river requirements for Xiliao River, Dongliao River, mainstream Liaohe River, Huntai River and northeast rivers along the coasts of the Yellow and Bohai seas in unitary water cycle are calculated, each taking up 39.3%, 63.0%, 43.9%, 43.3% and 43.5% of runoff respectively. Evaluated according to Tennant recommended flow, the results show that： except Xiliao River is ＂median＂, the rest are all upon ＂good＂, the Dongliao River is even ＂very good＂. The corresponding results in dualistic water cycle are that, the proportion of natural flows for each river is 57.5%, 74.1%, 60.8%, 60.3% and 60.4%; while the combined evaluation results show that： considering ＂quantity＂, except Xiliao River, the rest rivers can all achieve the ＂quantity＂ criteria of the en- vironmental flows of river requirements, but if considering the aspect of ＂quality＂, only Dongliao River can reach the ＂quality＂ standard. By water quantity-quality combined evaluation method, only Dongliao River can achieve the criteria. So the water quality is the main factor that determines whether the environmental flows can meet the river ecosystem demands.

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.

类风湿关节炎合并骨关节炎病人血清anti-Sa、anti-CCP水平与骨关节损伤、全身炎症反应的相关性分析

目的:分析类风湿关节炎(RA)病人血清anti-Sa、anti-CCP抗体水平与其骨关节损伤、全身炎症反应的相关性。方法:选择RA合并骨关节损伤病人108例,根据血清anti-Sa、anti-CCP抗体水平分别列入高anti-Sa组和低anti-Sa组、高anti-CCP组和低anti-CCP组。比较各组病人WOMAC骨性关节炎指数、lysholms膝关节功能评分值,血清白细胞介素(IL)-1β、IL-6、IL-27、肿瘤坏死因子α(TNF-α)水平。采用Pearson检验评估有关指标的相关性。结果:高anti-Sa组、高anti-CCP组病人的WOMAC骨性关节炎指数明显高于低anti-Sa组(P<0.01),lysholms膝关节功能评分明显低于低anti-Sa组(P<0.01);血清中IL-1β、IL-6、IL-27、TNF-α的水平明显高于低anti-CCP组(P<0.01)。RA病人血清anti-Sa、anti-CCP抗体水平与骨关节损伤、全身炎症反应严重程度呈正相关关系(P<0.05~P<0.01),与lysholms膝关节功能评分呈负相关关系(P<0.01)。结论:RA病人血清中anti-Sa、anti-CCP抗体水平显著升高与关节损伤及全身炎症反应有一定的相关性,可作为临床判断病情活动性与骨关节损伤的参考指标。

Building Requirements Semantics for Networked Software Interoperability

Naturally, like the web, integrated software systems in Internet will have to be distributed and heterogeneous. To im-prove the interoperability of services for SAAS, it is crucial to build requirements semantics that will cross the entire lifecycle of services especially on requirements stage. In this paper, a requirements semantics interoperability extend-ing approach called Connecting Ontologies (CO) that will act as semantics information carrier designing to facilitate the requirements identification and services composition is proposed. Semantic measurement of Chinese scenario is explored. By adopting the approach, a series of tools support for transport domain are developed and applied based on CO and DPO (Domain Problem Ontology) to enforce requirements engineering of networked software efficiently.

Antibody Pattern: Correlation of Age and Gender in ANA and Anti-ds-DNA Prevalence

The study was designed to find the prevalence of ANA antibodies and anti-dsDNA antibodies in samples tested at AFIP Rawalpindi and their correlation with age and gender and to find positive and negative predictive values of ANA antibodies.For this purpose,twelve thousand nine hundred sixty-seven(12,967)patients were analyzed for ANA with four hundred sixty-eight(468)healthy samples tested as control and four thousand seven hundred three(4,703)patients tested for ds-DNA antibodies.Retrospective data of all samples tested by indirect immunofluorescence(IF)for ANA antibodies and dsDNA antibodies was collected.To address positive and negative predictive values another control group(autoimmunity not suspected)of serum samples was taken from the healthy population.For the first group,age,gender,ANA antibodies and ds-DNA antibodies results(both tests performed by IIF)data was collected from a computer record cell;for the second control group,ANA antibodies were performed by IIF.12,967 and 4,703 samples(Group 1)were tested for ANA antibodies and dsDNA antibodies,respectively,during this period.1,119(9%)and 99(2%)were found positive for ANA antibodies and ds DNA antibodies.Among these positive samples,850(76%)and 73(74%)were females respectively.Gender predisposition towards autoimmunity(ANA)was found significant with a P value of(P=0.001).Relation of age was also found significant with anti-ANA antibodies with a P value of(P=0.001).This study shows a negative correlation between age(P=0.025)and gender(P=0.001)with anti-dsDNA which is also significant.High prevalence was found below the mean age of 38 years(SD±16.635)for ANA antibodies and the mean age of 35 years(SD±15.066)for ds-DNA antibodies.The age of ANA antibodies and dsDNA antibodies positive patients ranged from 1 year old to 98 years old and 2 years old to 95 years old respectively.In the second(autoimmunity-free)control group,a total of 468 samples were tested for ANA antibodies and 9(2%)were found positive.Positive predictive value(PPV)was 8.6%and negative predictive value(NPV)was 98%.ANA is a sensitive test for autoimmunity and it is significantly related to female gender and increasing age.The low prevalence of ANA antibodies among clinically suspected cases suggests that rationalization of test prescriptions is needed.Anti-ds-DNA is also a sensitive test for diagnosis of SLE and it is significantly related to female gender and increasing age.

基于特征信息融合预测Anti-CRISPR蛋白

CRISPR-Cas系统是一种存在于细菌和古细菌中的获得性免疫系统,作为基因编辑工具在癌症治疗等方面被广泛研究,但CRISPR-Cas基因编辑技术存在基因脱靶效应。研究发现,Anti-CRISPR蛋白是一种可以调节CRISPR-Cas系统功能的蛋白质,在不破坏靶向基因编辑的情况下,可以减少脱靶效应等不良影响,从而提高基因编辑技术的效率和安全性。因此,研究Anti-CRISPR蛋白对于理解CRISPR-Cas系统的功能和细菌-病毒相互作用具有重要意义。本文构建了Anti-CRISPR蛋白数据集,提取氨基酸组分、氨基酸二肽组分、g-gap二肽组成、蛋白质二级结构、平均化学位移和蛋白质骨架6种特征参数,利用支持向量机对Anti-CRISPRs蛋白进行预测,在Jackknife检验下,单特征参数最高预测成功率为93.50%;对维度过高的氨基酸二肽组分和g-gap二肽组成分别进行降维处理,得到g-gap二肽组成在g=3、维数是121维时预测成功率最高,为95.10%,进一步研究发现有16种g-gap二肽组合对应11种氨基酸与Anti-CRISPR蛋白预测相关度较大;最后对特征参数进行融合,融合后最高预测成功率为96.07%。

基于YOLOv5s-AntiUAV的反无人机目标检测算法研究

随着无人机的应用领域不断拓展,无人机的“黑飞”给公共安全造成严重损害。为解决侵入式无人机小目标在复杂飞行环境下的错检和漏检问题,提出基于YOLOv5s-AntiUAV的反无人机目标检测算法。首先,引入结合深度超参数卷积的Slim-Neck范式,增强算法特征提取能力并保持计算效率。其次,在骨干和颈部网络引入SPD-Conv模块,提高在低分辨率图像中小目标的检测性能。最后,用Alpha-CIoU替换YOLOv5s算法中的CIoU,增强算法泛用性。YOLOv5s-AntiUAV算法与YOLOv5s、SSD和Faster R-CNN算法在数据集Anti-UAV上的对比实验结果表明,改进算法的mAP@0.5值分别增长了1.1、12.1和4.9个百分点,凸显其实用性。由在VisDrone2019数据集上进行的迁移实验显示,相较于YOLOv5s算法,改进算法mAP@0.5值提升了4.5个百分点,表明其相较于原算法具有更强的鲁棒性。

Safety and in Vivo Anti-Inflammatory Activity of Ethanolic Extract of Ficus umbellata (Vahl.) Leaves

Toxicity is the totality of adverse effects, which can be functional and morphological lesions in a living organism, caused by a substance introduced in relatively high single doses or in small, repeated doses. The aim of this study was to assess the OECD-recommended acute oral toxicity and anti-inflammatory activity of ethanolic extract of Ficus umbellata leaves. Animals were given a single oral dose of 1000, 3000 and 5000 mg/Kg body weight (BW) of the extract. For the anti-inflammatory activity test, rats were given the ethanolic extract of F. umbellata leaves at doses of 100, 300 and 500 mg/Kg or aspirin® at a concentration of 100 mg/Kg PC orally, one hour before injection of 0.05 ml of 1% formalin under the plantar fascia of the rat’s right hind paw. Paw volume measurements were taken one, two and three hours after formalin injection, using an electronic caliper. After 14 days of observation, no deaths were observed in treated rats. The LD50 of ethanolic extract of Ficus umbellata leaf powder is greater than 5000 mg/Kg body weight. This extract has no significant effects on hematological parameters and on the main markers of nephrotoxicity and hepatotoxicity for a single dose of less than 5000 mg/Kg PC. It reduces formalin-induced edema. Evaluation of the percentage inhibition showed that the extract had greater anti-inflammatory activity at 3 hours after the start of the experiment. However, better inhibition of inflammatory oedema of the paw of rats treated with 500 mg/Kg was observed at 5 hours after the start of the experiment, with a percentage inhibition of 69.23 ± 1.02, compared with the reference group treated with aspirin® 100 mg/Kg, which showed an inhibition of 63.50 ± 0.98. These results show that F. umbellata leaves possess anti-inflammatory activity, which would justify their use in traditional African medicine to prevent or treat inflammation.

Implications for Antigravity Tests of Dirac’s Negative Energy Antiparticles

P. A. M. Dirac conceived antimatter in 1928 as having negative energy by allowing a consistent representation of matter-antimatter annihilation into light. To achieve compatibility with special relativity, particle physics of the early 20th century made the theoretical assumption that antiparticles have positive energy, an assumption that remains in effect as of today. In this note we prove apparently for the first time a theorem stating that positive mass antiparticles violate Dirac’s particle-antiparticle annihilation into light. We then show the consequential unsettled character of the recent gravity test of the anti-Hydrogen atom due to the positive mass of its nucleus. We conclude by suggesting that a final scientific claim on matter-antimatter gravity requires tests on particles with clear antimatter character, such as the 1994 resolutory proposal for the comparative test of the gravity of very low energy electron and positron in horizontal flight on a supercooled vacuum tube.

31 Plant Species against Blood Feeding and Disease Vectors Insects: Beyond Anti-Insect Properties, Unvalued Opportunities and Challenges for Health and Sustainability

Plants with bioactive properties are greatly useful in preventing and controlling blood-sucking and disease-vector invertebrates, particularly in developing countries and low-income communities. Their application is a promising alternative to synthetic compounds whose use remains a health, environmental, and economic challenge. However, many are still unknown and unvalued, while others are becoming ignored and threatened. The main objective of this ethnobotanical study is to identify and characterize indigenous and locally grown plants against blood-sucking and disease-vector insects. Salient opportunities and challenges of using these plants are documented and discussed. Semi-structured interviews, using a prepared questionnaire, were conducted with 228 informants. The consensus index (CI) was calculated to analyze the reliability of the collected information. The identified 31 anti-insect plant species belong to 20 botanical families, four morphological categories, and six habitat types. They can be categorized as insecticidal plants (42% of the total), insect repellent (42% of the total), and both insecticidal and insect repellent (16% of the total). More than 54% of these are still abundant in the study area, while about 35.5% have become rare and difficultly accessible. Based on the numerical importance of related anti-insect plant species, the seven targeted blood-sucking insects range in the following decreasing order: Jiggers (16 species) > Fire Ants (9 species) > Flies (8 plants) > Mosquitoes (4 species) > Fleas (2 species) > Bedbugs (1 species) > lice (0 species). The three most commonly used plants, with the highest confirmation indices, are Tetradenia riparia (ICs = 0.712), Eucalyptus globulus subsp. maidenii (ICs = 0.302), and Solanum aculeastrum (ICs = 0.288). The antimicrobial role of many locally grown anti-insect plants and the multiple other associated valorization possibilities are ignored by most informants. Domesticating, propagating, protecting, and promoting the sustainable use of these plants would be an appropriate route for their conservation and continued availability.