23 research outputs found

    NL-based automated software requirements elicitation and specification

    Get PDF
    This paper presents a novel approach to automate the process of software requirements elicitation and specification. The software requirements elicitation is perhaps the most important phase of software development as a small error at this stage can result in absurd software designs and implementations. The automation of the initial phase (such as requirement elicitation) phase can also contribute to a long standing challenge of automated software development. The presented approach is based on Semantic of Business Vocabulary and Rules (SBVR), an OMG’s recent standard. We have also developed a prototype tool SR-Elicitor (an Eclipse plugin), which can be used by software engineers to record and automatically transform the natural language software requirements to SBVR software requirements specification. The major contribution of the presented research is to demonstrate the potential of SBVR based approach, implemented in a prototype tool, proposed to improve the process of requirements elicitation and specification

    Internet of things (IoT) assisted soil salinity mapping at irrigation schema level

    Get PDF
    Soil salinity accumulates a high concentration of salts in soils that interfere with normal plant growth. Early detection and quantification of soil salinity are essential to effectively deal with soil salinity in agriculture. Soil salinity quantification and mapping at the irrigation scheme level are vital to evaluating saline soil's reclamation activity. Existing solutions of salinity mapping are costly, time-consuming, and inadequate for applications at the irrigation scheme level. Internet of Things (IoT) assisted salinity mapping at the irrigation scheme level is proposed to quantify and map the soil salinity in agriculture. The proposed IoT-assisted salinity mapping characterizes the soil salinity in terms of Electric Conductivity, pH, and Total Dissolved Salts. The proposed IoT-assisted salinity mapping effectively observes impacts of reclamation activities in saline soil by frequent observation of soil salinity cost-effectively. The accuracy of proposed IoT-assisted salinity mapping is evaluated against the standard method of salinity measurements. The proposed IoT-assisted salinity mapping is cost-effective, and portable, which is very useful for site-specific treatments and soil zones management in saline soils

    Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

    Get PDF
    Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

    A web smart space framework for information mining: a base for intelligent search engines

    No full text
    A web smart space is an intelligent environment which has additional capability of searching the information smartly and efficiently. New advancements like dynamic web contents generation has increased the size of web repositories. Among so many modern software analysis requirements, one is to search information from the given repository. But useful information extraction is a troublesome hitch due to the multi-lingual; base of the web data collection. The issue of semantic based information searching has become a standoff due to the inconsistencies and variations in the characteristics of the data. In the accomplished research, a web smart space framework has been proposed which introduces front end processing for a search engine to make the information retrieval process more intelligent and accurate. In orthodox searching anatomies, searching is performed only by using pattern matching technique and consequently a large number of irrelevant results are generated. The projected framework has insightful ability to improve this drawback and returns efficient outcomes. Designed framework gets text input from the user in the form complete question, understands the input and generates the meanings. Search engine searches on the basis of the information provided

    A controlled Natural Language Interface to Class Models

    No full text
    The available approaches for automatically generating class models from natural language (NL) software requirements specifications (SRS) exhibit less accuracy due to informal nature of NL such as English. In the automated class model generation, a higher accuracy can be achieved by overcoming the inherent syntactic ambiguities and semantic inconsistencies in English. In this paper, we propose a SBVR based approach to generate an unambiguous representation of NL software requirements. The presented approach works as the user inputs the English specification of software requirements and the approach processes input English to extract SBVR vocabulary and generate a SBVR representation in the form of SBVR rules. Then, SBVR rules are semantically analyzed to extract OO information and finally OO information is mapped to a class model. The presented approach is also presented in a prototype tool NL2SBVRviaSBVR that is an Eclipse plugin and a proof of concept. A case study has also been solved to show that the use of SBVR in automated generation of class models from NL software requirements improves accuracy and consistency

    Aligning Textual and Graphical Descriptions of Processes Through ILP Techniques

    No full text
    With the aim of having individuals from different backgrounds and expertise levels examine the operations in an organization, different representations of business processes are maintained. To have these different representations aligned is not only a desired feature, but also a real challenge due to the contrasting nature of each process representation. In this paper we present an efficient technique for aligning a textual description and a graphical model of a process. The technique is grounded on using natural language processing techniques to extract linguistic features of each representation, and encode the search as a mathematical optimization encoded using Integer Linear Programming (ILP) whose resolution ensures an optimal alignment between both descriptions. The technique has been implemented and the experiments witness the significance of the approach with respect to the state-of-the-art technique for the same task.Peer Reviewe

    Dystonic Movement Disorders in Children

    No full text
    Bei den Dystonien handelt es sich um eine heterogene Gruppe verschiedenartiger Erkrankungen mit ähnlichen Symptomen. Klassifikation, Differenzialdiagnosen und Therapien sind komplex und sollten von spezialisierten Zentren durchgeführt werden. Die Erkrankungen können vom Säuglings- bis ins späte Erwachsenenalter auftreten. Das Spektrum reicht von oligosymptomatischen Formen bis hin zu solchen, die schwerste Beeinträchtigungen in der Lebensqualität und Behinderungen bedingen können. Zur konservativen Therapie werden Krankengymnastik, orale Medikamente sowie lokale Injektionsbehandlungen eingesetzt. Von neurochirurgisch operativer Seite existieren die Neuromodulationstherapien (implantierbare Pumpen, Tiefe Hirnstimulation) sowie ablative Verfahren. Die neuere Literatur zeigt, dass insbesondere die kognitive Entwicklung bei Kindern umso günstiger beeinflusst werden kann, je früher eine effektive Therapie erfolgt
    corecore